Public Class
Live Virtual Class
Private Class
This 5-day instructor led course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
At least 2 years’ experience of working with relational databases, including:
Designing a normalized database.
Creating tables and relationships.
Querying with Transact-SQL.
Some exposure to basic programming constructs (such as looping and branching).
An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
Audience Profile
The primary audience for this course is individuals who administer and maintain SQL Server databases. These individuals perform database administration and maintenance as their primary area of responsibility, or work in environments where databases play a key role in their primary job.
The secondary audiences for this course are individuals who develop applications that deliver content from SQL Server databases.
After completing this course, students will be able to:
Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.
Lessons
Lab: Exploring a Data Warehouse Solution
After completing this module, you will be able to:
Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.
Lessons
Lab : Planning Data Warehouse Infrastructure
After completing this module, you will be able to:
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
Lab : Implementing a Data Warehouse Schema
After completing this module, you will be able to:
Module 4 : Column store Indexes
This module introduces Column store Indexes.
Lessons
Lab : Using Columnstore Indexes
After completing this module, you will be able to:
Module 5 : Implementing and Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.
Lessons
Lab : Implementing an Azure SQL Data Warehouse
After completing this module, you will be able to:
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
Lab : Implementing Data Flow in an SSIS Package
After completing this module, you will be able to:
Module 7 : Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.
Lessons
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints
After completing this module, you will be able to:
Module 8: Debugging and Troubleshooting SSIS Package
This module describes how to debug and troubleshoot SSIS packages.
Lessons
Lab : Debugging and Troubleshooting an SSIS Package
After completing this module, you will be able to:
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
Lab : Extracting Modified DataLab : Loading Incremental Changes
After completing this module, you will be able to:
Module 10 : Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.
Lessons
Lab : Cleansing DataLab : De-duplicating Data
After completing this module, you will be able to:
Module 11 : Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.
Lessons
Lab : Implementing Master Data Services
After completing this module, you will be able to:
Module 12 : Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.
Lessons
Lab : Using Scripts and Custom Components
After completing this module, you will be able to:
Module 13 : Deploying and Configuring SSIS Package
This module describes how to deploy and configure SSIS packages.
Lessons
Lab : Deploying and Configuring SSIS Packages
After completing this module, you will be able to:
Module 14 : Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.
Lessons
Lab : Using Business Intelligence Tools
After completing this module, you will be able to:
