“Universal” semantic layer tools introduced in recent years promise to standardize business metrics across the data stack, and eliminate silos of metrics trapped in semantic layers that are limited to specific data sources or BI platforms. This post offers considerations for adopting a universal semantic layer.
Published at: https://www.eckerson.com/articles/the-universal-semantic-layer-more-than-enough

The Universal Semantic Layer: More Than Enough?

The need for an independent semantic layer continues to rise as data science gains traction in the enterprise. Its five primary elements—metrics, caching, metadata management, APIs, and access controls—support AI/ML use cases as part of data science projects.
Published at: 
https://www.eckerson.com/articles/why-and-how-to-enable-data-science-with-an-independent-semantic-layer

Why and How to Enable Data Science with an Independent Semantic Layer - Audio Blog

Data modeling is a core skill of data engineering, but it is missing or inadequate in many data engineering teams. These teams focus on moving data with little attention to shaping the data. They engineer processes, not products. Full data engineering is both process and product engineering, and that calls for data modeling.
Published at:
https://www.eckerson.com/articles/a-fresh-look-at-data-modeling-part-2-rediscovering-the-lost-art-of-data-modeling

A Fresh Look at Data Modeling Part 2: Rediscovering the Lost Art of Data Modeling - Audio Blog

Listen to data and analytics leaders share the secrets of their success. Wayne Eckerson, long-time global thought leader interviews guests who run data and analytics programs at Fortune 2000 organizations around the world. Tune in to stay abreast of the latest technologies, techniques, and trends in our fast-paced industry.

New tracks tagged #SemanticLayer