Implementing a SQL Data Warehouse Training

This course requires that you meet the following prerequisites:

• Basic knowledge of the Microsoft Windows operating system and its core functionality.
• Working knowledge of relational databases.
• Some experience with database design

After completing this course, students will be able to:

• Describe the key elements of a data warehousing solution
• Describe the main hardware considerations for building a data warehouse
• Implement a logical design for a data warehouse
• Implement a physical design for a data warehouse
• Create columnstore indexes
• Implementing an Azure SQL Data Warehouse
• Describe the key features of SSIS
• Implement a data flow by using SSIS
• Implement control flow by using tasks and precedence constraints
• Create dynamic packages that include variables and parameters
• Debug SSIS packages
• Describe the considerations for implement an ETL solution
• Implement Data Quality Services
• Implement a Master Data Services model
• Describe how you can use custom components to extend SSIS
• Deploy SSIS projects
• Describe BI and common BI scenarios

Module 1: Introduction to Data Warehousing

Describe data warehouse concepts and architecture considerations.

Lessons

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

Lab : Exploring 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 Building a Data Warehouse
• Data Warehouse Reference Architectures and Appliances

Lab : Planning Data Warehouse Infrastructure

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

• Logical Design for a Data Warehouse
• Physical Design for a Data Warehouse

Lab : Implementing a Data Warehouse Schema

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.

Lessons

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

Lab : Using 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

Lab : Implementing an Azure SQL Data Warehouse

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

Lab : Implementing Data Flow in an SSIS Package

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

Lab : Implementing Control Flow in an SSIS PackageLab : Using Transactions and Checkpoints

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

Lab : Debugging and Troubleshooting an SSIS Package

Module 9: Implementing an Incremental ETL Process

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
• Temporal Tables

Lab : Extracting Modified DataLab : Loading Incremental Changes

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

Lab : Cleansing DataLab : De-duplicating Data

Module 11: Using Master Data Services

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

Lessons

• Master Data Services Concepts
• Implementing a Master Data Services Model
• Managing Master Data
• Creating a Master Data Hub

Lab : Implementing Master Data Services

Module 12: Extending SQL Server Integration Services (SSIS)

This module describes how to extend SSIS with custom scripts and components.

Lessons

• Using Custom Components in SSIS
• Using Scripting in SSIS

Lab : Using Scripts and Custom Components

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

Lab : Deploying and Configuring SSIS Packages

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.

Lessons

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

Lab : Using Business Intelligence Tools