This course has been superseded by course 20463.
Data warehousing is a solution organizations use to centralize business data for reporting and analysis. This five-day instructor-led course focuses on teaching individuals 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 exam 70-463.
After completing this course, students will be able to:
This course is intended for database professionals who need to fulfill 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 include:
We can also deliver and customise this training course for larger groups saving your organisation time, money and resources. For more information, please make a note when you enquire.
Before attending this course, student should have:
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 starting a data warehousing project.
Lab : Exploring a Data Warehousing Solution
Module 2: Data Warehouse Hardware
This module describes the characteristics of typical data warehouse workloads, and explains how you can use reference architectures and data warehouse appliances to ensure you build the system that is right for your organization.
Module 3: Designing and Implementing a Data Warehouse
In this module, you will learn how to implement the logical and physical architecture of a data warehouse based on industry-proven design principles.
Lab : Implementing a Data Warehouse Schema
Module 4: Creating an ETL Solution with SSIS
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.
Lab : Implementing Data Flow in a SSIS Package
Module 5: Implementing Control Flow in an SSIS Package
Control flow in SQL Server Integration Services packages enables you to implement complex ETL solutions that combine multiple tasks and workflow logic. This module covers how to implement control flow, and design robust ETL processes for a data warehousing solution that coordinate data flow operations with other automated tasks.
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 SQL Server Integration Services (SSIS) packages to find the cause of errors that occur during execution. Then module then covers the logging functionality built into SSIS 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 an Incremental ETL Process
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
Lab : Extracting Modified Data
Lab : Loading Incremental Changes
Module 8: Incorporating Data from the Cloud into a Data Warehouse
In this module, you will learn about how you can use cloud computing in your data warehouse infrastructure and learn about the tools and services available from the Microsoft Azure Marketplace.
Lab : Using Cloud Data in a Data Warehouse Solution
Module 9: Enforcing Data Quality
Ensuring the high quality of data is essential if the results of data analysis are to be trusted. This module explains how to use the SQL Server 2012 Data Quality Services (DQS) to provide a computer assisted process for cleansing data values and identifying and removing duplicate data entities.
Lab : Cleansing Data
Lab : Deduplicating Data
Module 10: Using Master Data Services
This module introduces Master Data Services and explains the benefits of using it in a data warehousing context. The module also describes the key configuration options for Master Data Services, and explains how to import and export data. Finally, the module explains how to apply rules that help to preserve data integrity, and introduces the new Master Data Services Add-in for Excel.
Lab : Implementing Master Data Services
Module 11: Extending SQL Server Integration Services
This module describes the techniques you can use to extend SQL Server Integration Services (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 Components and Scripts
Module 12: Deploying and Configuring SSIS Packages
SQL Server Integration Services provides tools that make it easy to deploy packages to another computer. The deployment tools also manage any dependencies, such as configurations and files that the package needs. In this module, you will learn how to use these tools to install packages and their dependencies on a target computer.
Lab : Deploying and Configuring SSIS Packages
Module 13: Consuming Data in a Data Warehouse
This module introduces Business Intelligence (BI), describes the components of SQL Server that you can use to create a BI solution, and the client tools that users can use to create reports and analyze data.
Lab : Using Business Intelligence Tools
|Teaching mode:||Classroom - Instructor Led|
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