Data lakes and semantic layers have been around for a long time – each living in their own walled gardens, tightly coupled to fairly narrow use cases. As data and analytics infrastructure migrates to the cloud, many are challenging how these foundational technology components fit in the modern data and analytics stack. In this article, […]
What’s a Semantic Layer Worth?
There’s been a lot of talk about semantic layers lately. I’ve seen dozens of companies using a semantic layer to drive self-service analytics at scale. But even with all these success stories, I still get this question: “Is a semantic layer worth the effort?” In other words, is the juice worth the squeeze? So, how […]
The Rise of the Semantic Layer
Cloud giants like Google and Snowflake, unicorns like dbt Labs, and a host of venture-backed startups are now talking about a critical new layer in the data and analytics stack. Some call it a “metrics layer,” or a “metrics hub” or “headless BI,” but most call it a “semantic layer.” I prefer to call it a “semantic layer” because it best describes a business-friendly interface […]
Do You Need a Semantic Layer?
I co-founded my company to focus on the challenges of supporting a large number of data analysts working on disparate sets of data managed in a massive lake. We borrowed the term “semantic layer” from the folks at Business Objects, who originally coined it in the 1990s. The term was actually over 20 years old […]
The Semantic Layer Goes Mainstream
The semantic layer concept within the data stack is not new but is an increasingly popular topic of conversation. I predict that in 2022, we’ll see mainstream awareness of the semantic layer, especially as enterprises begin to see real-world examples of its benefits. The fact that industry leaders are discussing the need for a semantic […]