This course describes how to implement a data warehouse platform to support a BI solution. Delegates 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.
This course is intended for database professionals who need to create and support a data warehousing solution. Primary responsibilities include:
At the end of this course you will be able to:
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 you embark on a data warehousing project.
Lab : Exploring a Data Warehousing Solution
Module 2: Planning Data Warehouse Infrastructure
This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
Lab : Planning Data Warehouse Infrastructure
Planning Data Warehouse Hardware
Module 3: Designing and Implementing a Data Warehouse
This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.
Lab : Implementing a Data Warehouse
Module 4: Creating an ETL Solution with SSIS
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.
Lab : Implementing Data Flow in an SSIS Package
Module 5: Implementing Control Flow in an SSIS Package
This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints
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.
Lab : Debugging and Troubleshooting an SSIS Package
Module 7: Implementing a Data Extraction Solution
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
Lab : Extracting Modified Data
Module 8: Loading Data into a Data Warehouse
This module describes the techniques you can use to implement data warehouse load process.
Lab : Loading a Data Warehouse
Module 9: Enforcing Data Quality
This module introduces Microsoft SQL Server Data Quality Services (DQS), and describes how you can use it to cleanse and deduplicate data.
Lab : Cleansing Data
Module 10: Master Data Services
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.
Lab : Implementing Master Data Services
Module 11: Extending SQL Server Integration Services
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.
Lab : Using Custom Scripts
Using a Script Task
Module 12: Deploying and Configuring SSIS Packages
In this module, delegates will learn how to deploy packages and their dependencies to a server, and how to manage and monitor the execution of deployed packages.
Lab : Deploying and Configuring SSIS Packages
Module 13: Consuming Data in a Data Warehouse
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 : Using a Data Warehouse
At least 2 years’ experience of working with relational databases, including: