Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500.
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.
SSAS Cube
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.
Dimensions
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 ordering
Hands-on Exercise – Create MDX hierarchies, Perform data ordering in ascending order, in descending order
DAX language
Data Analysis Expressions (DAX), Using the EVALUATE and CALCULATE functions, filter DAX queries, create calculated measures, perform data analysis by using DAX
Hands-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 columns
Hands-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 performance, SSAS Tabular model with vNext, Excel portability, importing model from Power BI Desktop, importing a Power Pivot model, bidirectional cross-filtering relationship in MSBI.
Hands-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 Server
Hands-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
SSAS Project
Project 2 – Cube Creation – SSAS Cube 2012
Industry : Sales
Problem Statement : How to create the SSAS Cubes for faster reporting
Topics : In this project you will be work on large volume of data and use it for creating reports and dashboards for sales performance in order to derive valuable insights. You will deploy the sales database in sql server and build SSAS Cubes. 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.
Highlights :