SSAS Training

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

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.

The various operations on Cube, the limitations of OLAP Cubes, the architecture of in-memory analytics and its advantages.

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

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

Understanding the Measure of Cube, analyzing the Measure, exploring the relationship between Measure and Measure Group, Cube features and Dimension usage.

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

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

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

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

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

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.