This module provides an introduction to the key components of a data warehousing solution and the high-level considerations you must take into account when embarking on a data warehousing project.
Lessons
Lab : Exploring a Data Warehousing Solution
This module describes the considerations for selecting the appropriate hardware platform for your data warehouse solution.
Lessons
This module describes how to implement the logical and physical architecture of a data warehouse based on industry proven design principles.
Lessons
Lab : Implementing a Data Warehouse Schema
This module discusses considerations for implementing an ETL process, and then focuses on SQL Server Integration Services (SSIS) as a platform for building ETL solutions.
Lessons
Lab : Implementing Data Flow in an SSIS Package
This module describes how to implement control flow which allows users to design robust ETL processes for a data warehousing solution that coordinate data flow operations with other automated tasks.
Lessons
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints
This module describes how you can debug packages to find the cause of errors that occur during execution. It then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.
Lessons
Lab : Debugging and Troubleshooting an SSIS Package
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
Lessons
Lab : Extracting Modified Data
Lab : Loading Incremental Changes
This modules describes how integrate cloud data into a data warehouse ecosystem.
Lessons
Lab : Using Cloud data in a Data Warehouse Solution
This modules describes how to use Data Quality Services (DQS) for cleansing and deduplicating your data.
Lessons
Lab : Cleansing Data
Lab : De-Duplicating Data
This module introduces Master Data Services and explains the benefits of using it in a business intelligence (BI) context. It also describes the key configuration options, explains how to import and export data and apply rules that help to preserve data integrity, and introduces the new Master Data Services Add-in for Excel.
Lessons
Lab : Implementing Master Data Services
Module 11: Extending SSIS
This module describes how to extend SSIS by using custom scripts and components.
Lessons
Lab : Using Scripts and Custom Components
This modules describes how to deploy and configure SSIS packages.
Lessons
Lab : Deploying and Configuring SSIS Packages
This module describes how information workers can consume data from the data warehouse.
Lessons
Lab : Using a Data Warehouse
This course describes how to implement a BI platform to support information worker analytics. Students will learn how to create a data warehouse with SQL Server 2012, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services. This course helps people prepare for the exam 70-463.
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. Primary responsibilities will include: