IMPLEMENTING A DATA WAREHOUSE WITH MICROSOFT SQL SERVER 2012 

 

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 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 include:

• Implementing a data warehouse. 

• Developing SSIS packages for data extraction, transformation, and loading. 

• Enforcing data integrity by using Master Data Services. 

• Cleansing data by using Data Quality Services.

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Duration

5 days

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Program

Module 1: Introduction to Data Warehousing

• Overview of Data Warehousing

• Considerations for a Data Warehouse Solution

 

Module 2: Data Warehouse Hardware

• Considerations for Building a Data Warehouse

• Data Warehouse Reference Architectures and Appliances

 

Module 3: Designing and Implementing a Data Warehouse

• Logical Design for a Data Warehouse

• Physical Design for a Data Warehouse

 

Module 4: Creating an ETL Solution with SSIS

• Introduction to ETL with SSIS

• Exploring Source Data

• Implementing Data Flow

 

Module 5: Implementing Control Flow in an SSIS Package

• Introduction to Control Flow

• Creating Dynamic Packages

• Using Containers

• Managing Consistency

 

Module 6: Debugging and Troubleshooting SSIS Packages

• Debugging an SSIS Package

• Logging SSIS Package Events

• Handling Errors in an SSIS Package

 

Module 7: Implementing an Incremental ETL Process

• Introduction to Incremental ETL

• Extracting Modified Data

• Loading Modified Data

 

Module 8: Incorporating Data from the Cloud into a Data Warehouse

• Overview of Cloud Data Sources

• SQL Server Database

• The Windows Azure Marketplace

 

Module 9: Enforcing Data Quality

• Introduction to Data Quality

• Using Data Quality Services to Cleanse Data

• Using Data Quality Services to Match Data

 

Module 10: Using Master Data Services

• Introduction to Master Data Services

• Implementing a Master Data Services Model

• Using the Master Data Services Add-in for Excel

 

Module 11: Extending SQL Server Integration Services

• Using Custom Components in SSIS

• Using Scripts in SSIS

 

Module 12: Deploying and Configuring SSIS Packages

• Overview of SSIS Deployment

• Deploying SSIS Projects

• Planning SSIS Package Execution

 

Module 13: Consuming Data in a Data Warehouse

• Introduction to Business Intelligence

• Introduction to Reporting

• Introduction to Data Analysis

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Objectives

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 Control Flow in an SSIS Package.

• Debug and Troubleshoot SSIS packages. 

• Implement an ETL solution that supports incremental data extraction.

• Implement an ETL solution that supports incremental data loading.

• Implement data cleansing by using Microsoft Data Quality Services.

• Implement Master Data Services to enforce data integrity. 

• Extend SSIS with custom scripts and components. 

• Deploy and Configure SSIS packages.

• Describe how BI solutions can consume data from the data warehouse.

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Certifications

At the end of this course every learner will receive a certificate of attendance.

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