SSAS Training

Topics: 

• Importance of data dimensions
• Various relationships between data 
• Referenced,regular, many to many relationships 
• working on data partitions
• Data aggregations

Learning Outcome: After completion of this section you will gain an overall knowledge of dashboards and various relationships between data.

Topics: 

• Understanding SSAS cube 
• Different cubes in SSAS
• Scope of cube
• Comparing cube with data warehouse 

Learning Outcome: Upon the completion of this section you will gain a complete overview of Cube.

Topics:

• Various operations on cube 
• architecture of in-memory analytics
• limitations of OLAP cubes
• Advantages of in-memory analytics 

Learning Outcome: After completion of this session you will gain an overall knowledge of functionality and limitations associated with Cube concept. 

Topics: 

• Implementing Cube with existing warehouse 
• Understanding in-memory analytics functioning process

Learning Outcome: You will gain overall knowledge to deploy the cube to get self-service business intelligence.

Topics: 

• Building a logical model of schema 
• Understanding named queries & relationships 
• Components of Cube 

Learning Outcome: Upon the completion of this section you will gain expertise in building logical models, using components of Cube, queries and relationships etc. 

Topics:

• Overview of dimensions concept 
• understanding Key/Value pairs
• Introduction to Attributes and attributes hierarchies 
• Role-based dimensions and logical keys 
• Metadata reload

Learning Outcome: Upon the completion of this section you will be able to use attributes hierarchies and create role-based dimensions. 

• Overview of measure of a cube
• Relationship between measure and measure group
• Analyzing the measure
• Cube features and dimension 

Learning Outcome: Upon the completion of this section you will gain an overall knowledge of Cube features and dimensions and master various features of Cube. 

Topics: 

• Introduction to cube measures
• Overview of Key performance indicators
• Deploying analytics and actions
• working on data partitions
• Drill-through actions on data
• Aggregations
• Working on data partitions
• translations and perspectives

Learning outcome: Upon the completion of this section, you will gain hands-on expertise in Deploy analytics, Cube Measures, Deploy actions, Make data partitions and drill-through actions on data. 

Topics: 

• Introduction to the multidimensional expression language
• Working with clause, filter, tuple set condition in MDX. 
• working with MDX queries to retrieve data 

Learning Outcome: Upon the completion of this section you will gain practical knowledge in using various conditions in MDX to retrieve data.

Topics:

• Introduction to MDX hierarchies 
• Functions used in MDX
• Ascendant, Ancestor, and Descendant function
• Data ordering 

Learning Outcome: After completion of this chapter you will gain hands-on expertise in various functions executed by MDX.

• Create MDX hierarchies
• data ordering in ascending order
• data order in descending order 

Topics: 

• Data Analysis Expressions (DAX)
• CALCULATE and EVALUATE functions 
• Perform data analysis
• Create calculated measures
• Filter DAX queries

Learning Outcome: Upon the completion of this section, you will be able to use filter DAX queries, EVALUATE and CALCULATE functions, perform data analysis, create calculated measures by using DAX.

Topics: 

• Creating and publishing a tabular model 
• Hierarchies, perspectives, partitions, and calculated columns
• Designing measures relationships,  

Learning outcome: Upon the completion of this section you will gain hands-on expertise in all the above-mentioned concepts: 

Topics: 

• Configuring and maintaining SSAS
• Monitoring and optimizing performance 
• Non-Union memory architecture (NUMA)
• SSAS Tabular model with vNext,
• Model importing from Power BI desktop 
• Excel portability
• Bidirectional cross-filtering 
• Importing a Power pivot model 

Learning Outcome: In this section, you will gain hands-on experience in configuring and maintaining SSAS. 

Topics:

• R server to read data from txt, SAS or excel formats 
• Summarizing data
• converting data to XDF format
• Quantities extraction using rxQuantiler
• xCube versus rxCrossTabs
• Data visualization 
• Performing transforms using transformVars
• Processing data with rxDataStep
• Using ScaleR to build predictive models 
• Text processing with RML packages 
• Executing in-database analytics with SQL server 

Learning Outcome: Upon the completion of this section you will gain overall knowledge and execution of all the above concepts in real-time. 

HKR Trainings provides SSAS Interview Questions, SSAS Tutorial and sample Resumes for clear understanding.

We at HKR trainings provide the learners with practice Mock Interview Sessions and excellent Job Support at the end of the course.