MCSA SQL 2016 Business Intelligence Development

Module 1: Introduction to Data Warehousing

This module describes data warehouse concepts and architecture consideration.Lessons

• Overview of Data Warehousing
• Considerations for a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure

This module describes the main hardware considerations for building a data warehouse.Lessons

• Considerations for data warehouse infrastructure.
• Planning data warehouse hardware.

Module 3: Designing and Implementing a Data Warehouse

This module describes how you go about designing and implementing a schema for a data warehouse.Lessons

• Designing dimension tables
• Designing fact tables
• Physical Design for a Data Warehouse

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.Lessons

• Introduction to Columnstore Indexes
• Creating Columnstore Indexes
• Working with Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse

This module describes Azure SQL Data Warehouses and how to implement them.Lessons

• Advantages of Azure SQL Data Warehouse
• Implementing an Azure SQL Data Warehouse
• Developing an Azure SQL Data Warehouse
• Migrating to an Azure SQ Data Warehouse
• Copying data with the Azure data factory

Module 6: Creating an ETL Solution

At the end of this module you will be able to implement data flow in a SSIS package.Lessons

• Introduction to ETL with SSIS
• Exploring Source Data
• Implementing Data Flow

Module 7: Implementing Control Flow in an SSIS Package

This module describes implementing control flow in an SSIS package.Lessons

• Introduction to Control Flow
• Creating Dynamic Packages
• Using Containers
• Managing consistency.

Module 8: Debugging and Troubleshooting SSIS Packages

This module describes how to debug and troubleshoot SSIS packages.Lessons

• Debugging an SSIS Package
• Logging SSIS Package Events
• Handling Errors in an SSIS Package

Module 9: Implementing a Data Extraction Solution

This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.Lessons

• Introduction to Incremental ETL
• Extracting Modified Data
• Loading modified data
• Temporal Tables

Module 10: Enforcing Data Quality

This module describes how to implement data cleansing by using Microsoft Data Quality services.Lessons

• Introduction to Data Quality
• Using Data Quality Services to Cleanse Data
• Using Data Quality Services to Match Data

Module 11: Using Master Data Services

This module describes how to implement master data services to enforce data integrity at source.Lessons

• Introduction to Master Data Services
• Implementing a Master Data Services Model
• Hierarchies and collections
• Creating a Master Data Hub

Module 12: Extending SQL Server Integration Services (SSIS)This module describes how to extend SSIS with custom scripts and components.Lessons

• Using scripting in SSIS
• Using custom components in SSIS

Module 13: Deploying and Configuring SSIS Packages

This module describes how to deploy and configure SSIS packages.Lessons

• Overview of SSIS Deployment
• Deploying SSIS Projects
• Planning SSIS Package Execution

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.Lessons

• Introduction to Business Intelligence
• An Introduction to Data Analysis
• Introduction to reporting
• Analyzing Data with Azure SQL Data Warehouse

Module 1: Introduction to Business Intelligence and Data Modeling

This module introduces key BI concepts and the Microsoft BI product suite.Lessons

• Introduction to Business Intelligence
• The Microsoft business intelligence platform

Module 2: Creating Multidimensional Databases

This module describes how to create multidimensional databases using SQL Server Analysis Services.Lessons

• Introduction to Multidimensional Analysis
• Creating Data Sources and Data Source Views
• Creating a Cube
• Overview of Cube Security
• Configure SSAS
• Monitoring SSAS

Module 3: Working with Cubes and Dimensions

This module describes how to implement dimensions in a cube.Lessons

• Configuring Dimensions
• Defining Attribute Hierarchies
• Sorting and Grouping Attributes
• Slowly Changing Dimensions

Module 4: Working with Measures and Measure Groups

This module describes how to implement measures and measure groups in a cube.Lessons

• Working with Measures
• Working with Measure Groups

Module 5: Introduction to MDX

This module describes the MDX syntax and how to use MDX.Lessons

• MDX fundamentals
• Adding Calculations to a Cube
• Using MDX to Query a Cube

Module 6: Customizing Cube Functionality

This module describes how to customize a cube.Lessons

• Introduction to Business Intelligence
• The Implementing Key Performance Indicators
• Implementing Actions
• Implementing Perspectives
• Implementing Translations

Module 7: Implementing a Tabular Data Model by Using Analysis Services

This module describes how to implement a tabular data model in Power Pivot.Lessons

• Introduction to Tabular Data Models
• Creating a Tabular Data Model
• Using an Analysis Services Tabular Data Model in an Enterprise BI Solution

Module 8: Introduction to Data Analysis Expression (DAX)

This module describes how to use DAX to create measures and calculated columns in a tabular data model.Lessons

• DAX Fundamentals
• Using DAX to Create Calculated Columns and Measures in a Tabular Data Model

Module 9: Performing Predictive Analysis with Data Mining

This module describes how to use data mining for predictive analysis.Lessons

• Overview of Data Mining
• Creating a Custom Data Mining Solution
• Validating a Data Mining Model
• Connecting to and Consuming a Data-Mining Model
• Using the Data Mining add-in for Excel