MSBI SSAS Course Content
Getting started with SSAS
Understanding the concept of multidimensional analysis, understanding SSAS Architecture and benefits, learn what is Cube, working with Tables and OLAP databases, understanding the concept of Data Sources, working with Dimension Wizard, understanding Dimension Structure, Attribute Relationships, flexible and rigid relationship.
Structures and Processes
Learning about Process Dimension, the Process database, creation of Cube, understanding Cube Structure, Cube browsing, defining the various categories, Product Key and Customer Key, Column Naming, processing and deploying a Cube, Report creation with a Cube.Hands-on Exercise – Create a Cube and name various columns Deploy a cube after applying keys and other rules Create reports with a cube
Type of Database Relationship
Understanding Data Dimensions and its importance, the various relationships, regular, referenced, many to many, fact, working on Data Partitions, and Data Aggregations.
Learning about SSAS Cube, the various types of Cubes, the scope of Cube and comparison with Data Warehouse.
Cube: Operations & Limitations
The various operations on Cube, the limitations of OLAP Cubes, the architecture of in-memory analytics and its advantages.
Cube and In-memory Analytics
Deploying cube with existing data warehouse capabilities to get self-service business intelligence, understanding how in-memory analytics works.Hands-on Exercise – Deploy cube to get self-service business intelligence
Data Source View
Logical model of the schema used by the Cube, components of Cube, understanding Named Queries and Relationships.
An overview of the Dimensions concept, describing the Attributes and Attributes Hierarchies, understanding Key/Value Pairs, Metadata Reload, logical keys and role-based dimensions.Hands-on Exercise – Create role based dimensions, Use Attributes Hierarchies
Measures & Features of Cube
Understanding the Measure of Cube, analyzing the Measure, exploring the relationship between Measure and Measure Group, Cube features and Dimension usage.
Measures and Features of Cube Cont.
Working with Cube Measures, deploying analytics, understanding the Key Performance Indicators, deploying actions and drill-through actions on data, working on data partitions, aggregations, translations and perspectives.Hands-on Exercise – Work with Cube Measures, Deploy analytics, Deploy actions and drill-through actions on data, Make data partitions
Working with MDX
Understanding Multidimensional Expressions language, working with MDX queries for data retrieval, working with Clause, Set, Tuple, Filter condition in MDX.Hands-on Exercise – Apply Clause, Set and filter condition in MDX query to retrieve data
Functions of MDX
Learning about MDX hierarchies, the functions used in MDX, Ancestor, Ascendant and Descendant function, performing data orderingHands-on Exercise – Create MDX hierarchies, Perform data ordering in ascending order, in descending order
Data Analysis Expressions (DAX), Using the EVALUATE and CALCULATE functions, filter DAX queries, create calculated measures, perform data analysis by using DAXHands-on Exercise – Use the EVALUATE and CALCULATE functions, filter DAX queries, create calculated measures, perform data analysis by using DAX
BI Semantic Model
Designing and publishing a tabular data model, Designing measures relationships, hierarchies, partitions, perspectives, and calculated columnsHands-on Exercise – Design and publish a tabular data model, Design measures relationships, hierarchies, partitions, perspectives, and calculated columns
Plan and deploy SSAS
Configuring and maintaining SQL Server Analysis Services (SSAS), Non-Union Memory Architecture (NUMA), Monitoring and optimizing performanceHands-on Exercise – Configure and maintain SQL Server Analysis Services (SSAS), Monitor and optimize performance
Analyzing Big Data with Microsoft R
Reading data with R Server from SAS, txt, or excel formats, converting data to XDF format; Summarizing data, rxCrossTabs versus rxCube, extracting quantiles by using rxQuantile; Visualizing data (rxSummary and rxCube, rxHistogram and rxLinePlot) Processing data with rxDataStep Performing transforms using functions transformVars and transformEnvir Processing text using RML packages Building predictive models with ScaleR Performing in-database analytics by using SQL ServerHands-on Exercise – Read data with R Server from SAS, txt or excel formats, convert data to XDF format; Summarize data, Extract quantiles by using rxQuantile; Visualize data (rxSummary, rxCube, rxHistogram and rxLinePlot) Perform transforms using functions transformVars and transformEnvir Build predictive models with ScaleR Perform in-database analytics by using SQL Server
Project – SSAS Cube Using BI Data Tools 2012Data – Adventure Works DW2012Topics–In this project you will be working exclusively on a business organization’s production volumes while comparing it to the sales performance in order to derive valuable insights. You will exclusively deploy the Adventure Works DW2012 which is a relational data warehouse that runs on a database engine instance. This relational data warehouse will provide the original data for the SQL Server Analysis Services (SSAS).You shall build SSAS Cubes using the Business Intelligence tools. Upon completion of the project you will be well-versed to work in a real world business scenario to analyze various parameters and instances in order to derive business insights.