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Can Blockchain Change The Game Of Data Analytics And Data Science?

June 1, 2022 | 378 views

Can Blockchain Change The Game Of Data Analytics And Data Science?
Blockchain has been causing ripples across major industries and verticals in the recent couple of years. We are seeing the future potential of blockchain technology that is scaling beyond just cryptocurrencies and trading.

It is only natural that Blockchain is going to have a huge impact on Data Analytics, another field that has been booming and seems to continue in the same trajectory for the foreseeable future.

However, very little research has been done on the implications of blockchain on Data Science or the potential of Data Science in Blockchain.

While Blockchain is about validating data and data science is about predictions and patterns, they are linked together by the fact that they both use algorithms to control interactions between various data points.

Blockchain in Big Data Analytics

Big Data has traditionally been a very centralized method where we had to collate data from various sources and bring it together in one place. Blockchain, considering its decentralized nature can potentially allow analysis of data to happen at the origin nodes of individual sources.

Also, considering that all data parsed through blockchain is validated across networks in a fool proof manner, the data integrity is ensured. This can be a game changer for analytics.

With the digital age creating so many new data points and making data more accessible than ever, the need for diving into depth with advanced analytics has been realized by businesses around the world. However, the data is still not organized and it takes a very long time to bring them together to make sense of it.

The other key challenge in Big Data remains data security. Centralized systems historically have been known for their vulnerability for leaks and hacks.

A decentralized infrastructure can address both of the above challenges enabling data scientists to build a robust infrastructure to build a predictive data model and also giving rise to new possibilities for more real time analysis.

Can Blockchain Enhance Data Science?

Blockchain can address some of the key aspects of Data Science and Analytics.

Data Security & Encoding:

The smart contracts ensure that no transaction can be reversed or hidden. The complex mathematical algorithms that form the base of Blockchain are built to encrypt every single transaction on the ledger.

Origin Tracing & Integrity:

Blockchain technology is known for enabling P2P relationships. With blockchain technology, the ledgers can be transparent channels where the data flowing through it is validated and every stakeholder involved in the process is made accountable and accessible. This also enables the data to be of higher quality than what was possible with traditional methods.

Summing Up

Data science itself is fairly new and advancing in recent years. Blockchain Technology, as advanced as it seems, is still at what is believed to be a very nascent stage. We have been seeing an increasing interest in data being moved to the cloud and it is only a matter of time when businesses will want it to be moved to decentralized networks.

On the other hand, blockchain’s network and server requirements are still not addressed and data analytics can be very heavy on the network, considering the volume of data collected for analysis. With very small volumes of data stored in blocks, we need viable solutions to make sure data analysis in blockchain is possible at scale.

At Pyramidion, we have been working with clients globally on some exciting blockchain projects. These projects are being led by visionaries, who are looking to change how the world functions, for good. Being at the forefront of innovation, where we see the best minds working on new technologies, ICOs and protocols, we strongly believe it is only a matter of time before the challenges are addressed and Blockchain starts being a great asset to another rapidly growing field like Data Science and Data Analytics.

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Masergy owns and operates the largest independent Software Defined Platform in the world, delivering hybrid networking, managed security and cloud communication solutions to enterprises around the globe. Our platform leverages advanced technologies including software defined networking, network function virtualization, advanced machine learning, and big data analytics to drive the flexibility, visibility, and control that enterprise IT teams require. By simplifying complexity through automation, we design, deploy, modify and manage these essential solutions…

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Business Intelligence, Big Data Management, Big Data

Choose the Right BI Solution: Top Business Intelligence Companies

Article | July 4, 2023

Explore the top business intelligence and analytics solution providers and discover how these tailored and innovative BI solutions meet the unique needs of organizations across various sectors. Organizations constantly seek innovative solutions to unlock the power of their data and extract valuable insights. In this data-driven space, business intelligence and analytics solutions have become indispensable tools for navigating the complexities of data analysis. These BI solutions empower businesses to explore, analyze, and visualize their data, providing actionable insights, trend identification, and driving overall business success. This article delves into the realm of business intelligence and analytics, highlighting the key players in the industry and showcasing their distinct offerings and capabilities. From scalable analytics on big data platforms to interactive visualizations and real-time insights, these BI solutions cater to the diverse needs of organizations across various industries. With a wide array of solution providers to choose from, organizations have the opportunity to select the solution that best aligns with their unique requirements, enabling them to master BI and fully unleash the potential of their data resources. 1. Yellowfin BI Yellowfin BI is a prominent business intelligence solutions provider known for its user-friendly analytics platform. It sets itself apart by emphasizing simplicity and intuitive design, making it easy for users to navigate and leverage the power of analytics. The platform offers interactive dashboards, real-time data updates, and advanced data visualization tools. It also supports collaborative analytics and data storytelling, empowering users to create compelling narratives that communicate insights collectively. Furthermore, the mobile access feature ensures that users can stay connected to their data even while on the move, enabling timely decision-making. Data security is a top priority for Yellowfin BI, offering robust features such as role-based access controls and encryption. These measures ensure that data remains secure and protected throughout the analytics process. 2. GoodData GoodData is a leading business intelligence company, renowned for its cloud-based analytics platform. The platform offers a comprehensive range of features designed to meet the diverse needs of businesses. It seamlessly combines data integration, visualization, and reporting capabilities, allowing organizations to make sense of their data and derive valuable insights. GoodData excels in connecting with various data sources, whether internal or external and consolidating them into a unified view for analysis. Additionally, the platform goes beyond traditional analytics by providing robust tools and APIs that allow businesses to embed analytics directly into their applications or customer-facing portals. This seamless integration empowers users to access data insights within their existing workflows. Moreover, GoodData prioritizes data security and compliance, offering features such as role-based access controls, data encryption, and audit logs to protect sensitive information. 3. Pyramid Analytics Pyramid is a trusted business intelligence solutions provider. Its Decision Intelligence Platform offers a seamless and efficient decision-making environment. The AI-driven platform integrates data preparation, business analytics, and data science into a unified environment, enabling businesses to fully leverage their data assets and address challenges posed by data silos and disparate self-service analytics tools. Pyramid simplifies complex data landscapes by harnessing artificial intelligence to streamline decision-making processes. In addition, the platform strongly emphasizes enterprise-level collaboration and governance, offering a centralized hub for teams to collaborate, share insights, and ensure data consistency throughout the organization. 4. AtScale AtScale is a business intelligence company specializing in data virtualization and analytics. The company enables organizations to leverage the power of big data by creating a unified and simplified view of their data infrastructure. AtScale's unique offering lies in its ability to provide a semantic layer that abstracts the complexities of underlying data sources, making it easier for users to access and analyze data without requiring extensive technical skills. By virtualizing data, AtScale eliminates the need for data replication, reducing storage costs and ensuring data consistency across the organization. The platform supports a wide range of data platforms and cloud providers, allowing businesses to seamlessly connect and analyze data from various sources. AtScale also offers advanced analytics capabilities, including OLAP (Online Analytical Processing) and multidimensional analysis, empowering users to derive valuable insights from their data. 5. DataWeave DataWeave is an advanced Software-as-a-Service (SaaS) solutions provider that offers a digital commerce analytics platform for consumer brands and retailers. Through the platform’s digital shelf analytics capabilities, brands can effectively measure and optimize key performance indicators (KPIs) such as content audit, availability, share of search, promotions, and ratings. DataWeave also provides brand protection services, helping consumer brands maintain their brand integrity by monitoring Minimum Advertised Price (MAP) pricing and identifying counterfeit products in e-commerce channels. The platform's AI-powered pricing intelligence solution equips retailers with valuable insights to optimize their pricing strategies, improving margins and revenues. In addition, DataWeave's assortment analytics solution enables retailers to curate winning assortments, fostering customer loyalty, driving higher retention and repeat purchases. 6. Dimensional Insight Dimensional Insight is a renowned business intelligence software company that excels in providing tailored business intelligence and analytics solutions across diverse industries. Diver Platform, the company's flagship product, empowers users to seamlessly integrate, model, analyze, and visualize data from multiple sources. With a keen focus on industry-specific needs, Dimensional Insight offers specialized applications for healthcare, wine and spirits, manufacturing, and distribution sectors. These tailored solutions enable organizations to gain valuable insights and make informed business decisions. The Diver Platform enables users to easily create stunning reports and dashboards, explore data with a simple click, and share insights with others. It also has unique features such as no database requirement, data compression and optimization, and data integration from multiple sources and formats. 7. InetSoft InetSoft is a leading software company specializing in business intelligence and analytics solutions. Its web-based platform, InetSoft Style Intelligence, empowers users to effortlessly connect, transform, analyze, and visualize data from any source, enabling them to share valuable insights with others. Style Intelligence offers a range of powerful features, including data mashups, visual analytic dashboards, document reporting, self-service analytics, embedded analytics, and seamless integration with machine learning. The platform offers intelligent and personalized insights and recommendations by leveraging AI and ML. Moreover, InetSoft Style Intelligence is designed to be embedded and OEM-friendly, offering multi-tenant hosting, white-labeling, and flexible licensing models. With its versatility, the platform caters to various industries and use cases, such as sales and marketing, finance, operations, healthcare, education, and more. 8. 1010data 1010data is a leading business intelligence company that empowers organizations with advanced data insights and capabilities. The platform offers a comprehensive suite of tools specifically designed to handle large and complex datasets, equipping users with the ability to analyze, visualize, and derive meaningful insights from their data. 1010data can efficiently manage massive volumes of data, enabling users to explore and analyze information swiftly and effectively. The platform also provides a powerful set of data querying and transformation capabilities, allowing users to manipulate and refine data to suit their specific analysis needs. Additionally, 1010data's platform supports advanced analytics techniques, such as predictive modeling and machine learning. Collaborative features are another key aspect of the platform, enabling users can easily collaborate on data analysis projects, share insights, and generate reports to facilitate effective decision-making processes. 9. Kyvos Insights Kyvos Insights is a business intelligence solutions provider specializing in scalable and high-performance analytics on big data platforms. Kyvos offers a unique approach to data analysis by leveraging Massively Parallel Processing (MPP) architecture and in-memory technology to deliver interactive and multidimensional analytics on large volumes of data. Users can explore data from various angles and dimensions without compromising performance, gaining valuable insights quickly. The platform seamlessly integrates with popular big data platforms like Hadoop and Snowflake, allowing organizations to leverage their existing data infrastructure. Kyvos Insights' advanced analytics features, such as Online Analytical Processing (OLAP), drill-downs, and data slicing, empower users to delve deep into their data and uncover valuable business trends. Moreover, Kyvos Insights offers a user-friendly interface with self-service analytics capabilities, empowering business users to explore and visualize data intuitively. 10. TARGIT TARGIT is a prominent software company specializing in accessible business intelligence and analytics solutions, recognized by its TARGIT Decision Suite. This suite facilitates simplified data utilization, catering to a diverse clientele. TARGIT empowers customers to enhance decision-making for improved profitability, productivity, and competitiveness by translating data into actionable insights. The company leverages its industry expertise and customer insights to solidify its foundation, thereby effectively translating intelligence into impactful decisions with a proven record of tangible business value. Its emphasis on cost-effectiveness ensures low Total Cost of Ownership (TCO), offering enduring value to customers and their organizations. Final Thoughts The landscape of business intelligence and analytics solutions is vast and constantly evolving as companies strive to harness the full potential of data for organizations. This article showcases the top business intelligence companies in the industry that offer tailored solutions to meet the unique needs of various sectors. These business intelligence companies deliver innovative and robust solutions that empower businesses to extract valuable insights from their data resources. With a strong commitment to user-friendly interfaces and powerful functionalities, they enable organizations to gain a competitive edge in the market. As businesses navigate the complexities of data analysis, the expertise and offerings of these top business intelligence companies become invaluable. Through their tools and technologies, organizations can unlock the true potential of their data, identify growth opportunities, and make informed decisions that drive success.Explore the top business intelligence and analytics solution providers and discover how these tailored and innovative BI solutions to meet the unique needs of organizations across various sectors.

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Business Intelligence, Big Data Management, Big Data

Leveraging Big Data for Competitive Advantage: Benefits

Article | July 10, 2023

Big Data has grown more valuable, helping businesses grow with features like real-time insights and enhanced decision-making; investing in a data strategy helps to stay ahead of the competition. Contents 1. Introduction 2. Leveraging Big Data for Competitive Edge and Sales Growth 3. Benefits of Big Data Analytics in Businesses 3.1 Improved Customer Insights 3.2 Enhanced Operational Efficiency 3.3 Better Decision-Making 3.4 New Product Development 3.5 Competitive Intelligence and Market Research 4. The Path Ahead 1. Introduction The benefits of big data for organizations have amplified with the advent of digital transformation and the prevalence of cloud technology, the Internet of Things (IoT), and ubiquitous internet access. A comprehensive data strategy has become a prerequisite for organizations to retain their competitive edge and leverage big data's advantages. Data analytics is widely employed across different industries and departments, including finance, human resources, and online retail, to glean insights into customer behavior and identify fraudulent activities. In addition, big data in business assumes a critical role in furthering social good by facilitating the monitoring of emissions and pollutants, aiding against climate change. 2. Leveraging Big Data for Competitive Edge and Sales Growth Big data is vital for companies seeking to gain a competitive edge and foster innovation in the current business landscape. By leveraging big data, companies can quickly extract valuable insights from vast amounts of data. This requires investments in tools & technologies, and skilled data analysts & scientists. With a robust big data strategy in place, companies optimize operations, identify new opportunities, and drive innovation. Furthermore, data analytics plays a crucial role in boosting sales by providing insights into customer behavior, preferences, and buying patterns. Companies can optimize their marketing, pricing, and product placement strategies through data analysis, thus leading to increased revenue. Real-time data enables businesses to adapt to market changes quickly, improving their agility and competitiveness. Therefore, developing data analytics capabilities is imperative for businesses to stay ahead and gain a competitive edge. 3. Benefits of Big Data Analytics in Businesses 3.1 Improved Customer Insights Big data has revolutionized how businesses gain a competitive edge through data analytics, offering improved customer insights by analyzing their behavior, preferences, and sentiment toward products. As a result, companies personalize experiences, segment audiences, map customer journeys, and enhance satisfaction. By analyzing data from multiple sources, companies create a 360-degree view of their customers and offer targeted marketing campaigns. 3.2 Enhanced Operational Efficiency Big data improves operational efficiency through predictive maintenance, supply chain optimization, and fraud detection. Predictive maintenance reduces downtime and increases productivity by identifying potential equipment failures. Supply chain optimization streamlines logistics processes, reducing shipping times and costs. Fraud detection identifies and prevents fraudulent activities, protecting businesses from financial losses. 3.3 Better Decision-Making Data-driven decision-making is one of the benefits of using big data, as it provides real-time insights into market trends, customer preferences, and key performance indicators. This helps companies make informed decisions to drive growth and success. Additionally, big data improves decision-making by providing real-time analytics for risk assessment and management, allowing businesses to identify and mitigate potential risks before they become major issues. 3.4 New Product Development Big data uses in businesses enable creation of innovative products and services by analyzing customer feedback and market trends. By gaining insights into customer needs and preferences, businesses identify new opportunities and optimize & innovate their products. 3.5 Competitive Intelligence and Market Research Big data is helpful in providing competitive intelligence and market research. Social listening is a way for businesses to use big data to gain insights into customer sentiment, preferences, and behavior. By analyzing conversations on social media, companies can identify areas for improvement and create effective marketing campaigns. Competitor analysis is another crucial use case for big data in business. By analyzing data on competitors' strategies, businesses can adjust their own strategies and gain a competitive edge. For example, companies can optimize their offerings by tracking competitors' pricing strategies, marketing tactics, and product offerings. 4. The Path Ahead With the continuous evolution of technology, the benefits of big data in business have become increasingly significant in day-to-day operations. The proliferation of digital transformation has provided companies with access to an overwhelming amount of data. In order to maintain a competitive edge, it is imperative for organizations to establish a comprehensive data strategy. However, merely collecting data is insufficient to leverage the potential of big data fully. Companies must possess the necessary tools and expertise to analyze and interpret it. This necessitates investment in advanced analytics tools, as well as the recruitment of data scientists and analysts who can extract valuable insights from the data.

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Business Intelligence, Big Data Management, Data Science

Mastering BI: Key Business Intelligence Events to Attend in 2023

Article | May 2, 2023

Explore top business intelligence events in 2023 to leverage unparalleled networking opportunities, engaging discussions, and cutting-edge technologies. Stay ahead and unlock the true potential of BI. The ability to harness data and make informed decisions has become paramount for success in the increasingly data-driven world. To stay ahead of the curve and leverage the power of data, professionals in this field must actively engage in continuous learning, networking, and exploring the latest trends and technologies. Fortunately, there are numerous business intelligence conferences and events that cater specifically to the needs of business intelligence professionals. These gatherings provide industry experts, thought leaders and practitioners a platform to share their knowledge, exchange ideas, and showcase cutting-edge solutions. This article will explore a curated list of top BI events to attend for business intelligence and analytics professionals. These events are designed to empower professionals in their journey toward data-driven excellence. Delve into the world of business intelligence and analytics and uncover the key features and benefits of each event. 1.2023 International Conference on Business Analytics for Operations Excellence & Resilience (BAOER 2023) July 15 - 17, 2023 | Singapore BAOER (Business Analytics for Operations Excellence & Resilience) is a highly anticipated annual meeting that serves as a premier platform for industry professionals, researchers, and practitioners to gather and explore the latest advancements in business analytics. The event encompasses various engaging activities, including keynote talks, invited talks, oral presentations, poster presentations, and online sessions. One of the distinguishing features of BAOER is its commitment to quality and academic rigor. The conference invites submissions of papers and abstracts on various topics related to business analytics for Operations Excellence & Resilience, which undergo a meticulous peer-review process by the esteemed Conference Technical Program Committee. Accepted papers are not only presented at the conference but also hold the opportunity to be published in the prestigious International Conference Proceedings. By bringing together a diverse group of authors and speakers from across nations and regions, BAOER fosters a vibrant exchange of ideas and fresh perspectives. Attendees can delve into both theoretical and practical aspects of Operations Excellence & Resilience, gaining valuable insights and building fruitful connections. 2.Melbourne Business Analytics Conference August 2, 2023 | Melbourne (Australia) In today's fast-paced world, where AI and automation play a pivotal role, businesses must adapt and embrace data and digital transformation to remain competitive. With this in mind, Melbourne Business Analytics Conference is, focused on the compelling theme of 'Leading the way: Navigating Data and Digital Transformation in the Age of AI & Automation.' This highly anticipated event will bring together esteemed analytics academics, executives, and practitioners from around the globe. The program will feature a lineup of distinguished speakers who will share their cutting-edge research, real-world experiences, and success stories. Over 600 board members, senior executives, and industry professionals will converge for a power-packed, one-day conference. It will serve as an exceptional platform for knowledge-sharing and networking opportunities. The conference aims to equip Australian businesses with the tools and insights needed to gain a distinctive advantage by harnessing the trilingual insights of business, technology, and mathematics. Participants can expect to immerse themselves in the latest advancements in Machine Learning, AI, and advanced Data Analytics business applications. These valuable insights will help organizations optimize their strategies, drive innovation, and make data-driven decisions. 3.OSU Business Analytics Conference 2023 October 4 - 5, 2023 | Portland (Oregon) Prepare to embark on a unique learning journey at the 4th annual Business Analytics Conference hosted by the Oregon State Center for Business Analytics. This in-person event offers an unparalleled experience, allowing participants to learn from esteemed analytics experts in a dynamic combination of hands-on activities and engaging lectures. This year's conference will strongly emphasize on AI trends, forthcoming technical breakthroughs, innovative applications of AI, and the implications and opportunities it presents for businesses. The panel sessions will feature industry experts alongside faculty members from the College of Business, Engineering, and Liberal Arts. This diverse range of perspectives ensures a comprehensive exploration of the subject matter. Gain invaluable insights into integrating AI programs into your daily operations & long-term planning, along with the growing impact of AI on business strategies, operations, and the workforce. The event will serve as a platform for stimulating discussions around the changes and opportunities that AI can bring and equip organizations with the knowledge and readiness required to navigate the AI landscape effectively. 4.Future Data Driven Summit 2023 September 27, 2023 | Online The Future Data Driven Summit is a prestigious online event that centers around the Microsoft Data Platform, offering attendees an unparalleled opportunity to stay updated on the latest developments in the field. This highly anticipated summit aims to provide valuable insights and knowledge pertaining to Data & AI, DevOps, PowerBI & Visualization, Integration & Automation, and cloud infrastructure. Catering to a diverse audience of IT professionals, data engineers & analysts, data scientists, AI & machine learning engineers, business analysts, and developers, the Future Data Driven Summit will ensure that each participant can derive immense value from the event. With its comprehensive range of topics and sessions, this summit will cater to the needs and interests of professionals across various domains within the data ecosystem. Attendees will be privileged to engage in informative sessions led by subject matter experts, witness hands-on demos of cutting-edge technologies, and gain profound insights from industry leaders' keynote speeches. By participating in these activities, attendees can expand their knowledge base, enhance their skill sets, and stay abreast of the latest trends and advancements in the Microsoft Data Platform. 5.TDWI Executive Summit for Analytics August 7 - 8, 2023 | San Diego (California) The TDWI Executive Summit for Analytics is an interactive and highly curated event specifically designed for business leaders, data science professionals, and IT executives who bear the responsibility of selecting, managing, and extracting value from analytics applications, AI/ML, business intelligence, and the underlying data that powers them. Organizations today constantly rely on analytics to drive innovation, attract and retain customers, improve operational efficiency, and effectively manage risk. However, TDWI has identified a common challenge many organizations face—struggling to progress in their analytics journey. These difficulties often result in user frustration, errors, and increased costs. By attending the TDWI Executive Summit for Analytics, participants can acquire invaluable knowledge on accelerating their analytics journey and achieving optimal business outcomes. The event places a specific focus on deriving the highest value from data assets through analytics and AI/ML into strategies for fostering stakeholder collaboration and effectively scaling analytics and AI/ML initiatives, including the implementation of MLOps—a methodology for managing the machine learning lifecycle. Additionally, the summit will explore emerging trends and technologies, such as generative AI, enabling attendees to stay ahead of the curve. 6.Business Intelligence & Analytics Conference Europe November 7 - 10, 2023 | London (UK) The Business Intelligence & Analytics Conference Europe presents a unique and immersive four-day experience focused on learning and networking. This exceptional business intelligence event offers attendees unparalleled opportunities to connect and collaborate with professionals from Europe and beyond. The conference will encompass five tracks and hosts over 45 sessions, ensuring a comprehensive and diverse range of topics to explore. Through a myriad of fascinating case studies, attendees can learn from various organizations' past successes and challenges. This firsthand knowledge-sharing provides invaluable practical insights that can be applied in real-world scenarios. Broadening knowledge and gaining insights from internationally renowned experts is a key highlight of the event. These experts bring their wealth of experience and expertise to the forefront, sharing innovative approaches and best practices that can drive success in business intelligence and analytics. A notable roster of esteemed organizations participated in the previous year's conference edition. Among notable names were Aizonic, Allianz, AstraZeneca, Bank of England, Dufrain, Volva Penta and many more. The presence of such esteemed organizations further reinforces the conference's credibility and significance within the industry. 7.Data & Analytics Live July 25, 2023 | Online Data & Analytics Live is a highly immersive event that brings a multitude of data and analytics professionals from across North America, offering a full day of learning, networking, and collaboration, catering to newcomers to the field and seasoned industry leaders. Attendees can expect to gain valuable insights and takeaways from renowned speakers sharing their insights into the solutions required to address the most pressing challenges faced by the data and analytics community. These thought leaders will provide invaluable perspectives and expertise, guiding participants toward effective strategies and innovative approaches. One of the key highlights of Data & Analytics Live is the opportunity to discover the latest trends and solutions provided by leading industry providers. Navigating uncharted territory in the data and analytics landscape can be complex, but this event will equip attendees with the knowledge and resources to navigate confidently. Data & Analytics Live will offer a glimpse into how data and analytics are revolutionizing businesses across industries and serves as a unique platform to interact with industry leaders, influential technologists, and pioneering data scientists shaping the future of data and analytics. 8.Customer Analytics Summit September 10 - 12, 2023 | Jersey City (New Jersey) The Customer Analytics Summit is an exciting event designed specifically for professionals in the data and customer insights community. Tailored to address the most pertinent issues in this field, the summit provides a unique opportunity to gain insights from highly successful leaders in data and customer insights. This event will offer an authentic peer-to-peer learning experience, fostering meaningful exchanges among professionals who understand the challenges and opportunities within the data and analytics space. The Customer Analytics Summit showcases renowned industry leaders who will share their expertise and experiences in maximizing the potential of data-driven insights. Attendees will discover how these leaders have harnessed data-driven, actionable insights to unlock exceptional customer value. In addition to insightful presentations, the summit will also provide focused individual discussion groups. These groups offer a platform for in-depth conversations on topics currently shaping the data and analytics landscape. Moreover, the summit will include interactive workshops that provide hands-on training on the latest tools, techniques, and strategies in data and analytics. The Customer Analytics Summit is a must-attend event for professionals seeking to stay at the forefront of the data and customer insights industry. 9.BI Innovation & Tech Fest September 18 - 19, 2023 | Sandton (South Africa) The business intelligence, analytics, and data environment is undergoing an extraordinary transition in today's rapidly evolving world. In this context, the annual BI Innovation & Tech Fest stands out as a premier event that celebrates and empowers individuals passionate about driving innovation in the business intelligence function from multiple perspectives - people, processes, and technology. This extraordinary BI event will provide attendees with a world-class experience, offering an unparalleled agenda that covers a wide range of topics critical to the industry. Whether exploring the latest advancements in AI and machine learning applied to business intelligence, mastering data reporting, visualization, and time analytics or delving into cloud-based BI and self-service BI, the event will present a comprehensive platform to stay ahead of the curve. One of the highlights of BI Innovation & Tech Fest is its emphasis on creating opportunities for networking and collaboration. Attendees will gain access to leading partners and vendors in the business intelligence space, providing valuable insights into cutting-edge technologies, tools, and solutions. The event will foster an environment where professionals can exchange ideas, forge new connections, and engage in meaningful conversations that drive innovation and excellence. 10.Big Data LDN (London) September 20-21, 2023 | Olympia London Big Data LDN (London) is the preeminent free-to-attend conference and exhibition in the UK, dedicated to data, analytics, and AI. With a host of renowned experts in these fields, the event equips attendees with the necessary tools to drive their most effective data-driven strategies. It will bring together over 180 leading technology vendors and consultants, providing a platform for in-depth discussions about business requirements and the latest advancements in the industry. One of the event's key highlights is the opportunity to hear from 300 expert speakers across 15 technical and business-led conference theatres. These speakers will present real-world use cases, share insights, and engage in panel debates, providing attendees with valuable knowledge and practical examples to apply in their organizations. In addition, the event offer exceptional networking opportunities, allowing attendees to connect with their peers, industry experts, and thought leaders. This networking aspect is invaluable for fostering collaborations, exchanging ideas, and building relationships to drive future field success. Big Data LDN goes well beyond the conference sessions and exhibitions by offering free on-site data consultancy services. Conclusion Business intelligence and analytics are evolving unprecedentedly, driven by technological advancements, data availability, and the growing need for data-driven decision-making. Attending industry conferences and events is crucial for professionals in this field to stay abreast of the latest trends, learn from experts, network with peers, and discover innovative solutions. Attending these top business intelligence events allows professionals to gain the knowledge, skills, and connections necessary to excel in their roles. These conferences provide a platform for sharing ideas, learning best practices, and exploring the latest advancements in the field. They serve as catalysts for growth, enabling individuals to unlock the full potential of data and analytics in their organizations. In this era of data-driven decision-making, seize the opportunities, and embark on a journey of continuous learning and professional development through these top business intelligence events in the BI and analytics domain.

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Business Intelligence, Big Data Management, Big Data

Implementing Data Analytics: Emerging Big Data Tools in 2023

Article | July 10, 2023

Discover the prominent big data analytics tools in 2023 and unlock the full potential of big data. Leverage data-driven decision-making to gain insights and implement strategies to accelerate growth. Adopting Big Data Analytics Tools In the current data-driven world, organizations increasingly recognize the value of data analytics in driving businesses’ success. As the volume and complexity of data continue to grow, staying at the forefront of data analytics tools and technologies becomes crucial for businesses to gain actionable insights and make informed decisions. As we delve into 2023, it becomes paramount for businesses to keep pace with emerging cutting-edge big data tools. These tools serve as catalysts for enterprises to harness the power of data analytics effectively. By adopting the right tools and technologies, organizations gain a competitive advantage, foster innovation, and make data-driven decisions that accelerate their growth in an ever-evolving digital landscape. This article delves into the realm of data analytics and explores the emerging big data analytics tools poised to have a significant impact in 2023. From sophisticated machine learning algorithms that push the boundaries of analysis to robust data visualization platforms that bring insights to life, these tools present captivating opportunities for organizations to unlock the full potential of their data and derive actionable intelligence. Exploring Key Trends and Emerging Tools One of the key trends in the data analytics landscape is the rise of cloud-based analytics platforms. These platforms provide scalability, flexibility, and accessibility, allowing businesses to leverage the power of distributed computing and storage for their data analysis needs. With cloud-based tools, organizations can easily process and analyze large volumes of data without significant infrastructure investments. Another emerging trend is integrating artificial intelligence and machine learning into data analytics workflows. AI-powered analytics tools enable businesses to automate data processing, uncover hidden patterns, and generate predictive insights. ML algorithms can learn from vast amounts of data, continuously improving accuracy and enabling organizations to make data-driven decisions with precision. Furthermore, big data visualization tools are becoming increasingly sophisticated, enabling users to transform intricate data into interactive visual representations. These tools facilitate enhanced comprehension and interpretation of data, allowing stakeholders to swiftly extract insights with efficacy. Moreover, the convergence of big data and internet of things (IoT) technologies is creating new opportunities. As IoT devices generate vast amounts of data, organizations can leverage tools for big data analytics to capture, store, and analyze this data, uncovering valuable insights and driving innovation in various industries. Top Big Data Tools to Lookout For: 1. Talend Data Fabric Cloud Integration Software by Talend Talend Data Fabric is an integrated data management and governance platform that enables organizations to access, transform, move and synchronize big data across the enterprise. It provides a comprehensive suite of tools and technologies to address data integration, quality, governance, and stewardship challenges. The platform allows users to access and work with data, regardless of location or format, whether in traditional databases, data lakes, cloud environments, or even in real-time streaming sources. This flexibility empowers organizations to leverage their data assets more effectively and make data-driven decisions. 2. Alteryx Platform Predictive Analytics Software by Alteryx Alteryx is a user-friendly data analytics platform that enables efficient processing and analysis of large datasets. It empowers users to quickly derive valuable insights from data without extensive coding skills. Alteryx facilitates the automation of analytics tasks at scale and enables intelligent decision-making across the organization. The platform provides a comprehensive set of tools, including automated data preparation, analytics, machine learning capabilities, and AI-generated insights. Its intuitive interface enables seamless data access from diverse sources like databases, cloud-based data warehouses, and spreadsheets. Alteryx simplifies data blending and preparation from multiple sources, ensuring high-quality and analysis-ready data for enhanced decision-making. 3. Adverity Data Integration Platform Adverity is a comprehensive data platform that automates data connectivity, transformation, governance, and utilization at scale. It simplifies the arduous task of cleansing and merging data from diverse sources, encompassing sales, finance, and marketing channels, to establish a reliable source of business performance information. The platform seamlessly integrates with multiple databases and cloud-based software, providing access to previously inaccessible data. Adverity empowers users to efficiently analyze incoming data from any source and format, facilitating the discovery of patterns, trends, and correlations. Its robust dashboard enables real-time interaction with data, empowering businesses to make faster, smarter decisions. 4. GoodData Cloud BI and Analytics Platform GoodData is an advanced cloud-based analytics platform that offer intuitive and user-friendly tools for data analysis, embeddable data visualizations, and seamless application integration solutions. Its API-first approach enables users to effortlessly aggregate, analyze, and visualize its data in real time, facilitating swift and effective decision-making. In addition, the platform's microservice-based architecture integrates seamlessly with existing ecosystems, providing a comprehensive end-to-end data analytics solution. With its scalable architecture and straightforward setup, GoodData is an excellent choice for businesses seeking powerful insights without expensive infrastructure investments. 5. Datameer Data Preparation Tool Datameer is an advanced analytics and data science platform designed to help businesses quickly discover insights in their enterprise data. It enables users to connect to multiple data sources effortlessly, employing a user-friendly drag-and-drop interface to transform data and create interactive visualizations and dashboards. The platform also offers access to various analytics tools, including predictive analytics and machine learning algorithms. By simplifying the data exploration process, Datameer provides an intuitive and robust environment for loading, storing, querying, and manipulating data from any source. This streamlined approach aids businesses in reducing time-to-insight by revealing previously concealed relationships and trends. Final Thoughts In the dynamic and data-intensive landscape of 2023, organizations must prioritize the integration of data analytics and adopting emerging big data tools. Adopting emerging tools for big data analytics empowers organizations to seamlessly collect, store, process, and analyze vast volumes of data in real time, providing valuable insights and enabling timely decision-making. However, to fully capitalize on the benefits of these tools, organizations must invest in skilled data professionals who can adeptly leverage these tools to extract meaningful insights. Data literacy and cultivating a data-driven culture within the organization are pivotal components for success in the data-driven landscape of 2023. Organizations can thrive in the ever-evolving realm of data analytics by fostering an environment where data is valued and utilized to drive business outcomes.

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Business Intelligence, Big Data Management, Big Data

Business Intelligence for Actionable Insights: Top BI books to Explore

Article | July 4, 2023

Explore the top business intelligence and analytics solution providers and discover how these tailored and innovative BI solutions meet the unique needs of organizations across various sectors. Organizations constantly seek innovative solutions to unlock the power of their data and extract valuable insights. In this data-driven space, business intelligence and analytics solutions have become indispensable tools for navigating the complexities of data analysis. These BI solutions empower businesses to explore, analyze, and visualize their data, providing actionable insights, trend identification, and driving overall business success. This article delves into the realm of business intelligence and analytics, highlighting the key players in the industry and showcasing their distinct offerings and capabilities. From scalable analytics on big data platforms to interactive visualizations and real-time insights, these BI solutions cater to the diverse needs of organizations across various industries. With a wide array of solution providers to choose from, organizations have the opportunity to select the solution that best aligns with their unique requirements, enabling them to master BI and fully unleash the potential of their data resources. 1. Yellowfin BI Yellowfin BI is a prominent business intelligence solutions provider known for its user-friendly analytics platform. It sets itself apart by emphasizing simplicity and intuitive design, making it easy for users to navigate and leverage the power of analytics. The platform offers interactive dashboards, real-time data updates, and advanced data visualization tools. It also supports collaborative analytics and data storytelling, empowering users to create compelling narratives that communicate insights collectively. Furthermore, the mobile access feature ensures that users can stay connected to their data even while on the move, enabling timely decision-making. Data security is a top priority for Yellowfin BI, offering robust features such as role-based access controls and encryption. These measures ensure that data remains secure and protected throughout the analytics process. 2. GoodData GoodData is a leading business intelligence company, renowned for its cloud-based analytics platform. The platform offers a comprehensive range of features designed to meet the diverse needs of businesses. It seamlessly combines data integration, visualization, and reporting capabilities, allowing organizations to make sense of their data and derive valuable insights. GoodData excels in connecting with various data sources, whether internal or external and consolidating them into a unified view for analysis. Additionally, the platform goes beyond traditional analytics by providing robust tools and APIs that allow businesses to embed analytics directly into their applications or customer-facing portals. This seamless integration empowers users to access data insights within their existing workflows. Moreover, GoodData prioritizes data security and compliance, offering features such as role-based access controls, data encryption, and audit logs to protect sensitive information. 3. Pyramid Analytics Pyramid is a trusted business intelligence solutions provider. Its Decision Intelligence Platform offers a seamless and efficient decision-making environment. The AI-driven platform integrates data preparation, business analytics, and data science into a unified environment, enabling businesses to fully leverage their data assets and address challenges posed by data silos and disparate self-service analytics tools. Pyramid simplifies complex data landscapes by harnessing artificial intelligence to streamline decision-making processes. In addition, the platform strongly emphasizes enterprise-level collaboration and governance, offering a centralized hub for teams to collaborate, share insights, and ensure data consistency throughout the organization. 4. AtScale AtScale is a business intelligence company specializing in data virtualization and analytics. The company enables organizations to leverage the power of big data by creating a unified and simplified view of their data infrastructure. AtScale's unique offering lies in its ability to provide a semantic layer that abstracts the complexities of underlying data sources, making it easier for users to access and analyze data without requiring extensive technical skills. By virtualizing data, AtScale eliminates the need for data replication, reducing storage costs and ensuring data consistency across the organization. The platform supports a wide range of data platforms and cloud providers, allowing businesses to seamlessly connect and analyze data from various sources. AtScale also offers advanced analytics capabilities, including OLAP (Online Analytical Processing) and multidimensional analysis, empowering users to derive valuable insights from their data. 5. DataWeave DataWeave is an advanced Software-as-a-Service (SaaS) solutions provider that offers a digital commerce analytics platform for consumer brands and retailers. Through the platform’s digital shelf analytics capabilities, brands can effectively measure and optimize key performance indicators (KPIs) such as content audit, availability, share of search, promotions, and ratings. DataWeave also provides brand protection services, helping consumer brands maintain their brand integrity by monitoring Minimum Advertised Price (MAP) pricing and identifying counterfeit products in e-commerce channels. The platform's AI-powered pricing intelligence solution equips retailers with valuable insights to optimize their pricing strategies, improving margins and revenues. In addition, DataWeave's assortment analytics solution enables retailers to curate winning assortments, fostering customer loyalty, driving higher retention and repeat purchases. 6. Dimensional Insight Dimensional Insight is a renowned business intelligence software company that excels in providing tailored business intelligence and analytics solutions across diverse industries. Diver Platform, the company's flagship product, empowers users to seamlessly integrate, model, analyze, and visualize data from multiple sources. With a keen focus on industry-specific needs, Dimensional Insight offers specialized applications for healthcare, wine and spirits, manufacturing, and distribution sectors. These tailored solutions enable organizations to gain valuable insights and make informed business decisions. The Diver Platform enables users to easily create stunning reports and dashboards, explore data with a simple click, and share insights with others. It also has unique features such as no database requirement, data compression and optimization, and data integration from multiple sources and formats. 7. InetSoft InetSoft is a leading software company specializing in business intelligence and analytics solutions. Its web-based platform, InetSoft Style Intelligence, empowers users to effortlessly connect, transform, analyze, and visualize data from any source, enabling them to share valuable insights with others. Style Intelligence offers a range of powerful features, including data mashups, visual analytic dashboards, document reporting, self-service analytics, embedded analytics, and seamless integration with machine learning. The platform offers intelligent and personalized insights and recommendations by leveraging AI and ML. Moreover, InetSoft Style Intelligence is designed to be embedded and OEM-friendly, offering multi-tenant hosting, white-labeling, and flexible licensing models. With its versatility, the platform caters to various industries and use cases, such as sales and marketing, finance, operations, healthcare, education, and more. 8. 1010data 1010data is a leading business intelligence company that empowers organizations with advanced data insights and capabilities. The platform offers a comprehensive suite of tools specifically designed to handle large and complex datasets, equipping users with the ability to analyze, visualize, and derive meaningful insights from their data. 1010data can efficiently manage massive volumes of data, enabling users to explore and analyze information swiftly and effectively. The platform also provides a powerful set of data querying and transformation capabilities, allowing users to manipulate and refine data to suit their specific analysis needs. Additionally, 1010data's platform supports advanced analytics techniques, such as predictive modeling and machine learning. Collaborative features are another key aspect of the platform, enabling users can easily collaborate on data analysis projects, share insights, and generate reports to facilitate effective decision-making processes. 9. Kyvos Insights Kyvos Insights is a business intelligence solutions provider specializing in scalable and high-performance analytics on big data platforms. Kyvos offers a unique approach to data analysis by leveraging Massively Parallel Processing (MPP) architecture and in-memory technology to deliver interactive and multidimensional analytics on large volumes of data. Users can explore data from various angles and dimensions without compromising performance, gaining valuable insights quickly. The platform seamlessly integrates with popular big data platforms like Hadoop and Snowflake, allowing organizations to leverage their existing data infrastructure. Kyvos Insights' advanced analytics features, such as Online Analytical Processing (OLAP), drill-downs, and data slicing, empower users to delve deep into their data and uncover valuable business trends. Moreover, Kyvos Insights offers a user-friendly interface with self-service analytics capabilities, empowering business users to explore and visualize data intuitively. 10. TARGIT TARGIT is a prominent software company specializing in accessible business intelligence and analytics solutions, recognized by its TARGIT Decision Suite. This suite facilitates simplified data utilization, catering to a diverse clientele. TARGIT empowers customers to enhance decision-making for improved profitability, productivity, and competitiveness by translating data into actionable insights. The company leverages its industry expertise and customer insights to solidify its foundation, thereby effectively translating intelligence into impactful decisions with a proven record of tangible business value. Its emphasis on cost-effectiveness ensures low Total Cost of Ownership (TCO), offering enduring value to customers and their organizations. Final Thoughts The landscape of business intelligence and analytics solutions is vast and constantly evolving as companies strive to harness the full potential of data for organizations. This article showcases the top business intelligence companies in the industry that offer tailored solutions to meet the unique needs of various sectors. These business intelligence companies deliver innovative and robust solutions that empower businesses to extract valuable insights from their data resources. With a strong commitment to user-friendly interfaces and powerful functionalities, they enable organizations to gain a competitive edge in the market. As businesses navigate the complexities of data analysis, the expertise and offerings of these top business intelligence companies become invaluable. Through their tools and technologies, organizations can unlock the true potential of their data, identify growth opportunities, and make informed decisions that drive success.Explore the top business intelligence and analytics solution providers and discover how these tailored and innovative BI solutions to meet the unique needs of organizations across various sectors.

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Business Intelligence, Big Data Management, Big Data

Implementing Data Analytics: Emerging Big Data Tools in 2023

Article | July 10, 2023

Big Data has grown more valuable, helping businesses grow with features like real-time insights and enhanced decision-making; investing in a data strategy helps to stay ahead of the competition. Contents 1. Introduction 2. Leveraging Big Data for Competitive Edge and Sales Growth 3. Benefits of Big Data Analytics in Businesses 3.1 Improved Customer Insights 3.2 Enhanced Operational Efficiency 3.3 Better Decision-Making 3.4 New Product Development 3.5 Competitive Intelligence and Market Research 4. The Path Ahead 1. Introduction The benefits of big data for organizations have amplified with the advent of digital transformation and the prevalence of cloud technology, the Internet of Things (IoT), and ubiquitous internet access. A comprehensive data strategy has become a prerequisite for organizations to retain their competitive edge and leverage big data's advantages. Data analytics is widely employed across different industries and departments, including finance, human resources, and online retail, to glean insights into customer behavior and identify fraudulent activities. In addition, big data in business assumes a critical role in furthering social good by facilitating the monitoring of emissions and pollutants, aiding against climate change. 2. Leveraging Big Data for Competitive Edge and Sales Growth Big data is vital for companies seeking to gain a competitive edge and foster innovation in the current business landscape. By leveraging big data, companies can quickly extract valuable insights from vast amounts of data. This requires investments in tools & technologies, and skilled data analysts & scientists. With a robust big data strategy in place, companies optimize operations, identify new opportunities, and drive innovation. Furthermore, data analytics plays a crucial role in boosting sales by providing insights into customer behavior, preferences, and buying patterns. Companies can optimize their marketing, pricing, and product placement strategies through data analysis, thus leading to increased revenue. Real-time data enables businesses to adapt to market changes quickly, improving their agility and competitiveness. Therefore, developing data analytics capabilities is imperative for businesses to stay ahead and gain a competitive edge. 3. Benefits of Big Data Analytics in Businesses 3.1 Improved Customer Insights Big data has revolutionized how businesses gain a competitive edge through data analytics, offering improved customer insights by analyzing their behavior, preferences, and sentiment toward products. As a result, companies personalize experiences, segment audiences, map customer journeys, and enhance satisfaction. By analyzing data from multiple sources, companies create a 360-degree view of their customers and offer targeted marketing campaigns. 3.2 Enhanced Operational Efficiency Big data improves operational efficiency through predictive maintenance, supply chain optimization, and fraud detection. Predictive maintenance reduces downtime and increases productivity by identifying potential equipment failures. Supply chain optimization streamlines logistics processes, reducing shipping times and costs. Fraud detection identifies and prevents fraudulent activities, protecting businesses from financial losses. 3.3 Better Decision-Making Data-driven decision-making is one of the benefits of using big data, as it provides real-time insights into market trends, customer preferences, and key performance indicators. This helps companies make informed decisions to drive growth and success. Additionally, big data improves decision-making by providing real-time analytics for risk assessment and management, allowing businesses to identify and mitigate potential risks before they become major issues. 3.4 New Product Development Big data uses in businesses enable creation of innovative products and services by analyzing customer feedback and market trends. By gaining insights into customer needs and preferences, businesses identify new opportunities and optimize & innovate their products. 3.5 Competitive Intelligence and Market Research Big data is helpful in providing competitive intelligence and market research. Social listening is a way for businesses to use big data to gain insights into customer sentiment, preferences, and behavior. By analyzing conversations on social media, companies can identify areas for improvement and create effective marketing campaigns. Competitor analysis is another crucial use case for big data in business. By analyzing data on competitors' strategies, businesses can adjust their own strategies and gain a competitive edge. For example, companies can optimize their offerings by tracking competitors' pricing strategies, marketing tactics, and product offerings. 4. The Path Ahead With the continuous evolution of technology, the benefits of big data in business have become increasingly significant in day-to-day operations. The proliferation of digital transformation has provided companies with access to an overwhelming amount of data. In order to maintain a competitive edge, it is imperative for organizations to establish a comprehensive data strategy. However, merely collecting data is insufficient to leverage the potential of big data fully. Companies must possess the necessary tools and expertise to analyze and interpret it. This necessitates investment in advanced analytics tools, as well as the recruitment of data scientists and analysts who can extract valuable insights from the data.

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Business Intelligence, Big Data Management, Data Science

Predictive Maintenance with Industrial Big Data: Reactive to Proactive Strategies

Article | May 2, 2023

Explore top business intelligence events in 2023 to leverage unparalleled networking opportunities, engaging discussions, and cutting-edge technologies. Stay ahead and unlock the true potential of BI. The ability to harness data and make informed decisions has become paramount for success in the increasingly data-driven world. To stay ahead of the curve and leverage the power of data, professionals in this field must actively engage in continuous learning, networking, and exploring the latest trends and technologies. Fortunately, there are numerous business intelligence conferences and events that cater specifically to the needs of business intelligence professionals. These gatherings provide industry experts, thought leaders and practitioners a platform to share their knowledge, exchange ideas, and showcase cutting-edge solutions. This article will explore a curated list of top BI events to attend for business intelligence and analytics professionals. These events are designed to empower professionals in their journey toward data-driven excellence. Delve into the world of business intelligence and analytics and uncover the key features and benefits of each event. 1.2023 International Conference on Business Analytics for Operations Excellence & Resilience (BAOER 2023) July 15 - 17, 2023 | Singapore BAOER (Business Analytics for Operations Excellence & Resilience) is a highly anticipated annual meeting that serves as a premier platform for industry professionals, researchers, and practitioners to gather and explore the latest advancements in business analytics. The event encompasses various engaging activities, including keynote talks, invited talks, oral presentations, poster presentations, and online sessions. One of the distinguishing features of BAOER is its commitment to quality and academic rigor. The conference invites submissions of papers and abstracts on various topics related to business analytics for Operations Excellence & Resilience, which undergo a meticulous peer-review process by the esteemed Conference Technical Program Committee. Accepted papers are not only presented at the conference but also hold the opportunity to be published in the prestigious International Conference Proceedings. By bringing together a diverse group of authors and speakers from across nations and regions, BAOER fosters a vibrant exchange of ideas and fresh perspectives. Attendees can delve into both theoretical and practical aspects of Operations Excellence & Resilience, gaining valuable insights and building fruitful connections. 2.Melbourne Business Analytics Conference August 2, 2023 | Melbourne (Australia) In today's fast-paced world, where AI and automation play a pivotal role, businesses must adapt and embrace data and digital transformation to remain competitive. With this in mind, Melbourne Business Analytics Conference is, focused on the compelling theme of 'Leading the way: Navigating Data and Digital Transformation in the Age of AI & Automation.' This highly anticipated event will bring together esteemed analytics academics, executives, and practitioners from around the globe. The program will feature a lineup of distinguished speakers who will share their cutting-edge research, real-world experiences, and success stories. Over 600 board members, senior executives, and industry professionals will converge for a power-packed, one-day conference. It will serve as an exceptional platform for knowledge-sharing and networking opportunities. The conference aims to equip Australian businesses with the tools and insights needed to gain a distinctive advantage by harnessing the trilingual insights of business, technology, and mathematics. Participants can expect to immerse themselves in the latest advancements in Machine Learning, AI, and advanced Data Analytics business applications. These valuable insights will help organizations optimize their strategies, drive innovation, and make data-driven decisions. 3.OSU Business Analytics Conference 2023 October 4 - 5, 2023 | Portland (Oregon) Prepare to embark on a unique learning journey at the 4th annual Business Analytics Conference hosted by the Oregon State Center for Business Analytics. This in-person event offers an unparalleled experience, allowing participants to learn from esteemed analytics experts in a dynamic combination of hands-on activities and engaging lectures. This year's conference will strongly emphasize on AI trends, forthcoming technical breakthroughs, innovative applications of AI, and the implications and opportunities it presents for businesses. The panel sessions will feature industry experts alongside faculty members from the College of Business, Engineering, and Liberal Arts. This diverse range of perspectives ensures a comprehensive exploration of the subject matter. Gain invaluable insights into integrating AI programs into your daily operations & long-term planning, along with the growing impact of AI on business strategies, operations, and the workforce. The event will serve as a platform for stimulating discussions around the changes and opportunities that AI can bring and equip organizations with the knowledge and readiness required to navigate the AI landscape effectively. 4.Future Data Driven Summit 2023 September 27, 2023 | Online The Future Data Driven Summit is a prestigious online event that centers around the Microsoft Data Platform, offering attendees an unparalleled opportunity to stay updated on the latest developments in the field. This highly anticipated summit aims to provide valuable insights and knowledge pertaining to Data & AI, DevOps, PowerBI & Visualization, Integration & Automation, and cloud infrastructure. Catering to a diverse audience of IT professionals, data engineers & analysts, data scientists, AI & machine learning engineers, business analysts, and developers, the Future Data Driven Summit will ensure that each participant can derive immense value from the event. With its comprehensive range of topics and sessions, this summit will cater to the needs and interests of professionals across various domains within the data ecosystem. Attendees will be privileged to engage in informative sessions led by subject matter experts, witness hands-on demos of cutting-edge technologies, and gain profound insights from industry leaders' keynote speeches. By participating in these activities, attendees can expand their knowledge base, enhance their skill sets, and stay abreast of the latest trends and advancements in the Microsoft Data Platform. 5.TDWI Executive Summit for Analytics August 7 - 8, 2023 | San Diego (California) The TDWI Executive Summit for Analytics is an interactive and highly curated event specifically designed for business leaders, data science professionals, and IT executives who bear the responsibility of selecting, managing, and extracting value from analytics applications, AI/ML, business intelligence, and the underlying data that powers them. Organizations today constantly rely on analytics to drive innovation, attract and retain customers, improve operational efficiency, and effectively manage risk. However, TDWI has identified a common challenge many organizations face—struggling to progress in their analytics journey. These difficulties often result in user frustration, errors, and increased costs. By attending the TDWI Executive Summit for Analytics, participants can acquire invaluable knowledge on accelerating their analytics journey and achieving optimal business outcomes. The event places a specific focus on deriving the highest value from data assets through analytics and AI/ML into strategies for fostering stakeholder collaboration and effectively scaling analytics and AI/ML initiatives, including the implementation of MLOps—a methodology for managing the machine learning lifecycle. Additionally, the summit will explore emerging trends and technologies, such as generative AI, enabling attendees to stay ahead of the curve. 6.Business Intelligence & Analytics Conference Europe November 7 - 10, 2023 | London (UK) The Business Intelligence & Analytics Conference Europe presents a unique and immersive four-day experience focused on learning and networking. This exceptional business intelligence event offers attendees unparalleled opportunities to connect and collaborate with professionals from Europe and beyond. The conference will encompass five tracks and hosts over 45 sessions, ensuring a comprehensive and diverse range of topics to explore. Through a myriad of fascinating case studies, attendees can learn from various organizations' past successes and challenges. This firsthand knowledge-sharing provides invaluable practical insights that can be applied in real-world scenarios. Broadening knowledge and gaining insights from internationally renowned experts is a key highlight of the event. These experts bring their wealth of experience and expertise to the forefront, sharing innovative approaches and best practices that can drive success in business intelligence and analytics. A notable roster of esteemed organizations participated in the previous year's conference edition. Among notable names were Aizonic, Allianz, AstraZeneca, Bank of England, Dufrain, Volva Penta and many more. The presence of such esteemed organizations further reinforces the conference's credibility and significance within the industry. 7.Data & Analytics Live July 25, 2023 | Online Data & Analytics Live is a highly immersive event that brings a multitude of data and analytics professionals from across North America, offering a full day of learning, networking, and collaboration, catering to newcomers to the field and seasoned industry leaders. Attendees can expect to gain valuable insights and takeaways from renowned speakers sharing their insights into the solutions required to address the most pressing challenges faced by the data and analytics community. These thought leaders will provide invaluable perspectives and expertise, guiding participants toward effective strategies and innovative approaches. One of the key highlights of Data & Analytics Live is the opportunity to discover the latest trends and solutions provided by leading industry providers. Navigating uncharted territory in the data and analytics landscape can be complex, but this event will equip attendees with the knowledge and resources to navigate confidently. Data & Analytics Live will offer a glimpse into how data and analytics are revolutionizing businesses across industries and serves as a unique platform to interact with industry leaders, influential technologists, and pioneering data scientists shaping the future of data and analytics. 8.Customer Analytics Summit September 10 - 12, 2023 | Jersey City (New Jersey) The Customer Analytics Summit is an exciting event designed specifically for professionals in the data and customer insights community. Tailored to address the most pertinent issues in this field, the summit provides a unique opportunity to gain insights from highly successful leaders in data and customer insights. This event will offer an authentic peer-to-peer learning experience, fostering meaningful exchanges among professionals who understand the challenges and opportunities within the data and analytics space. The Customer Analytics Summit showcases renowned industry leaders who will share their expertise and experiences in maximizing the potential of data-driven insights. Attendees will discover how these leaders have harnessed data-driven, actionable insights to unlock exceptional customer value. In addition to insightful presentations, the summit will also provide focused individual discussion groups. These groups offer a platform for in-depth conversations on topics currently shaping the data and analytics landscape. Moreover, the summit will include interactive workshops that provide hands-on training on the latest tools, techniques, and strategies in data and analytics. The Customer Analytics Summit is a must-attend event for professionals seeking to stay at the forefront of the data and customer insights industry. 9.BI Innovation & Tech Fest September 18 - 19, 2023 | Sandton (South Africa) The business intelligence, analytics, and data environment is undergoing an extraordinary transition in today's rapidly evolving world. In this context, the annual BI Innovation & Tech Fest stands out as a premier event that celebrates and empowers individuals passionate about driving innovation in the business intelligence function from multiple perspectives - people, processes, and technology. This extraordinary BI event will provide attendees with a world-class experience, offering an unparalleled agenda that covers a wide range of topics critical to the industry. Whether exploring the latest advancements in AI and machine learning applied to business intelligence, mastering data reporting, visualization, and time analytics or delving into cloud-based BI and self-service BI, the event will present a comprehensive platform to stay ahead of the curve. One of the highlights of BI Innovation & Tech Fest is its emphasis on creating opportunities for networking and collaboration. Attendees will gain access to leading partners and vendors in the business intelligence space, providing valuable insights into cutting-edge technologies, tools, and solutions. The event will foster an environment where professionals can exchange ideas, forge new connections, and engage in meaningful conversations that drive innovation and excellence. 10.Big Data LDN (London) September 20-21, 2023 | Olympia London Big Data LDN (London) is the preeminent free-to-attend conference and exhibition in the UK, dedicated to data, analytics, and AI. With a host of renowned experts in these fields, the event equips attendees with the necessary tools to drive their most effective data-driven strategies. It will bring together over 180 leading technology vendors and consultants, providing a platform for in-depth discussions about business requirements and the latest advancements in the industry. One of the event's key highlights is the opportunity to hear from 300 expert speakers across 15 technical and business-led conference theatres. These speakers will present real-world use cases, share insights, and engage in panel debates, providing attendees with valuable knowledge and practical examples to apply in their organizations. In addition, the event offer exceptional networking opportunities, allowing attendees to connect with their peers, industry experts, and thought leaders. This networking aspect is invaluable for fostering collaborations, exchanging ideas, and building relationships to drive future field success. Big Data LDN goes well beyond the conference sessions and exhibitions by offering free on-site data consultancy services. Conclusion Business intelligence and analytics are evolving unprecedentedly, driven by technological advancements, data availability, and the growing need for data-driven decision-making. Attending industry conferences and events is crucial for professionals in this field to stay abreast of the latest trends, learn from experts, network with peers, and discover innovative solutions. Attending these top business intelligence events allows professionals to gain the knowledge, skills, and connections necessary to excel in their roles. These conferences provide a platform for sharing ideas, learning best practices, and exploring the latest advancements in the field. They serve as catalysts for growth, enabling individuals to unlock the full potential of data and analytics in their organizations. In this era of data-driven decision-making, seize the opportunities, and embark on a journey of continuous learning and professional development through these top business intelligence events in the BI and analytics domain.

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Business Intelligence, Big Data Management, Big Data

Implementing Data Analytics: Emerging Big Data Tools in 2023

Article | July 10, 2023

Discover the prominent big data analytics tools in 2023 and unlock the full potential of big data. Leverage data-driven decision-making to gain insights and implement strategies to accelerate growth. Adopting Big Data Analytics Tools In the current data-driven world, organizations increasingly recognize the value of data analytics in driving businesses’ success. As the volume and complexity of data continue to grow, staying at the forefront of data analytics tools and technologies becomes crucial for businesses to gain actionable insights and make informed decisions. As we delve into 2023, it becomes paramount for businesses to keep pace with emerging cutting-edge big data tools. These tools serve as catalysts for enterprises to harness the power of data analytics effectively. By adopting the right tools and technologies, organizations gain a competitive advantage, foster innovation, and make data-driven decisions that accelerate their growth in an ever-evolving digital landscape. This article delves into the realm of data analytics and explores the emerging big data analytics tools poised to have a significant impact in 2023. From sophisticated machine learning algorithms that push the boundaries of analysis to robust data visualization platforms that bring insights to life, these tools present captivating opportunities for organizations to unlock the full potential of their data and derive actionable intelligence. Exploring Key Trends and Emerging Tools One of the key trends in the data analytics landscape is the rise of cloud-based analytics platforms. These platforms provide scalability, flexibility, and accessibility, allowing businesses to leverage the power of distributed computing and storage for their data analysis needs. With cloud-based tools, organizations can easily process and analyze large volumes of data without significant infrastructure investments. Another emerging trend is integrating artificial intelligence and machine learning into data analytics workflows. AI-powered analytics tools enable businesses to automate data processing, uncover hidden patterns, and generate predictive insights. ML algorithms can learn from vast amounts of data, continuously improving accuracy and enabling organizations to make data-driven decisions with precision. Furthermore, big data visualization tools are becoming increasingly sophisticated, enabling users to transform intricate data into interactive visual representations. These tools facilitate enhanced comprehension and interpretation of data, allowing stakeholders to swiftly extract insights with efficacy. Moreover, the convergence of big data and internet of things (IoT) technologies is creating new opportunities. As IoT devices generate vast amounts of data, organizations can leverage tools for big data analytics to capture, store, and analyze this data, uncovering valuable insights and driving innovation in various industries. Top Big Data Tools to Lookout For: 1. Talend Data Fabric Cloud Integration Software by Talend Talend Data Fabric is an integrated data management and governance platform that enables organizations to access, transform, move and synchronize big data across the enterprise. It provides a comprehensive suite of tools and technologies to address data integration, quality, governance, and stewardship challenges. The platform allows users to access and work with data, regardless of location or format, whether in traditional databases, data lakes, cloud environments, or even in real-time streaming sources. This flexibility empowers organizations to leverage their data assets more effectively and make data-driven decisions. 2. Alteryx Platform Predictive Analytics Software by Alteryx Alteryx is a user-friendly data analytics platform that enables efficient processing and analysis of large datasets. It empowers users to quickly derive valuable insights from data without extensive coding skills. Alteryx facilitates the automation of analytics tasks at scale and enables intelligent decision-making across the organization. The platform provides a comprehensive set of tools, including automated data preparation, analytics, machine learning capabilities, and AI-generated insights. Its intuitive interface enables seamless data access from diverse sources like databases, cloud-based data warehouses, and spreadsheets. Alteryx simplifies data blending and preparation from multiple sources, ensuring high-quality and analysis-ready data for enhanced decision-making. 3. Adverity Data Integration Platform Adverity is a comprehensive data platform that automates data connectivity, transformation, governance, and utilization at scale. It simplifies the arduous task of cleansing and merging data from diverse sources, encompassing sales, finance, and marketing channels, to establish a reliable source of business performance information. The platform seamlessly integrates with multiple databases and cloud-based software, providing access to previously inaccessible data. Adverity empowers users to efficiently analyze incoming data from any source and format, facilitating the discovery of patterns, trends, and correlations. Its robust dashboard enables real-time interaction with data, empowering businesses to make faster, smarter decisions. 4. GoodData Cloud BI and Analytics Platform GoodData is an advanced cloud-based analytics platform that offer intuitive and user-friendly tools for data analysis, embeddable data visualizations, and seamless application integration solutions. Its API-first approach enables users to effortlessly aggregate, analyze, and visualize its data in real time, facilitating swift and effective decision-making. In addition, the platform's microservice-based architecture integrates seamlessly with existing ecosystems, providing a comprehensive end-to-end data analytics solution. With its scalable architecture and straightforward setup, GoodData is an excellent choice for businesses seeking powerful insights without expensive infrastructure investments. 5. Datameer Data Preparation Tool Datameer is an advanced analytics and data science platform designed to help businesses quickly discover insights in their enterprise data. It enables users to connect to multiple data sources effortlessly, employing a user-friendly drag-and-drop interface to transform data and create interactive visualizations and dashboards. The platform also offers access to various analytics tools, including predictive analytics and machine learning algorithms. By simplifying the data exploration process, Datameer provides an intuitive and robust environment for loading, storing, querying, and manipulating data from any source. This streamlined approach aids businesses in reducing time-to-insight by revealing previously concealed relationships and trends. Final Thoughts In the dynamic and data-intensive landscape of 2023, organizations must prioritize the integration of data analytics and adopting emerging big data tools. Adopting emerging tools for big data analytics empowers organizations to seamlessly collect, store, process, and analyze vast volumes of data in real time, providing valuable insights and enabling timely decision-making. However, to fully capitalize on the benefits of these tools, organizations must invest in skilled data professionals who can adeptly leverage these tools to extract meaningful insights. Data literacy and cultivating a data-driven culture within the organization are pivotal components for success in the data-driven landscape of 2023. Organizations can thrive in the ever-evolving realm of data analytics by fostering an environment where data is valued and utilized to drive business outcomes.

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Teradata helps customers accelerate AI-led initiatives with new ModelOps capabilities in ClearScape analytics

iTWire | September 27, 2023

Teradata today announced new enhancements to its leading AI/ML (artificial intelligence/machine learning) model management software in ClearScape Analytics (e.g., ModelOps) to meet the growing demand from organisations across the globe for advanced analytics and AI. These new features – including “no code” capabilities, as well as robust new governance and AI “explainability” controls – enable businesses to accelerate, scale, and optimise AI/ML deployments to quickly generate business value from their AI investments. Deploying AI models into production is notoriously challenging. A recent O'Reilly's survey on AI adoption in the enterprise found that only 26% of respondents currently have models deployed in production, with many companies stating they have yet to see a return on their AI investments. This is compounded by the recent excitement around generative AI and the pressure many executives are under to implement it within their organisation, according to a recent survey by IDC, sponsored by Teradata. ModelOps in ClearScape Analytics makes it easier than ever to operationalise AI investments by addressing many of the key challenges that arise when moving from model development to deployment in production: end-to-end model lifecycle management, automated deployment, governance for trusted AI, and model monitoring. The governed ModelOps capability is designed to supply the framework to manage, deploy, monitor, and maintain analytic outcomes. It includes capabilities like auditing datasets, code tracking, model approval workflows, monitoring model performance, and alerting when models are not performing well. We stand on the precipice of a new AI-driven era, which promises to usher in frontiers of creativity, productivity, and innovation. Teradata is uniquely positioned to help businesses take advantage of advanced analytics, AI, and especially generative AI, to solve the most complex challenges and create massive enterprise business value. Teradata chief product officer Hillary Ashton “We offer the most complete cloud analytics and data platform for AI. And with our enhanced ModelOps capabilities, we are enabling organisations to cost effectively operationalise and scale trusted AI through robust governance and automated lifecycle management, while encouraging rapid AI innovation via our open and connected ecosystem. Teradata is also the most cost-effective, with proven performance and flexibility to innovate faster, enrich customer experiences, and deliver value.” New capabilities and enhancements to ModelOps include: - Bring Your Own Model (BYOM), now with no code capabilities, allows users to deploy their own machine learning models without writing any code, simplifying the deployment journey with automated validation, deployment and monitoring - Mitigation of regulatory risks with advanced model governance capabilities and robust explainability controls to ensure trusted AI - Automatic monitoring of model performance and data drift with zero configuration alerts Teradata customers are already using ModelOps to accelerate time-to-value for their AI investments A major US healthcare institution uses ModelOps to speed up the deployment process and scale its AI/ML personalisation journey. The institution accelerated its deployment with a 3x increase in productivity to successfully deploy thirty AI/ML models that predict which of its patients are most likely to need an office visit to implement “Personalisation at Scale.” A major European financial institution leveraged ModelOps to reduce AI model deployment time from five months to one week. The models are deployed at scale and integrated with operational data to deliver business value.

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Big Data Management

Congruity360 Delivers Intelligent Data Migrations and Storage Tiering

PR Newswire | September 27, 2023

Congruity360, a leading unstructured data management and risk mitigation provider, announces the addition of data mobility in Enterprise Insights. As unstructured data grows at the annual rate of 55% to 65% and accounts for more than 80% of all enterprise data, businesses must find a way to identify, classify and move data intelligently and automatically during its lifecycle. As enterprises grow, their valuable data must mature with their business. This may require a journey to the cloud, SLA changes which optimize storage costs, classification to mitigate risk, and moving the right data to additional key AI platform initiatives. A simple, scalable, high-performance data classification engine, Enterprise Insights delivers next-generation data lifecycle management for storage optimization, security and risk optimization, and IT business optimization. Enterprise Insights Approach to Successful Data Optimization: Identify – Securely analyze PBs of unstructured data across on premises (NAS & object) and cloud (files/objects & SaaS) sources by harnessing the power of the platform's rapid insights and auto-discover technologies, which can reduce data identification times by 1,000%. Classify – Quickly identify key client data attributes for cost savings, risk mitigation, and business impact with simple to consume dashboards and drill down capabilities. Review – Confidently create and take actions by leveraging the comprehensive search engine to quickly find and preview data for movement without ever leaving the platform. Remediate – Seamlessly take action (migrate and tier) on classified data to ensure it's properly protected, optimally stored, and most effectively serving the business. Enterprise Insights offers three use case-driven insight analysis modules: Storage and Migration Optimization – Insights into over 35 file data attributes including systems' aged, stale, obsolete, redundant, trivial, and types of systems files. Business Optimization – Insight into and classification by business units' or cost centers' aged, stale, obsolete, redundant, trivial, and types of files. Data Security and Risk Optimization – Insights into files containing PII and SPII, financial, legal, security, and risk data, as well as open shares and other network & storage security vulnerabilities. By leveraging Enterprise Insights, clients can classify data for simple and secure migration both on premise and in the cloud. Equally important is Insights data tiering capabilities, enabling users to match data storage costs to data usage. Powered by the Classify360 Platform, Enterprise Insights' secure hybrid approach to data analysis scales capabilities to exabyte levels at unmatched speed. Enterprise Insights is the industry's most powerful weapon to tackle the costs, time, and complexity of cloud migration projects, backup modernization, storage tiering, hardware refresh, and security posture management. By providing users with dashboards highlighting their existing storage costs and risks, Enterprise Insights frees clients from hidden, legacy, CapEx and OpEx expenditures, performance, and scalability bottlenecks while discovering and acting on sensitive and risk data. Unstructured data insanity is treating all data equally with zero insights into its business impact, said Brian Davidson, Chief Executive Officer and Managing Partner of Congruity360. Enterprise Insights is the first step in implementing optimized data lifecycle management. With historically high data growth and new business uses for unstructured data, it is essential to attack the costs and risks inherent in unmanaged data. Our customers have realized 7-10x returns on their data lifecycle management implementations while reducing risk in an auditable compliance framework. As AI continues to gain steam, don't overpay by moving useless data to your expensive AI platforms. The Classify360 Platform is comprehensive, simple to implement, scale, and operate. Businesses leverage the Classify360 Platform for unstructured data discovery, classification, business workflows, remediation actions, and insightful reporting. Congruity360 continues to tackle additional data governance challenges through innovations to the Classify360 Platform to continue delivering revolutionary data governance and classification, at scale, to the enterprise world. ABOUT CONGRUITY360 Congruity360 delivers the only data life cycle management solution built on a foundation of classification, by expert data storage engineers alongside expert data privacy consultants. The Classify360 Platform is easy to implement, requires no outside consultants, and quickly analyzes your data at the petabyte scale in days, not weeks or months.

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Big Data Management

Microsoft's AI Data Exposure Highlights Challenges in AI Integration

Microsoft | September 22, 2023

AI models rely heavily on vast data volumes for their functionality, thus increasing risks associated with mishandling data in AI projects. Microsoft's AI research team accidentally exposed 38 terabytes of private data on GitHub. Many companies feel compelled to adopt generative AI but lack the expertise to do so effectively. Artificial intelligence (AI) models are renowned for their enormous appetite for data, making them among the most data-intensive computing platforms in existence. While AI holds the potential to revolutionize the world, it is utterly dependent on the availability and ingestion of vast volumes of data. An alarming incident involving Microsoft's AI research team recently highlighted the immense data exposure risks inherent in this technology. The team inadvertently exposed a staggering 38 terabytes of private data when publishing open-source AI training data on the cloud-based code hosting platform GitHub. This exposed data included a complete backup of two Microsoft employees' workstations, containing highly sensitive personal information such as private keys, passwords to internal Microsoft services, and over 30,000 messages from 359 Microsoft employees. The exposure was a result of an accidental configuration, which granted "full control" access instead of "read-only" permissions. This oversight meant that potential attackers could not only view the exposed files but also manipulate, overwrite, or delete them. Although a crisis was narrowly averted in this instance, it serves as a glaring example of the new risks organizations face as they integrate AI more extensively into their operations. With staff engineers increasingly handling vast amounts of specialized and sensitive data to train AI models, it is imperative for companies to establish robust governance policies and educational safeguards to mitigate security risks. Training specialized AI models necessitates specialized data. As organizations of all sizes embrace the advantages AI offers in their day-to-day workflows, IT, data, and security teams must grasp the inherent exposure risks associated with each stage of the AI development process. Open data sharing plays a critical role in AI training, with researchers gathering and disseminating extensive amounts of both external and internal data to build the necessary training datasets for their AI models. However, the more data that is shared, the greater the risk if it is not handled correctly, as evidenced by the Microsoft incident. AI, in many ways, challenges an organization's internal corporate policies like no other technology has done before. To harness AI tools effectively and securely, businesses must first establish a robust data infrastructure to avoid the fundamental pitfalls of AI. Securing the future of AI requires a nuanced approach. Despite concerns about AI's potential risks, organizations should be more concerned about the quality of AI software than the technology turning rogue. PYMNTS Intelligence's research indicates that many companies are uncertain about their readiness for generative AI but still feel compelled to adopt it. A substantial 62% of surveyed executives believe their companies lack the expertise to harness the technology effectively, according to 'Understanding the Future of Generative AI,' a collaboration between PYMNTS and AI-ID. The rapid advancement of computing power and cloud storage infrastructure has reshaped the business landscape, setting the stage for data-driven innovations like AI to revolutionize business processes. While tech giants or well-funded startups primarily produce today's AI models, computing power costs are continually decreasing. In a few years, AI models may become so advanced that everyday consumers can run them on personal devices at home, akin to today's cutting-edge platforms. This juncture signifies a tipping point, where the ever-increasing zettabytes of proprietary data produced each year must be addressed promptly. If not, the risks associated with future innovations will scale up in sync with their capabilities.

Read More

Big Data

Teradata helps customers accelerate AI-led initiatives with new ModelOps capabilities in ClearScape analytics

iTWire | September 27, 2023

Teradata today announced new enhancements to its leading AI/ML (artificial intelligence/machine learning) model management software in ClearScape Analytics (e.g., ModelOps) to meet the growing demand from organisations across the globe for advanced analytics and AI. These new features – including “no code” capabilities, as well as robust new governance and AI “explainability” controls – enable businesses to accelerate, scale, and optimise AI/ML deployments to quickly generate business value from their AI investments. Deploying AI models into production is notoriously challenging. A recent O'Reilly's survey on AI adoption in the enterprise found that only 26% of respondents currently have models deployed in production, with many companies stating they have yet to see a return on their AI investments. This is compounded by the recent excitement around generative AI and the pressure many executives are under to implement it within their organisation, according to a recent survey by IDC, sponsored by Teradata. ModelOps in ClearScape Analytics makes it easier than ever to operationalise AI investments by addressing many of the key challenges that arise when moving from model development to deployment in production: end-to-end model lifecycle management, automated deployment, governance for trusted AI, and model monitoring. The governed ModelOps capability is designed to supply the framework to manage, deploy, monitor, and maintain analytic outcomes. It includes capabilities like auditing datasets, code tracking, model approval workflows, monitoring model performance, and alerting when models are not performing well. We stand on the precipice of a new AI-driven era, which promises to usher in frontiers of creativity, productivity, and innovation. Teradata is uniquely positioned to help businesses take advantage of advanced analytics, AI, and especially generative AI, to solve the most complex challenges and create massive enterprise business value. Teradata chief product officer Hillary Ashton “We offer the most complete cloud analytics and data platform for AI. And with our enhanced ModelOps capabilities, we are enabling organisations to cost effectively operationalise and scale trusted AI through robust governance and automated lifecycle management, while encouraging rapid AI innovation via our open and connected ecosystem. Teradata is also the most cost-effective, with proven performance and flexibility to innovate faster, enrich customer experiences, and deliver value.” New capabilities and enhancements to ModelOps include: - Bring Your Own Model (BYOM), now with no code capabilities, allows users to deploy their own machine learning models without writing any code, simplifying the deployment journey with automated validation, deployment and monitoring - Mitigation of regulatory risks with advanced model governance capabilities and robust explainability controls to ensure trusted AI - Automatic monitoring of model performance and data drift with zero configuration alerts Teradata customers are already using ModelOps to accelerate time-to-value for their AI investments A major US healthcare institution uses ModelOps to speed up the deployment process and scale its AI/ML personalisation journey. The institution accelerated its deployment with a 3x increase in productivity to successfully deploy thirty AI/ML models that predict which of its patients are most likely to need an office visit to implement “Personalisation at Scale.” A major European financial institution leveraged ModelOps to reduce AI model deployment time from five months to one week. The models are deployed at scale and integrated with operational data to deliver business value.

Read More

Big Data Management

Congruity360 Delivers Intelligent Data Migrations and Storage Tiering

PR Newswire | September 27, 2023

Congruity360, a leading unstructured data management and risk mitigation provider, announces the addition of data mobility in Enterprise Insights. As unstructured data grows at the annual rate of 55% to 65% and accounts for more than 80% of all enterprise data, businesses must find a way to identify, classify and move data intelligently and automatically during its lifecycle. As enterprises grow, their valuable data must mature with their business. This may require a journey to the cloud, SLA changes which optimize storage costs, classification to mitigate risk, and moving the right data to additional key AI platform initiatives. A simple, scalable, high-performance data classification engine, Enterprise Insights delivers next-generation data lifecycle management for storage optimization, security and risk optimization, and IT business optimization. Enterprise Insights Approach to Successful Data Optimization: Identify – Securely analyze PBs of unstructured data across on premises (NAS & object) and cloud (files/objects & SaaS) sources by harnessing the power of the platform's rapid insights and auto-discover technologies, which can reduce data identification times by 1,000%. Classify – Quickly identify key client data attributes for cost savings, risk mitigation, and business impact with simple to consume dashboards and drill down capabilities. Review – Confidently create and take actions by leveraging the comprehensive search engine to quickly find and preview data for movement without ever leaving the platform. Remediate – Seamlessly take action (migrate and tier) on classified data to ensure it's properly protected, optimally stored, and most effectively serving the business. Enterprise Insights offers three use case-driven insight analysis modules: Storage and Migration Optimization – Insights into over 35 file data attributes including systems' aged, stale, obsolete, redundant, trivial, and types of systems files. Business Optimization – Insight into and classification by business units' or cost centers' aged, stale, obsolete, redundant, trivial, and types of files. Data Security and Risk Optimization – Insights into files containing PII and SPII, financial, legal, security, and risk data, as well as open shares and other network & storage security vulnerabilities. By leveraging Enterprise Insights, clients can classify data for simple and secure migration both on premise and in the cloud. Equally important is Insights data tiering capabilities, enabling users to match data storage costs to data usage. Powered by the Classify360 Platform, Enterprise Insights' secure hybrid approach to data analysis scales capabilities to exabyte levels at unmatched speed. Enterprise Insights is the industry's most powerful weapon to tackle the costs, time, and complexity of cloud migration projects, backup modernization, storage tiering, hardware refresh, and security posture management. By providing users with dashboards highlighting their existing storage costs and risks, Enterprise Insights frees clients from hidden, legacy, CapEx and OpEx expenditures, performance, and scalability bottlenecks while discovering and acting on sensitive and risk data. Unstructured data insanity is treating all data equally with zero insights into its business impact, said Brian Davidson, Chief Executive Officer and Managing Partner of Congruity360. Enterprise Insights is the first step in implementing optimized data lifecycle management. With historically high data growth and new business uses for unstructured data, it is essential to attack the costs and risks inherent in unmanaged data. Our customers have realized 7-10x returns on their data lifecycle management implementations while reducing risk in an auditable compliance framework. As AI continues to gain steam, don't overpay by moving useless data to your expensive AI platforms. The Classify360 Platform is comprehensive, simple to implement, scale, and operate. Businesses leverage the Classify360 Platform for unstructured data discovery, classification, business workflows, remediation actions, and insightful reporting. Congruity360 continues to tackle additional data governance challenges through innovations to the Classify360 Platform to continue delivering revolutionary data governance and classification, at scale, to the enterprise world. ABOUT CONGRUITY360 Congruity360 delivers the only data life cycle management solution built on a foundation of classification, by expert data storage engineers alongside expert data privacy consultants. The Classify360 Platform is easy to implement, requires no outside consultants, and quickly analyzes your data at the petabyte scale in days, not weeks or months.

Read More

Big Data Management

Microsoft's AI Data Exposure Highlights Challenges in AI Integration

Microsoft | September 22, 2023

AI models rely heavily on vast data volumes for their functionality, thus increasing risks associated with mishandling data in AI projects. Microsoft's AI research team accidentally exposed 38 terabytes of private data on GitHub. Many companies feel compelled to adopt generative AI but lack the expertise to do so effectively. Artificial intelligence (AI) models are renowned for their enormous appetite for data, making them among the most data-intensive computing platforms in existence. While AI holds the potential to revolutionize the world, it is utterly dependent on the availability and ingestion of vast volumes of data. An alarming incident involving Microsoft's AI research team recently highlighted the immense data exposure risks inherent in this technology. The team inadvertently exposed a staggering 38 terabytes of private data when publishing open-source AI training data on the cloud-based code hosting platform GitHub. This exposed data included a complete backup of two Microsoft employees' workstations, containing highly sensitive personal information such as private keys, passwords to internal Microsoft services, and over 30,000 messages from 359 Microsoft employees. The exposure was a result of an accidental configuration, which granted "full control" access instead of "read-only" permissions. This oversight meant that potential attackers could not only view the exposed files but also manipulate, overwrite, or delete them. Although a crisis was narrowly averted in this instance, it serves as a glaring example of the new risks organizations face as they integrate AI more extensively into their operations. With staff engineers increasingly handling vast amounts of specialized and sensitive data to train AI models, it is imperative for companies to establish robust governance policies and educational safeguards to mitigate security risks. Training specialized AI models necessitates specialized data. As organizations of all sizes embrace the advantages AI offers in their day-to-day workflows, IT, data, and security teams must grasp the inherent exposure risks associated with each stage of the AI development process. Open data sharing plays a critical role in AI training, with researchers gathering and disseminating extensive amounts of both external and internal data to build the necessary training datasets for their AI models. However, the more data that is shared, the greater the risk if it is not handled correctly, as evidenced by the Microsoft incident. AI, in many ways, challenges an organization's internal corporate policies like no other technology has done before. To harness AI tools effectively and securely, businesses must first establish a robust data infrastructure to avoid the fundamental pitfalls of AI. Securing the future of AI requires a nuanced approach. Despite concerns about AI's potential risks, organizations should be more concerned about the quality of AI software than the technology turning rogue. PYMNTS Intelligence's research indicates that many companies are uncertain about their readiness for generative AI but still feel compelled to adopt it. A substantial 62% of surveyed executives believe their companies lack the expertise to harness the technology effectively, according to 'Understanding the Future of Generative AI,' a collaboration between PYMNTS and AI-ID. The rapid advancement of computing power and cloud storage infrastructure has reshaped the business landscape, setting the stage for data-driven innovations like AI to revolutionize business processes. While tech giants or well-funded startups primarily produce today's AI models, computing power costs are continually decreasing. In a few years, AI models may become so advanced that everyday consumers can run them on personal devices at home, akin to today's cutting-edge platforms. This juncture signifies a tipping point, where the ever-increasing zettabytes of proprietary data produced each year must be addressed promptly. If not, the risks associated with future innovations will scale up in sync with their capabilities.

Read More

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