Implementing A Data Warehouse With Microsoft SQL Server 2012

Course details

This instructor-led 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.

After completing this course, students will be able to:

• Describe data warehouse concepts and architecture considerations.
• Select an appropriate hardware platform for a data warehouse.
• Design and implement a data warehouse.
• Implement Data Flow in an SSIS Package.
• Implement Data Flow in an SSIS Package.
• Debug and Troubleshoot SSIS packages.
• Implement an SSIS solution that supports incremental DW loads and changing data.
• Integrate cloud data into a data warehouse ecosystem infrastructure.
• Implement data cleansing by using Microsoft Data Quality Services.
• Implement Master Data Services to enforce data integrity at source.
• Extend SSIS with custom scripts and components.
• Deploy and Configure SSIS packages.
• Describe how information workers can consume data from the data warehouse.

Module 1: Introduction to Data Warehousing
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.

Module 2: Data Warehouse Hardware Considerations
This module describes the considerations for selecting the appropriate hardware platform for your data warehouse solution.

Module 3: Designing and Implementing a Data Warehouse
This module describes how to implement the logical and physical architecture of a data warehouse based on industry proven design principles.
Lessons

Module 4: Design and implement a schema for a data warehouse
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.

Module 5: Implementing Control 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.

Module 6: Debugging and Troubleshooting SSIS Packages
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.

Module 7: Implementing an Incremental ETL Process
This module describes the techniques you can use to implement an incremental data warehouse refresh process. Lessons

Module 8: Incorporating Data from the Cloud in a Data Warehouse
This modules describes how integrate cloud data into a data warehouse ecosystem.

Module 9: Enforcing Data Quality
This modules describes how to use Data Quality Services (DQS) for cleansing and deduplicating your data.

Module 10: Using Master Data Services
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.

Module 11: Extending SSIS
This module describes how to extend SSIS by using custom scripts and components.

Module 12: Deploying and Configuring SSIS Packages
This modules describes how to deploy and configure SSIS packages.

Module 13: Consuming Data in a Data Warehouse
This module describes how information workers can consume data from the data warehouse.