knowledge of a wide range of topics related to the design, querying, configuration, and administration of
BI semantic models in Microsoft SQLServer 2016 Analysis Services (SSAS). Approximately half the
exam covers multidimensional BI semantic models, while the remainder covers tabular BI semantic
models. In addition, there are new development and query language features available for tabular models
developed in SQLServer 2016, with which you should be familiar to successfully pass this exam.
For multidimensional models, the exam focuses not only on the steps required to design and develop
the model in SQLServer Data Tools (SSDT), but also tests your understanding of the supported types of
dimension models, the options for implanting measures, and the configuration of properties to enable
specific behaviors, such as slowly changing dimensions and semi-additivity. It also covers the usage of
Multidimensional Expressions (MDX), both to query the model and to embed business logic into the
model in the form of calculated measures, named sets, Key Performance Indicators (KPIs), and additions
to the MDX script.
The exam’s coverage of tabular models requires you to understand how to import data into a model or
use DirectQuery mode, and how the implementation of DirectQuery mode impacts the model development
process. You must also know how to enhance the model by defining relationships between tables, adding
measures and calculated columns by using Data Analysis Expressions (DAX), configuring partitions, and
setting properties of model objects. Furthermore, you must know how to create KPIs from calculated
measures and how to use DAX to write analytical queries.
Additionally, the exam focuses on considerations related to deploying and securing models and keeping
them up-to-date by choosing the appropriate processing options for specific scenarios. It also requires
you to understand how to use various tools to monitor and troubleshoot performance of BI semantic
models and identify the necessary steps to take to resolve performance issues. Other areas of focus
include the deployment and configuration of Analysis Services instances for memory management and