Semantic Layers

Melissa Coates explains the relevance of Analysis Services as a semantic layer:

Part 1: Why a Semantic Layer Like Azure Analysis Services is Relevant {you are here}

Part 2: Where Azure Analysis Services Fits Into BI & Analytics Architecture {coming soon}

Fundamentally, Analysis Services serves as a semantic layer (see below for further discussion of a semantic layer). Because the business intelligence industry now embraces an array of technology choices, sometimes it seems like a semantic layer is no longer valued like it once was. Well, my opinion is that for many businesses, a semantic layer is tremendously important to support the majority of business users who do *not* want to do their own data wrangling, data prep, and data modeling activities.

We (I) spend so much time thinking about the Brave New World of massive blobs of semi-structured data that it’s a good idea to step back every once in a while and remember that yes, there is a need for sanitized, easy-to-consume data which answers known business questions.  The percentage of people at a company willing to create an R or Python notebook or run a MapReduce job is typically well under 5%.

Related Posts

Error Running Analysis Services Processing Task

Angela Henry ran into a problem with the SSIS Analysis Services processing task: In both of these scenarios you will not be able to save the package.  So what the heck are you supposed to do?!  Here’s where my tunnel vision (and panic) sets in.  How was I supposed to get my SSAS objects processed? […]

Read More

Gartner’s BI Magic Quadrant For 2018

Bruno Aziza looks at the new Gartner magic quadrant for business intelligence solutions: For the first time in 3 years, Gartner dropped a significant amount of vendors off its quadrant.  There were 24 vendors in the firm’s quadrant in 2016 and 2017.  This year, the Magic Quadrant only lists 20 vendors…that’s a 16% quadrant reduction.  Has […]

Read More


October 2016
« Sep Nov »