Data Visualization
Article | March 15, 2024
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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Text Analytics, Business Intelligence, Data Visualization
Article | June 21, 2024
Introduction
Data modeling is the study of data objects and their interactions with other things. It's used to research data requirements for a variety of business requirements. The data models are created to store the data in a database. Therefore, instead of focusing on what processes we must conduct, the data modeling methodologies focuses on what data is required and how to organize it.
Data modeling techniques facilitate the integration of high-level business processes with data structures, data rules, and the technical execution of physical data. Data modeling best parctices bring your company's operations and data usage together in a way that everyone can comprehend.
As 2.5 quintillion bytes of data are created every day, enterprises and business organizations are compelled to use data modeling techniques to handle them efficiently.
Data modeling for businesses reduces the budget for programming by up to 75%.
It typically consumes less than 10% of a project budget.
“The ability to take data – to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it – is going to be a hugely important skill in the next decades.”
- Hal Varian, Chief Economist, Google
Top Techniques to Enhance Your Data Modeling for Business
Data modeling methodology helps create a conceptual model and establish relationships between objects. The three perspectives of a data model are dealt with in the primary data modeling techniques. And they are conceptual, logical, and physical data models.
Let us look into some essential data modeling techniques to accelerate your business.
Have a Visualization of the Data You're Going to Model
It's unconvincing to think that staring at endless rows and columns of alphanumeric entries will lead to enlightenment. On the contrary, most people are significantly more comfortable inspecting and joining data tables using drag-and-drop screen interfaces or looking at graphical data representations that make it quick to spot any irregularities.
These types of data visualization techniques assist you in cleaning your data so that it is comprehensive, consistent, and free of errors and redundancies. They also help you identify distinct data record types that correspond to the same real-life entity, allowing you to change them to use standard fields and formats, making it easier to combine data sources.
Recognize the Business Requirements and Desired Outcomes
The purpose of data modeling best practices is to improve the efficiency of an organization. As a data modeler, you can only collect, organize, and store data for analysis if you understand your company's requirements.
Obtain feedback from business stakeholders to create conceptual and logical data models tailored to the company's needs. Collect data requirements from business analysts and other subject matter experts to aid in developing more comprehensive logical and physical models from the higher-level models and business requirements. Data models must change in response to changes in business and technology.
As a result, a thorough grasp of the company, its needs, goals, expected outcomes, and the intended application of the data modeling mission's outputs is a critical data modeling technique to follow.
According to IBM, “Data models are built around business needs. Rules and requirements are defined upfront through feedback from business stakeholders so they can be incorporated into the design of a new system or adapted in the iteration of an existing one.”
Distinguish Between Facts, Dimensions, Filters, and Order when Dealing with Business Enquiries
Understanding how these four parts characterize business questions will help you organize data in ways that make providing answers easier. For example, you may make locating the top sales performers per sales period easier and answer other business intelligence queries by structuring your data using different tables for facts and dimensions.
Before Continuing, Double-Check Each Stage of your Data Modelling.
Before going on to the next stage, each action should be double-checked, beginning with the data modeling priorities derived from the business requirements. For example, a dataset's main key must be chosen so that the primary key's value in each record may be used to identify each in the dataset uniquely. The same data modeling technique can check that joining two datasets is either one-to-one or one-to-many and avoid many-to-many interactions that lead to too complicated or unmanageable data models.
Instead of Just Looking for Correlation, Look for Causation
Data modeling best practices offers instructions on how to use the modeled data. While allowing end-users to access business intelligence on their own is a significant step forward, it's equally critical that they don't make mistakes.
They may notice, for example, that sales of two different products appear to grow and fall in lockstep. Are sales of one product driving sales of the other, or do they rise and fall in lockstep due to another factor like the economy or weather? Confusing causality and correlation could lead businesses to lose resources by focusing on the wrong or non-existent possibilities.
Summing Up
Data modeling can assist companies in quickly acquiring answers to their business concerns, improving productivity, profitability, efficiency, and customer happiness, among other things. Linking to corporate needs and objectives and employing tools to speed up the procedures in preparing data for replies to all inquiries are critical success elements and part of data modeling techniques.
Once these prerequisites are met, you can anticipate your data modeling to provide significant business value to you and your company, whether small, medium, or large.
Frequently Asked Questions
What are some of the crucial data modeling techniques?
There are many crucial data modeling techniques in the business. Some of them are:
Hierarchical data model
Network data model
Relational data model
Object-oriented data model
Entity-relationship data model
Data model with dimensions
Data model based on graphs
What are data modeling techniques?
Data modeling is optimizing data to streamline information flow inside businesses for various business needs. It improves analytics by formatting data and its attributes, creating links between data, and organizing data.
Why is data modeling important?
Data modeling is essential as a clear representation of data makes it easier to analyze it correctly. Also, it helps stakeholders to make data-driven decisions as data modeling improves data quality.
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Data Science
Article | March 13, 2024
There is no dispute that brands that harness and invest in data capabilities will be the ones to realize their maximum revenue potential. However, while today's marketers have access to a multitude of data sources, understanding what data to use and how to utilize it are two of the biggest challenges for all.
Data utilization in companies is an inconsistent experience. Some businesses have sensibly invested in improving their data maturity.
They can pivot quickly to maximize income potential in an unstable economic environment. Others face a cycle of declining returns as they try to reproduce previous achievements with variable outcomes.
Importance of Data Maturity for Businesses
Understanding your organization's data maturity is critical for five reasons. An understanding of data maturity may assist marketers in:
Align
Recognize which problems and challenges the wider organization is attempting to solve and modify techniques to support those goals.
Appreciate
Analyze honestly what the company is good at doing presently and where adjustments are needed to create better data decision-making.
Evaluate
Measure data literacy levels while implementing training and upskilling resources to facilitate the implementation of an open learning environment to encourage innovative thinking.
Anticipate
As the company's data capabilities develop, look forward to significantly advanced analytics possibilities.
Calibrate
Optimize technology and infrastructure to extract maximum value now while also appropriately planning for future resources.
Future-Proof Your Business with Data Maturity
Data maturity applies to the whole organization. It is a company-wide effort that extends beyond the goals of a single sales or marketing team.
As a result, it's critical to bring together diverse internal influencers to determine how improvements to your data strategy can assist everyone in achieving the same objectives. The mix of stakeholders is unique to each organization, so it will be determined by your company's priorities.
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Business Intelligence, Enterprise Business Intelligence
Article | July 10, 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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