Microsoft SQL Server 2019 Analysis Services (SSAS)

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Course Description

Analysis Services is a combination of two analytical engines (VertiPaq for multidimensional cubes and Data Mining and xVelocity for Tabular Data Models) used in decision support and business analytics. It provides enterprise-grade semantic data model capabilities for business intelligence (BI), data analysis, and reporting applications such as Power BI, Excel, Reporting Services, and other data visualization tools.

This course provides a full introduction to the use of both of these engines in an enterprise environment.  You will learn about creating cubes and their constituent components, the use of MDX to query the cubes, as well as how to customize a cube with KPI, actions, perspectives, and language translations.  You will also learn about the differences and similarities between cubes and tabular data models, how to create a tabular data model, and the use of DAX to query the model.

The third major component of the course is a form of Machine Learning called Data Mining.  Data Mining is the analysis of large data set to reveal hidden patterns and trends. This course will teach you how to create a Data Mining solution, how to compare and validate different data mining options (models) for a given data set, and how to use your chosen model in a consumer-friendly client.

Key Learning Topics In This Course
  • You will learn about creating cubes and their constituent components
  • The use of MDX to query the cubes
  • How to customize a cube with KPI, actions, perspectives, and language translations.
  • Differences and similarities between cubes and tabular data models,
  • How to create a tabular data model
  • The use of DAX to query the model.

Course Video Content: 8 Hours 56 Minutes
Test Questions: 75

Course Content

Module 1 - Introduction to Business Intelligence and Data Modeling
1.1 Course Introduction
1.2 Module 1 Introduction
1.3 Introduction to Business Intelligence
1.4 The Microsoft Business Intelligence Platform
1.5 Exploring a Data Warehouse
1.6 Exploring a Data Model

Module 2 - Multidimensional Databases
2.1 Module 2 Introduction
2.2 Introduction to Multidimensional Analysis
2.3 Overview of Cube Security
2.4 Creating and Configuring a Cube
2.5 Data Sources
2.6 Data Source Views
2.7 Adding a Dimension to a Cube

Module 3 - Cubes and Dimensions
3.1 Module 3 Introduction
3.2 Dimensions
3.3 Attribute Hierarchies and Relationships
3.4 Sorting and Grouping Attributes
3.5 Slowly Changing Dimensions

Module 4 - Measures and Measure Groups
4.1 Module 4 Introduction
4.2 Measures
4.3 Measure Groups and Relationships
4.4 Measure Group Storage

Module 5 - Introduction to MDX
5.1 Module 5 Introduction
5.2 MDX Fundamentals
5.3 Adding Calculations to a Cube
5.4 Querying a cube using MDX

Module 6 - Customizing Cube Functionality
6.1 Module 6 Introduction
6.2 Key Performance Indicators
6.3 Actions
6.4 Perspectives
6.5 Translations

Module 7 - Tabular Data Models
7.1 Module 7 Introduction
7.2 Introduction to Tabular Data Models
7.3 Creating a Tabular Data Model
7.4 Configure Relationships and Attributes
7.5 Configuring Data Model for an Enterprise BI Solution

Module 8 - Data Analysis Expressions (DAX)
8.1 Module 8 Introduction
8.2 DAX Fundamentals
8.3 Calculated Columns
8.4 Relationships
8.5 Measures
8.6 Time Intelligence
8.7 KPI
8.8 Parent - Child Hierarchies

Module 9 - Data Mining
9.1 Module 9 Introduction
9.2 Overview of Data Mining
9.3 Custom Data Mining Solutions
9.4 Validating a Data Mining Model
9.5 Consuming a Data Mining Model
9.6 Course Wrap Up


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