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

Moving a Power BI Data Model to Tabular

Ginger Grant provides some tips on migrating from a Power BI data model to an Analysis Services Tabular model: Unless you are upgrading to analysis services on SQL Server 2019, chances are you are going to have to review your DAX code and make some modifications as DAX on the other versions of SQL Server […]

Read More

Auditing Azure Analysis Services

Kasper de Jonge shows how you can audit an Azure Analysis Services cube: So the question was: how can I see who connected to my AS Azure database and what queries where send? Initially I thought of ways I used to do this in the on premises world. Capture profiler traces or XEvents by writing […]

Read More

Categories

October 2016
MTWTFSS
« Sep Nov »
 12
3456789
10111213141516
17181920212223
24252627282930
31