Understanding Big Data and Artificial Intelligence

SHAIVI CHAPALGAONKAR | June 18, 2021 | 629 views

Data is an important asset. Data leads to innovation and organizations tend to compete for leading these innovations on a global scale. Today, every business requires data and insights to stay relevant in the market. Big Data has a huge impact on the way organizations conduct their businesses. Big Data is used in different enterprises like travel, healthcare, manufacturing, governments, and more.  If they need to determine their audience, understand what clients want, forecast the needs of the customers and the clients, AI and big data analysis is vital to every decision-making scenario. When companies process the collected data accurately, they get the desired results, which leads them to their desired goals.

The term Big Data has been around since the 1990s. By the time we could fully comprehend it, Big Data had already amassed a huge amount of stored data. If this data is analyzed properly, it would reveal valuable industry insights into the industry to which the data belonged.

IT professionals and computer scientists realized that going through all of the data and analyzing it for the purpose was too big of a task for humans to undertake. When artificial intelligence (AI) algorithm came into the picture, it accomplished analyzing the accumulated data and deriving insights. The use of AI in Big Data is fundamental to get desired results for organizations.

According to Northeastern University, the amount of data in the world was 4.4 zettabytes in 2013. By of 2020, the data rose to 44 zettabytes.

When there is this amount of data produced globally, this information is invaluable to the enterprises and now can leverage AI algorithms to process it. Because of this, the companies can understand and influence customer behavior. By 2018, over 50% of countries had adopted Big Data.

Let us understand what Big Data, convergence of big data and AI, and impact of AI on big data analytics. 

Understanding Big Data

In simple words, Big Data is a term that comprises every tool and process that helps people use and manage vast sets of data. According to Gartner, Big Data is a “high-volume and/or high-variety information assets that demand cost-effective, innovative forms of information processing to enable enhanced insight, decision-making, and process automation.”

The concept of Big Data was created to capture trends, preferences, and user behavior in one place called the data lake. Big Data in enterprises can help them analyze and configure their customers’ motivations and come up with new ideas for the creation of new offerings. Big Data studies different methods of extracting, analyzing, or dealing with data sets that are too complicated for traditional data processing systems. To analyze a large amount of data requires a system designed to stretch its extraction and analysis capability.

Data is everywhere. This stockpile of data can give us insights and business analytics to the industry belonging to the data set. Therefore, the AI algorithms are written to benefit from large and complex data.

Importance of Big Data

Data is an integral part of understanding customer demographics and their motivations.
When customers interact with technology in active or passive manner, these actions create a new set of data. What contributes to this data creation is what they carry with them every day - their smartphones. Their cameras, credit cards, purchased products all contribute to their growing data profile. A correctly done analysis can tell a lot about their behavior patterns, personality, and events in the customer’s life. Companies can use this information to rethink their strategies, improve on their product, and create targeted marketing campaigns, which would ultimately lead them to their target customer.

Industry experts, for years and years, have discussed Big Data and its impact on businesses. Only in recent years, however, has it become possible to calculate that impact. Algorithms and software can now analyze large datasets quickly and efficiently.The forty-four zettabyte of data will only quadruple in the coming years. This collection and analysis of the data will help companies get the AI insights that will aid them in generating profits and be future-ready.

Organizations have been using Big Data for a long time. Here’s how those organizations are using Big Data to drive success:

Answering customer questions

Using big data and analytics, companies can learn the following things:

• What do customers want?
• Where are they missing out on?
• Who are their best and loyal customers?
• Why people choose different products?

Every day, as organizations gather more information, they can get more insights into sales and marketing. Once they get this data, they can optimize their campaigns to suit the customer’s needs. Learning from their online habits and with correct analysis, companies can send personalized promotional emails. These emails may prompt this target audience to convert into full-time customers.

Making confident decisions

As companies grow, they all need to make complex decisions. With in-depth analysis of marketplace knowledge, industry, and customers, Big Data can help you make confident choices. Big Data gives you a complete overview of everything you need to know. With the help of this, you can launch your marketing campaign or launch a new product in the market, or make a focused decision to generate the highest ROI. Once you add machine learning and AI to the mix, your Big Data collections can form a neural network to help your AI suggest useful company changes.

Optimizing and Understanding Business Processes

Cloud computing and machine learning help you to stay ahead by identifying opportunities in your company’s practices. Big Data analytics can tell you if your email strategy is working even when your social media marketing isn’t gaining you any following. You can also check which parts of your company culture have the right impact and result in the desired turnover. The existing evidence can help you make quick decisions and ensure you spend more of your budget on things that help your business grow.

Convergence of Big Data and AI

Big Data and Artificial Intelligence have a synergistic relationship. Data powers AI. The constantly evolving data sets or Big Data makes it possible for machine learning applications to learn and acquire new skills. This is what they were built to do. Big Data’s role in AI is supplying algorithms with all the essential information for developing and improving features, pattern recognition capabilities.

AI and machine learning use data that has been cleansed of duplicate and unnecessary data. This clean and high-quality big data is then utilized to create and train intelligent AI algorithms, neural networks, and predictive models.

AI applications rarely stop working and learning. Once the “initial training” is done (initial training is preparing already collected data), they adjust their work as and when the data changes. This makes it necessary for data to be constantly collected.

When it comes to businesses using this technology, AI helps them use Big Data for analytics by making advanced tools accessible and obtainable to help users gain insights that would otherwise have been hidden in the huge amount of data. Once firms and businesses gain a hold on using AI and Big Data, they can provide decision-makers with a clear understanding of factors that affect their businesses. 

Impact of AI on Big Data Analytics

AI supports users in the Big Data cycle, including aggregation, storage, and retrieval of diverse data types from different data sources. This includes data management, context management, decision management, action management, and risk management.

Big Data can help alert problems and help find new solutions and get ideas about any new prospects. With the amount of information stream that comes in, it can be difficult to determine what is important and what isn’t. This is where AI and machine learning come in. It can help identify unusual patterns in the processes, help in the analysis, and suggest further steps to be taken.

It can also learn how users interact with analytics and learn subtle differences in meanings or context-specific nuances to understand numeric data sources. AI can also caution users about anomalies, unforeseen data patterns, monitoring events, and threats from system logs or social networking data.

Application of Big Data and Artificial Intelligence

After establishing how AI and Big Data work together, let us look at how some applications are benefitting from their synergy:

Banking and financial sectors

The banking and financial sectors apply these to monitor financial marketing activities. These institutions also use AI to keep an eye on any illegal trading activities. Trading data analytics are obtained for high-frequency trading, and decision making based on trading, risk analysis, and predictive analysis. It is also used for fraud warning and detection, archival and analysis of audit trails, reporting enterprise credit, customer data transformation, etc.

Healthcare

AI has simplified health data prescriptions and health analysis, thus benefitting healthcare providers from the large data pool. Hospitals are using millions of collected data that allow doctors to use evidence-based medicine. Chronic diseases can be tracked faster by AI.

Manufacturing and supply chain

AI and Big Data in manufacturing, production management, supply chain management and analysis, and customer satisfaction techniques are flawless. The quality of products is thus much better with higher energy efficiency, reliable increase in levels, and profit increase.

Governments

Governments worldwide use AI applications like facial recognition, vehicle recognition for traffic management, population demographics, financial classifications, energy explorations, environmental conservation, criminal investigations, and more.

Other sectors that use AI are mainly retail, entertainment, education, and more.

Conclusion

According to Gartner’s predictions, artificial intelligence will replace one in five workers by 2022. Firms and businesses can no longer afford to avoid using artificial intelligence and Big Data in their day-to-day. Investments in AI and Big Data analysis will be beneficial for everyone. Data sets will increase in the future, and with it, its application and investment will grow over time. Human relevance will continue to decrease as time goes by.

AI enables machine learning to be the future of the development of business technologies. It will automate data analysis and find new insights that were previously impossible to imagine by processing data manually. With machine learning, AI, and Big Data, we can redraw the way we approach everything else.

Frequently Asked Questions

Why does big data affect artificial intelligence?

Big Data and AI customize business processes and make better-suited decisions for individual needs and expectations. This improves its efficiency of processes and decisions. Data has the potential to give insights into a variety of predicted behaviors and incidents.

Is AI or big data better?

AI becomes better as it is fed more and more information. This information is gathered from Big Data which helps companies understand their customers better. On the other hand, Big Data is useless if there is no AI to analyze it. Humans are not capable of analyzing the data on a large scale.

Is AI used in big data?

When the gathered Big Data is to be analyzed, AI steps in to do the job. Big Data makes use of AI.

What is the future of AI in big data?

AI’s ability to work so well with data analytics is the primary reason why AI and Big Data now seem inseparable. AI machine learning and deep learning are learning from every data input and using those inputs to generate new rules for future business analytics.

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Leveraging Big Data for Competitive Advantage: Benefits

Article | July 18, 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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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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Performance Management

Implementing Data Analytics: Emerging Big Data Tools in 2023

Article | May 30, 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

In the fast-paced world of data-driven decision-making, having a solid understanding of BI is essential. Explore a handpicked selection of top books that cover everything a data professional needs. In today's data-driven landscape, businesses face the ongoing challenge of deriving meaningful insights from vast amounts of data to facilitate informed decision-making. This is where the field of business intelligence (BI) becomes crucial. Business intelligence encompasses a range of processes, technologies, and strategies that empower organizations to transform raw data into valuable insights, thereby driving business success. Access to comprehensive and insightful information is critical whether you're new to the field and seeking foundational knowledge or an experienced professional aiming to enhance your skills. This article will explore a curated selection of the best business intelligence books that offer valuable knowledge, practical guidance, and strategic insights. These books cover various facets of BI, including fundamental concepts, methodologies, agile approaches, data mining techniques, and cultural considerations. By delving into these essential resources, you will learn the tools and understanding necessary to navigate the complex realm of business intelligence, harness the full potential of your organization's data assets, and propel your business forward. 1. Business Intelligence Elizabeth Vitt, Michael Luckevich, Stacia Misner ‘Business Intelligence, 1st Edition’ presents a comprehensive approach to empower readers with the vital knowledge and expertise needed to thrive in the dynamic field of business intelligence (BI). Co-authored by Elizabeth Vitt, Michael Luckevich, and Stacia Misner, this BI book is an invaluable resource catering to both beginners and seasoned professionals within the realm of business intelligence. Setting the stage, the book lays a solid foundation by illuminating fundamental concepts in business intelligence. It adeptly demonstrates how organizations can harness the power of massive data repositories to glean invaluable business insights, enabling them to make informed decisions swiftly and effectively regarding customers, partners, and operational aspects. 'Business Intelligence' guides readers through the intricacies of leveraging business intelligence insights to seamlessly amalgamate information, individuals, and cutting-edge technologies. Armed with this knowledge, readers gain the confidence to devise and execute successful business strategies with precision. 2. Business Intelligence: Data Mining and Optimization for Decision Making Carlo Vercellis In the book 'Business Intelligence: Data Mining and Optimization for Decision Making,' Carlo Vercellis explores the crucial intersection between data mining, optimization techniques, and decision-making processes within the field of business intelligence. The author starts by laying the groundwork for business intelligence and introduces key concepts such as data warehousing, data mining and its applications, machine learning, supply optimization models, decision support systems, and analytical methods for performance evaluation, setting the stage for a holistic approach to business intelligence. The book emphasizes the practical application of data mining and optimization techniques through real-world examples and case studies. 'Business Intelligence: Data Mining and Optimization for Decision Making' though aimed at postgraduate students, is an essential resource for professionals and researchers interested in harnessing the power of data mining, optimization, and decision support systems. 3. Business Intelligence: An Essential Beginner’s Guide to BI Richard Hurley 'Business Intelligence: An Essential Beginner's Guide to BI, Big Data, Artificial Intelligence, Cybersecurity, Machine Learning, Data Science, Data Analytics, Social Media, and Internet Marketing,' provides a comprehensive introduction to the diverse and interconnected world of modern business intelligence. As the title suggests, this business intelligence book goes beyond traditional BI and explores emerging technologies shaping the business landscape. It delves into big data, providing insights into the challenges and opportunities associated with processing and analyzing massive datasets. Hurley introduces artificial intelligence (AI), machine learning (ML), and pattern recognition to explain their potential applications in driving business intelligence and decision-making. The book also addresses the critical roles that social media and internet marketing play in the growth of BI and how these platforms can be leveraged to gather valuable business intelligence insights and engage with customers effectively. 4. Business Intelligence: And How It Can Help You Grow Your Business Johan Faerch This book offers a practical and insightful guide to leveraging business intelligence strategies and techniques to drive business growth. This BI book is designed to empower entrepreneurs, business owners, and managers with the knowledge and tools necessary to make informed decisions and unlock the full potential of their organizations. It begins by introducing the concept of business intelligence and its significance in today's competitive marketplace and explains how BI goes beyond mere data analysis and reporting, acting as a catalyst for growth and innovation. The author highlights the transformative power of BI, demonstrating how it can provide a deep understanding of market trends, customer preferences, and internal operations. 'Business Intelligence: And How It Can Help You Grow Your Business' is a highly accessible and practical resource that bridges the gap between theory and real-world application. Johan Faerch's expertise and experience in the field, shines through as he provides valuable business intelligence insights and actionable strategies for harnessing the power of BI to achieve business growth. 5. Growing Business Intelligence Larry Burns 'Growing Business Intelligence: An Agile Approach to Leveraging Data and Analytics for Maximum Business Value' offers a comprehensive guide to unlocking the full potential of business intelligence (BI) through an agile and adaptable framework. This BI book provides practical insights and strategies for effectively utilizing data and analytics to drive continuous growth and optimize business value. With a keen focus on core principles, the book highlights the importance of navigating the complexities of BI architecture to find the most suitable path for each unique organization. The book serves as a trusted resource, guiding readers on effectively managing the risks associated with disruptive technologies and adopting agile methodologies to deliver on the promises of BI and analytics in a rapid, concise, and iterative manner. 'Growing Business Intelligence' is an invaluable asset for business leaders, managers, and data professionals involved in BI, analytics, or Big Data projects. It also caters to organizations aiming to maximize the value derived from their data and investments in BI technology. 6 Business Intelligence: A Comprehensive Approach to Information Needs, Technologies, and Culture Rimvydas Skyrius 'Business Intelligence: A Comprehensive Approach to Information Needs, Technologies, and Culture' by Rimvydas Skyrius delves deep into the multifaceted realm of business intelligence from various perspectives. This book looks at BI as a process driven by the synergistic blend of human capabilities and technological advancements and emphasizes the complex nature of information needs and decision-making support within organizations. It begins with a comprehensive introduction to the fundamental concepts of BI and related areas of information processing, navigating through the intricacies of BI, addressing data integration, information integration, and the processes & technologies involved. It further explores the maturity and agility of BI, delving into the components, drivers, and inhibitors of BI culture, as well as the soft factors like attention, sense, and trust that shape the BI landscape. Rimvydas, in this book, presents a holistic perspective view on business intelligence, possible structures and tradeoffs within the field of BI, providing readers with valuable insights. 7. Business Intelligence Strategy: A Practical Guide for Achieving BI Excellence John Boyer, Bill Frank, Brian Green, Tracy Harris, Kay Van De Vanter 'Business Intelligence Strategy: A Practical Guide for Achieving BI Excellence' serves as a comprehensive and practical guide for organizations aiming to develop and implement a successful business intelligence strategy that drives excellence and delivers tangible results. The book begins by emphasizing the strategic importance of BI in modern organizations, highlighting its role in enabling informed decision-making, improving operational efficiency, and fostering a data-driven culture. It guides readers through the process of creating business alignment strategies that help prioritize business requirements, build organizational & cultural strategies, increase IT efficiency, and promote user adoption. The authors emphasize the importance of engaging stakeholders and fostering collaboration between business and IT teams to ensure the strategy's effectiveness and long-term success. 'Business Intelligence Strategy' equip readers with the right tools and strategies to develop and implement a robust BI strategy that drives excellence and delivers measurable value to their organization. 8. Fundamentals of Business Intelligence (Data-Centric Systems and Applications) Wilfried Grossmann, Stefanie Rinderle-Ma 'Fundamentals of Business Intelligence' serves as a comprehensive and systematic introduction to the dynamic field of business intelligence , providing readers with strong foundational knowledge. This business intelligence book focuses on the transformation of process-oriented data into valuable information crucial for decision-making across diverse domains. The authors, Grossmann and Rinderle-Ma, follow a step-by-step approach to develop models and analytical tools that enable the acquisition of high-quality data structured in a manner conducive to applying complex analytical techniques. Covering a wide range of essential topics, the book delves into the fundamental concepts of business intelligence, the data-centric nature of BI, exploring various approaches to modeling in BI applications, data provisioning, data description, visualization, reporting, and more. The book seamlessly blends theoretical explanations with practical examples and compelling case studies to further enhance comprehension. 9. Business Intelligence: The Savvy Manager's Guide 1st Edition David Loshin 'Business Intelligence: The Savvy Manager's Guide' is an insightful resource offering, practical guidance and strategic insight to assist managers in comprehending, implementing, and maximizing the benefits of BI. Loshin initiates the journey by clearly describing the fundamental architectural components of a business intelligence environment. Topics covered range from traditional subjects such as business process modeling and data modeling to more contemporary areas like business rule systems, data profiling, information compliance and data quality, data warehousing, and data mining. The book follows a logical progression, starting with the establishment of a robust data model infrastructure, followed by data preparation, analysis, integration, knowledge discovery, and ultimately the practical utilization of the acquired knowledge. Loshin adeptly provides clear explanations devoid of technical jargon, coupled with in-depth descriptions that articulate the business value of emerging technologies while offering the necessary introductory technical background. The true strength of this book lies in its ability to bridge the gap between technical and managerial perspectives. 10. Business Intelligence: The Savvy Manager's Guide 2nd Edition David Loshin 'Business Intelligence: The Savvy Manager's Guide' by David Loshin is a comprehensive resource that equips managers with the knowledge and insights necessary to effectively navigate the field of business intelligence.The book covers the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. The author also explores key factors to be taken into account in the planning and execution of a successful BI program, considerations for developing a BI roadmap, the platforms for analysis, such as data warehouses, and the concepts of business metadata. 'Business Intelligence: The Savvy Manager's Guide' serves as an accessible resource for BI professionals, including senior and middle-level managers, Chief Information Officers, Chief Data Officers, senior business executives, business staff members, database or software engineers, and business analysts seeking to harness the power of BI in their organizations. Conclusion The field of business intelligence is ever-evolving and plays a vital role in the current data-driven business landscape. The books highlighted in this article provide a wealth of knowledge and insights for individuals at various stages of their BI journey. These business intelligence books collectively offer a comprehensive and diverse range of perspectives on business intelligence to promote growth and expertise. Whether you are a beginner seeking fundamental knowledge or a seasoned professional aiming to enhance your skills, these resources provide valuable insights and guidance for harnessing the power of BI to drive success in the modern business landscape.

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J.D. Power Acquires Autovista Group to Expand Automotive Data Portfolio

J.D. Power | September 18, 2023

J.D. Power, a prominent global leader in data analytics, has recently announced a definitive agreement to acquire Autovista Group, a renowned pan-European and Australian automotive data, analytics, and industry insights provider. This strategic acquisition complements J.D. Power's existing strengths in vehicle valuation and intricate vehicle specification data and analytics while significantly expanding its presence within the European and Australian automotive markets. This acquisition represents a crucial moment, as it delivers substantial value to the customers of both companies. It brings together Autovista Group's extensive European and Australian market intelligence with J.D. Power's market-leading predictive analytics, valuation data, and customer experience datasets. These complementary offerings will empower original equipment manufacturers (OEMs), insurers, dealers, and financing companies with a truly global perspective on critical industry trends. They will also provide the tools to accurately predict risk, capitalize on emerging trends, and align sales strategies with real-time market dynamics. Pete Cimmet, Chief Strategy Officer at J.D. Power, stated: The addition of Autovista Group broadens our global presence allowing us to serve our customers across key global markets including North America, Europe and Asia/Australia. We look forward to partnering with the Autovista team to launch innovative new products and pursue strategic add-on acquisitions in Europe and Australia. [Source: Business Wire] Autovista Group, through its five prominent brands—Autovista, Glass's, Eurotax, Schwacke, and Rødboka—standardizes and categorizes a multitude of technical attributes for nearly every vehicle manufactured in European and Australian markets. This comprehensive approach offers clients a 360-degree view of detailed vehicle data, which is invaluable for valuations, forecasts, and repair estimates. Furthermore, Autovista Group's robust analytical solutions and its team of seasoned experts are trusted by stakeholders across the automobile industry for their in-depth insights and benchmarks related to vehicle values, ownership, replacements, and repair costs. Under this agreement, Autovista Group's senior leadership, along with its 700 employees, will remain part of the organization, serving as J.D. Power's automotive data and analytics platform for Australia and Europe. Lindsey Roberts will continue to lead the team in her role as President of J.D. Power Europe, reporting to CEO Dave Habiger. Currently, Autovista Group is owned by Hayfin Capital Management, a prominent European alternative asset management firm. The anticipated closure of the Autovista Group acquisition is set for conclusion by the end of 2023, pending customary closing conditions and regulatory review and approval. For this transaction, RBC Capital Markets acted as the exclusive financial advisor, and Kirkland & Ellis provided legal counsel to J.D. Power. TD Cowen served as the exclusive financial advisor, with Macfarlanes, Cravath, Swaine & Moore, and Mishcon de Reya acting as legal advisors to Autovista Group and Hayfin. About J.D. Power J.D. Power, a renowned consumer insights, advisory services, and data and analytics firm, has consistently spearheaded the use of big data, artificial intelligence (AI), and algorithmic modeling to illuminate the intricacies of consumer behavior for more than half a century. With a storied legacy of providing in-depth industry intelligence on customer interactions with brands and products, J.D. Power serves as the trusted leader for the world's preeminent enterprises, spanning diverse major sectors, profoundly influencing and refining their customer-centric strategies.

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SQream Expands its End-To-End Low-Code Analytics Platform with Flex Connector AI Assistant

PR Newswire | August 17, 2023

SQream, the scalable data analytics company built for massive data stores and AI/ML workloads, announced today that its low-code ELT and analytics platform Panoply, is launching an AI Flex Connector helper which leverages generative AI to streamline the path to business intelligence. This tool will make it even easier for users to collect all of their business data - from CRMs, user applications, and other tools - into one single source, and further minimize the technical requirements to generate quick data insights. While there are multiple ingestion tools already on the market, these tools are often limited in terms of which data sources can connect with them. Released in April 2023, Panoply's Flex Connector has enabled greater platform flexibility by supporting connections to any RestAPI or GraphQL data source. The Flex Connector currently requires users or the Panoply Customer Success team to sift through multiple API documents to find the configuration that meets their needs, but the new Flex Connector AI helper takes these capabilities to the next level by removing this manual process and instead relying on generative AI to complete the required research. This will enable users to skip the majority of the steps previously required and provide a working configuration that analysts will then customize with minimal information (authentication details, domain names, dates etc.). "We're excited about the future of AI in data and how it can make data in general even simpler to use and more accessible for non-technical users," said Ittai Bareket, GM of SQream Americas and Panoply. "With our upcoming AI focused product enhancements, we're looking to automate and outsource the more technical and time consuming aspects of gaining insights from your data." The new feature is prompted by Open AI LLM models, which are deployed on Microsoft Azure and enable applications built on top of the LangChain framework, allowing users to switch between models in the future. The user provides two parameters to prompt the tool to scan the web for the most up-to-date API documentation of the selected service, and within it all the requirements needed to extract the selected resource. About Panoply by SQream Panoply's managed data warehouse plus ELT and dashboards make it easy for users to sync, store, access, and visualize their data without complex code. Panoply is a product line of SQream, a data analytics company that helps organizations break through barriers to ask the biggest, most important questions from their data. SQream's GPU-based technology empowers businesses to overcome dataset limits and query complexity to analyze exponentially more data, and get substantially faster insights at dramatic cost-savings. By leveraging SQream's advanced analytics capabilities for AI/ML, enterprises can stay ahead of their competitors while reducing hardware usage. If you want to take your data initiatives to the next level, Ask Bigger and unlock new opportunities with SQream. About SQream SQream is a data analytics company that helps organizations Ask Bigger by providing them with accurate insights at a lower cost. Our unique technology empowers businesses to analyze exponentially more data, and get substantially faster insights at dramatic cost-savings. By leveraging SQream's advanced analytics capabilities, organizations are able to stay ahead of their competitors while reducing hardware usage. If you want to take your data exploration to the next level, Ask Bigger and unlock new opportunities with SQream.

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Unravel Data Launches Cloud Data Cost Observability and Optimization for Google Cloud BigQuery

Business Wire | August 11, 2023

Unravel Data, the first AI-enabled data observability and FinOps platform built to address the speed and scale of modern data platforms, today announced the release of Unravel 4.8.1, enabling Google Cloud BigQuery customers to see and better manage their cloud data costs by understanding specific cost drivers, allocation insights, and performance and cost optimization of SQL queries. This launch comes on the heels of the recent BigQuery pricing model change that replaced flat-rate and flex slot pricing with three new pricing tiers, and will help BigQuery customers to implement FinOps in real-time to select the right new pricing plan based on their usage, and maximize workloads for greater return on cloud data investments. As today’s enterprises implement artificial intelligence (AI) and machine learning (ML) models, to continually garner more business value from their data, they are experiencing exploding cloud data costs, with a lack of visibility into cost-drivers and a lack of control for managing and optimizing their spend. As cloud costs continue to climb, managing cloud spend remains a top challenge for global business leaders. Data management services are the fastest-growing category of cloud service spending, representing 39% of the total cloud bill. Unravel 4.8.1 enables visibility into BigQuery compute and storage spend and provides cost optimization intelligence using its built-in AI to improve workload cost efficiency. Unravel’s purpose-built AI for BigQuery delivers insights based on Unravel’s deep observability of the job, user, and code level to supply AI-driven cost optimization recommendations for slots and SQL queries, including slot provisioning, query duration, autoscaling efficiencies, and more. With Unravel, BigQuery users can speed cloud transformation initiatives by having real-time cost visibility, predictive spend forecasting, and performance insights for their workloads. BigQuery customers can also use Unravel to customize dashboards and alerts with easy-to-use widgets that offer insights on spend, performance, and unit economics. “As AI continues to drive exponential data usage, companies are facing more problems with broken pipelines and inefficient data processing which slows time to business value and adds to the exploding cloud data bills. Today, most organizations do not have the visibility into cloud data spend or ways to optimize data pipelines and workloads to lower spend and mitigate problems,” said Kunal Agarwal, CEO and Co-founder, Unravel Data. “With Unravel’s built-in AI, BigQuery users have data observability and FinOps in one solution to increase data pipeline reliability and cost efficiency so that businesses can bring even more workloads to the cloud for the same spend.” “Enterprises are increasingly concerned about lack of visibility into and control of their cloud-related costs, especially for cloud-based analytics projects,” says Kevin Petrie, VP of Research at The Eckerson Group. "By implementing FinOps programs, they can predict, measure, monitor, optimize and account for cloud-related costs related to data and analytics projects." At the core of Unravel Data’s platform is its AI-powered Insights Engine, purpose-built for data platforms, which understands all the intricacies and complexities of each modern data platform and the supporting infrastructure to optimize efficiency and performance. The Insights Engine ingests and interprets the continuous millions of ongoing metadata streams to provide real-time insights into application and system performance, and recommendations to optimize costs and performance for operational and financial efficiencies. Unravel 4.8.1 includes additional features, such as: Recommendations for baseline and max setting for reservations Scheduling insights for recurring jobs SQL insights and anti-patterns Recommendations for custom quotas for projects and users Top-K projects, users, and jobs Showback by compute and storage types, services, pricing plans, etc. Chargeback by projects and users Out-of-the-box and custom alerts and dashboards Project/Job views of insights and details Side-by-side job comparisons Data KPIs, metrics, and insights such as size and number of tables and partitions, access by jobs, hot/warm/cold tables About Unravel Data Unravel Data radically transforms the way businesses understand and optimize the performance and cost of their modern data applications – and the complex data pipelines that power those applications. Providing a unified view across the entire data stack, Unravel’s market-leading data observability platform leverages AI, machine learning, and advanced analytics to provide modern data teams with the actionable recommendations they need to turn data into insights. A recent winner of the Best Data Tool & Platform of 2023 as part of the annual SIIA CODiE Awards, some of the world’s most recognized brands like Adobe, Maersk, Mastercard, Equifax, and Deutsche Bank rely on Unravel Data to unlock data-driven insights and deliver new innovations to market. To learn more, visit https://www.unraveldata.com.

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J.D. Power Acquires Autovista Group to Expand Automotive Data Portfolio

J.D. Power | September 18, 2023

J.D. Power, a prominent global leader in data analytics, has recently announced a definitive agreement to acquire Autovista Group, a renowned pan-European and Australian automotive data, analytics, and industry insights provider. This strategic acquisition complements J.D. Power's existing strengths in vehicle valuation and intricate vehicle specification data and analytics while significantly expanding its presence within the European and Australian automotive markets. This acquisition represents a crucial moment, as it delivers substantial value to the customers of both companies. It brings together Autovista Group's extensive European and Australian market intelligence with J.D. Power's market-leading predictive analytics, valuation data, and customer experience datasets. These complementary offerings will empower original equipment manufacturers (OEMs), insurers, dealers, and financing companies with a truly global perspective on critical industry trends. They will also provide the tools to accurately predict risk, capitalize on emerging trends, and align sales strategies with real-time market dynamics. Pete Cimmet, Chief Strategy Officer at J.D. Power, stated: The addition of Autovista Group broadens our global presence allowing us to serve our customers across key global markets including North America, Europe and Asia/Australia. We look forward to partnering with the Autovista team to launch innovative new products and pursue strategic add-on acquisitions in Europe and Australia. [Source: Business Wire] Autovista Group, through its five prominent brands—Autovista, Glass's, Eurotax, Schwacke, and Rødboka—standardizes and categorizes a multitude of technical attributes for nearly every vehicle manufactured in European and Australian markets. This comprehensive approach offers clients a 360-degree view of detailed vehicle data, which is invaluable for valuations, forecasts, and repair estimates. Furthermore, Autovista Group's robust analytical solutions and its team of seasoned experts are trusted by stakeholders across the automobile industry for their in-depth insights and benchmarks related to vehicle values, ownership, replacements, and repair costs. Under this agreement, Autovista Group's senior leadership, along with its 700 employees, will remain part of the organization, serving as J.D. Power's automotive data and analytics platform for Australia and Europe. Lindsey Roberts will continue to lead the team in her role as President of J.D. Power Europe, reporting to CEO Dave Habiger. Currently, Autovista Group is owned by Hayfin Capital Management, a prominent European alternative asset management firm. The anticipated closure of the Autovista Group acquisition is set for conclusion by the end of 2023, pending customary closing conditions and regulatory review and approval. For this transaction, RBC Capital Markets acted as the exclusive financial advisor, and Kirkland & Ellis provided legal counsel to J.D. Power. TD Cowen served as the exclusive financial advisor, with Macfarlanes, Cravath, Swaine & Moore, and Mishcon de Reya acting as legal advisors to Autovista Group and Hayfin. About J.D. Power J.D. Power, a renowned consumer insights, advisory services, and data and analytics firm, has consistently spearheaded the use of big data, artificial intelligence (AI), and algorithmic modeling to illuminate the intricacies of consumer behavior for more than half a century. With a storied legacy of providing in-depth industry intelligence on customer interactions with brands and products, J.D. Power serves as the trusted leader for the world's preeminent enterprises, spanning diverse major sectors, profoundly influencing and refining their customer-centric strategies.

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Business Intelligence, Big Data Management, Big Data

SQream Expands its End-To-End Low-Code Analytics Platform with Flex Connector AI Assistant

PR Newswire | August 17, 2023

SQream, the scalable data analytics company built for massive data stores and AI/ML workloads, announced today that its low-code ELT and analytics platform Panoply, is launching an AI Flex Connector helper which leverages generative AI to streamline the path to business intelligence. This tool will make it even easier for users to collect all of their business data - from CRMs, user applications, and other tools - into one single source, and further minimize the technical requirements to generate quick data insights. While there are multiple ingestion tools already on the market, these tools are often limited in terms of which data sources can connect with them. Released in April 2023, Panoply's Flex Connector has enabled greater platform flexibility by supporting connections to any RestAPI or GraphQL data source. The Flex Connector currently requires users or the Panoply Customer Success team to sift through multiple API documents to find the configuration that meets their needs, but the new Flex Connector AI helper takes these capabilities to the next level by removing this manual process and instead relying on generative AI to complete the required research. This will enable users to skip the majority of the steps previously required and provide a working configuration that analysts will then customize with minimal information (authentication details, domain names, dates etc.). "We're excited about the future of AI in data and how it can make data in general even simpler to use and more accessible for non-technical users," said Ittai Bareket, GM of SQream Americas and Panoply. "With our upcoming AI focused product enhancements, we're looking to automate and outsource the more technical and time consuming aspects of gaining insights from your data." The new feature is prompted by Open AI LLM models, which are deployed on Microsoft Azure and enable applications built on top of the LangChain framework, allowing users to switch between models in the future. The user provides two parameters to prompt the tool to scan the web for the most up-to-date API documentation of the selected service, and within it all the requirements needed to extract the selected resource. About Panoply by SQream Panoply's managed data warehouse plus ELT and dashboards make it easy for users to sync, store, access, and visualize their data without complex code. Panoply is a product line of SQream, a data analytics company that helps organizations break through barriers to ask the biggest, most important questions from their data. SQream's GPU-based technology empowers businesses to overcome dataset limits and query complexity to analyze exponentially more data, and get substantially faster insights at dramatic cost-savings. By leveraging SQream's advanced analytics capabilities for AI/ML, enterprises can stay ahead of their competitors while reducing hardware usage. If you want to take your data initiatives to the next level, Ask Bigger and unlock new opportunities with SQream. About SQream SQream is a data analytics company that helps organizations Ask Bigger by providing them with accurate insights at a lower cost. Our unique technology empowers businesses to analyze exponentially more data, and get substantially faster insights at dramatic cost-savings. By leveraging SQream's advanced analytics capabilities, organizations are able to stay ahead of their competitors while reducing hardware usage. If you want to take your data exploration to the next level, Ask Bigger and unlock new opportunities with SQream.

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Business Intelligence, Big Data Management, Data Science

Unravel Data Launches Cloud Data Cost Observability and Optimization for Google Cloud BigQuery

Business Wire | August 11, 2023

Unravel Data, the first AI-enabled data observability and FinOps platform built to address the speed and scale of modern data platforms, today announced the release of Unravel 4.8.1, enabling Google Cloud BigQuery customers to see and better manage their cloud data costs by understanding specific cost drivers, allocation insights, and performance and cost optimization of SQL queries. This launch comes on the heels of the recent BigQuery pricing model change that replaced flat-rate and flex slot pricing with three new pricing tiers, and will help BigQuery customers to implement FinOps in real-time to select the right new pricing plan based on their usage, and maximize workloads for greater return on cloud data investments. As today’s enterprises implement artificial intelligence (AI) and machine learning (ML) models, to continually garner more business value from their data, they are experiencing exploding cloud data costs, with a lack of visibility into cost-drivers and a lack of control for managing and optimizing their spend. As cloud costs continue to climb, managing cloud spend remains a top challenge for global business leaders. Data management services are the fastest-growing category of cloud service spending, representing 39% of the total cloud bill. Unravel 4.8.1 enables visibility into BigQuery compute and storage spend and provides cost optimization intelligence using its built-in AI to improve workload cost efficiency. Unravel’s purpose-built AI for BigQuery delivers insights based on Unravel’s deep observability of the job, user, and code level to supply AI-driven cost optimization recommendations for slots and SQL queries, including slot provisioning, query duration, autoscaling efficiencies, and more. With Unravel, BigQuery users can speed cloud transformation initiatives by having real-time cost visibility, predictive spend forecasting, and performance insights for their workloads. BigQuery customers can also use Unravel to customize dashboards and alerts with easy-to-use widgets that offer insights on spend, performance, and unit economics. “As AI continues to drive exponential data usage, companies are facing more problems with broken pipelines and inefficient data processing which slows time to business value and adds to the exploding cloud data bills. Today, most organizations do not have the visibility into cloud data spend or ways to optimize data pipelines and workloads to lower spend and mitigate problems,” said Kunal Agarwal, CEO and Co-founder, Unravel Data. “With Unravel’s built-in AI, BigQuery users have data observability and FinOps in one solution to increase data pipeline reliability and cost efficiency so that businesses can bring even more workloads to the cloud for the same spend.” “Enterprises are increasingly concerned about lack of visibility into and control of their cloud-related costs, especially for cloud-based analytics projects,” says Kevin Petrie, VP of Research at The Eckerson Group. "By implementing FinOps programs, they can predict, measure, monitor, optimize and account for cloud-related costs related to data and analytics projects." At the core of Unravel Data’s platform is its AI-powered Insights Engine, purpose-built for data platforms, which understands all the intricacies and complexities of each modern data platform and the supporting infrastructure to optimize efficiency and performance. The Insights Engine ingests and interprets the continuous millions of ongoing metadata streams to provide real-time insights into application and system performance, and recommendations to optimize costs and performance for operational and financial efficiencies. Unravel 4.8.1 includes additional features, such as: Recommendations for baseline and max setting for reservations Scheduling insights for recurring jobs SQL insights and anti-patterns Recommendations for custom quotas for projects and users Top-K projects, users, and jobs Showback by compute and storage types, services, pricing plans, etc. Chargeback by projects and users Out-of-the-box and custom alerts and dashboards Project/Job views of insights and details Side-by-side job comparisons Data KPIs, metrics, and insights such as size and number of tables and partitions, access by jobs, hot/warm/cold tables About Unravel Data Unravel Data radically transforms the way businesses understand and optimize the performance and cost of their modern data applications – and the complex data pipelines that power those applications. Providing a unified view across the entire data stack, Unravel’s market-leading data observability platform leverages AI, machine learning, and advanced analytics to provide modern data teams with the actionable recommendations they need to turn data into insights. A recent winner of the Best Data Tool & Platform of 2023 as part of the annual SIIA CODiE Awards, some of the world’s most recognized brands like Adobe, Maersk, Mastercard, Equifax, and Deutsche Bank rely on Unravel Data to unlock data-driven insights and deliver new innovations to market. To learn more, visit https://www.unraveldata.com.

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