Implementing a SQL Data Warehouse (20767C)

This five-day instructor-led course provides students with the knowledge and skills to provision a Microsoft SQL Server database. The course covers SQL Server provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.

Target Audience
The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role.  They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. 

Pre-Requisites
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.
  • Some experience with database design.

Objectives
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
 
Mostrar detalhes
Course Outline

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
  • Data warehouse design overview
  • 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