Read this white paper to learn how a Semantic Layer enables Analytics & Data Science Teams the ability to execute their jobs more effectively and efficiently.
All leading companies are building AI environments and leveraging data and analytics to extend their competitive advantage in their chosen markets. AI, data, and analytics are complex endeavors that require intelligence, resources, investment, vision, and fortitude. Not all companies have these attributes.
One of the most challenging problems faced by Analytics & Data Science Teams in all the years that I have been involved in the advanced analytics and AI field is arriving at a common definition of data describing – data elements, relationships between data elements, people, processes, time, geography, models, rates of change, and concepts.
This white paper will explain how the Semantic Layer is a solution to this problem. It’s where we as collaborators and companies as a whole decide, define, and document their agreement of definitions of data, processes, people, analytical models and more.
About the Author
John K. Thompson, Best Selling Author, Foremost Analytics Thought Leader
John is the author of the best-selling book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement. The book outlines how to hire and manage high-performance advanced analytics teams. The book outlines how to engage with executives and senior managers. How to select and undertake analytics projects that change and improve how a business operates.
John is an international technology executive with over 35 years of experience in the fields of data, advanced analytics and artificial intelligence (AI). He has been responsible for the global advanced analytics and AI function at a leading biopharmaceutical company where he led a team that developed and deployed over 25 analytical applications in 3 years.
Mr. Thompson’s technology expertise includes all aspects of advanced analytics and information management including – descriptive, predictive and prescriptive analytics, artificial intelligence, analytical applications, deep learning, cognitive computing, big data, simulation, optimization, synthetic data, and high performance computing.