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%.