Why Read This?
What’s the semantic layer? How can your analytics team leverage it? How does it bridge AI & BI?
Read this bundle of Semantic Layer whitepapers to learn the key value propositions to implement a semantic layer and best practices for analytics success with one.
Companies need quicker and better insights and have hence deployed numerous data and analytics solutions across diverse data platforms – cloud and on-prem. This distributed set-up has created challenges in data quality, literacy, adoption and ultimately business performance.
The semantic layer can reduce complexity/costs, improve security, and streamline reporting for the business users in today’s complex data environments.
The semantic layer links the analytics consumption platform with the data platforms using the facts (data values), dimensions (data attributes) and hierarchies (i.e., taxonomies) in the Data Warehouse or any other cloud data platforms.
By abstracting the physical form and location of data, the semantic layer platform makes data stored in the canonical data platforms accessible with the one consistent and secure interface for the business users.
Managing Principal, DBP Institute and Professor at IE Business School
Dr. Prashanth Southekal is the Managing Principal of DBP Institute (www.dbpinstitute.com), a data and analytics consulting and education firm. Dr. Southekal has consulted for over 75 organizations including P&G, GE, Shell, Apple, and SAP. is the author of two books — “Data for Business Performance” and “Analytics Best Practices”
Global Head of AI & Rapid Data Lab, CSL Behring
John Thompson is an international technology executive with over 35 years of experience in the fields of data, advanced analytics, and AI. He is the author of “Analytics Teams: Leveraging Analytics and Artificial Intelligence for Business Improvement” and co-author of “Analytics: How to Win with Intelligence”.
Chief Technology Officer, Founder, AtScale
Dave is the founder of AtScale and is the Chief Technology Officer. Prior to AtScale, he ran engineering and data at Klout and Yahoo! where he built the world’s largest multi-dimensional cube.
Chief Decision Scientist, Gramener
Ganes Kesari is an entrepreneur, AI thought leader, author, and TEDx speaker. He co-founded Gramener, where he heads Data Science Advisory and Innovation. He advises executives on decision-making with data. He helps apply data science to solve organizational challenges, tell stories with data, and build winning analytics teams. Ganes contributes articles to leading magazines such as Forbes and Entrepreneur. He teaches guest lectures on data science in schools such as Princeton University and runs corporate training on transforming organizations with data & analytics.
Business Intelligence, Author and Speaker
Dr. Barry Devlin is a founder of the data warehousing industry, defining its first architecture in 1985. A foremost authority on business intelligence (BI), big data, and beyond, he is respected worldwide as a visionary and thought-leader in the evolving industry. Barry has authored two ground-breaking books: the classic “Data Warehouse–from Architecture to Implementation” and “Business unIntelligence–Insight and Innovation Beyond Analytics and Big Data” in 2013.