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This 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 2014, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.
Note: This course is designed for customers who are interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features in SQL Server 2014, but also the important capabilities across the SQL Server data platform.
This course is intended for database professionals who need to create and support a data warehousing solution. Primary responsibilities include:
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 you embark on a data warehousing project.
This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.
This module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server Integration Services (SSIS) as a platform for building ETL solutions.
This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
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.
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
This module describes the techniques you can use to implement data warehouse load process.
This module introduces Microsoft SQL Server Data Quality Services (DQS), and describes how you can use it to cleanse and deduplicate data.
Master Data Services provides a way for organizations to standardize data and improve the quality, consistency, and reliability of the data that guides key business decisions. This module introduces Master Data Services and explains the benefits of using it.
This module describes the techniques you can use to extend SSIS. The module is not designed to be a comprehensive guide to developing custom SSIS solutions, but to provide an awareness of the fundamental steps required to use custom components and scripts in an ETL process that is based on SSIS.
In this module, students will learn how to deploy packages and their dependencies to a server, and how to manage and monitor the execution of deployed packages.
This module introduces business intelligence (BI) solutions and describes how you can use a data warehouse as the basis for enterprise and self-service BI.
Lab: Exploring a Data Warehousing Solution
Lab: Planning Data Warehouse Infrastructure
Lab: Implementing a Data Warehouse
Lab: Implementing Data Flow in an SSIS Package
Lab: Implementing Control Flow in an SSIS Package
Lab: Using Transactions and Checkpoints
Lab: Debugging and Troubleshooting an SSIS Package
Lab: Extracting Modified Data
Lab: Loading a Data Warehouse
Lab: Cleansing Data
Lab: Implementing Master Data Services
Lab: Using Custom Scripts
Lab: Deploying and Configuring SSIS Packages
Lab: Using a Data Warehouse
After completing this course, students will be able to:
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Last updated: 2018-05-26
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