Introduction to Multidimensional Data Model Design - SQL Server Analysis Services 2012 Cube Development - page 6

Choosing multidimensional or Tabular
Models
Given the complimentary nature of managed and Self-Service data environments, it's
reasonable to assume that in most organizations, at least one data warehouse will
exist and will be available as the primary source of information.
Prior to the introduction of Tabular Models, cubes were often implemented as the out-
ermost information interface for reporting and analysis. This configuration provided
preaggregated values, ad-hoc analysis functionality, and a central store for business
calculations. However, the development and maintenance of the Cube is in the ex-
clusive domain of IT, and the business calculations are written in the MultiDimen-
sional eXpressions ( MDX ) language (not the easiest of languages to learn). So,
cubes are the logical (multidimensional) extension of the managed data environment.
They provide high quality information and are consistent as well as fast to query, but
dependent on their defined relational sources and, as a result, often slow to respond
to changing needs.
The Tabular Model, like cubes part of the Analysis Services platform and multidimen-
sional in nature offers much greater flexibility for the introduction of new data sources
and subsequent definition of new dimensions, attributes, and measures.
Note
No formal ETL or data modeling is required; so, turnaround times for updates are
greatly reduced, and no MDX is needed in order to define calculated values, as
this is done via the new language, Data Analysis Expressions ( DAX ). Though
the DAX language is considered by many to be easier to learn and use than MDX,
it is not, in its current version, as capable as MDX. So, while certain basic op-
erations are easier to express in DAX compared to MDX, implementing complex
calculations is much more difficult using DAX. Although this topic isn't dedicated
to MDX or DAX, you can learn about the useful constructs of these languages in
Chapter 6 , MDX and Chapter 10 , DAX Calculations and Queries .