MOC On-Demand Packaged Set 20767B: Implementing a SQL Data Warehouse (Q4P-00168)

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.

Microsoft On Demand
Microsoft Official Courses On-Demand (MOC On-Demand) blend video, text, hands-on labs and knowledge checks to help you build your Microsoft technology skills?on your own schedule, at your own pace and in your own place. No need to spend time and money travelling to a classroom location or adhering to classroom hours?with a computer and an Internet connection, your Microsoft Official Courses On-Demand come to you, any time.
  • Microsoft On Demand covers the same objectives as the classroom course by the same name
  • After you activate your course, you have 3 months to complete it. You can work on your course at any time throughout the 3-month period after you activate the course.
Microsoft On Demand Packaged Set
Including
  • Microsoft On Demand Course OD20767B (includes Microsoft Labs Online)
  • Digital courseware Course 20767B

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
 
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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