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.

Module 1: Introduction to Data Warehousing

• Overview of Data Warehousing
• Considerations for a Data Warehouse Solution
• Lab : Exploring a Data Warehousing Solution

Module 2: Data Warehouse Hardware Considerations

• Considerations for building a Data Warehouse
• Data Warehouse Reference Architectures and Appliances
• Lab : Planning Data Warehouse Infrastructure

Module 3: Designing and Implementing a Data Warehouse

• Logical Design for a Data Warehouse
• Physical design for a data warehouse
• Lab : Implementing a Data Warehouse Schema

Module 4: Creating an ETL Solution with SSIS

• Introduction to ETL with SSIS
• Exploring Data Sources
• Implementing Data Flow
• Lab : Implementing Data Flow in an SSIS Package

Module 5: Implementing Control Flow in an SSIS Package

• Introduction to Control Flow
• Creating Dynamic Packages
• Using Containers
• Managing Consistency
• Lab : Implementing Control Flow in an SSIS Package
• Lab : Using Transactions and Checkpoints

Module 6: Debugging and Troubleshooting SSIS Packages

• Debugging an SSIS Package
• Logging SSIS Package Events
• Handling Errors in an SSIS Package
• Lab : Debugging and Troubleshooting an SSIS Package

Module 7: Implementing an Incremental ETL Process

• Introduction to Incremental ETL
• Extracting Modified Data
• Loading Modified data
• Lab : Extracting Modified DataLab : Loading Incremental Changes

Module 8: Enforcing Data Quality

• Introduction to Data Quality
• Using Data Quality Services to Cleanse Data
• Using Data Quality Services to Match data
• Lab : Cleansing DataLab : De-duplicating data

Module 9: Using Master Data Services

• Master Data Services Concepts
• Implementing a Master Data Services Model
• Managing Master Data
• Creating a Master Data Hub
• Lab : Implementing Master Data Services

Module 10: Extending SQL Server Integration Services

• Using Scripts in SSIS
• Using Custom Components in SSIS
• Lab : Using Custom Components and Scripts

Module 11: Deploying and Configuring SSIS Packages

• Overview of SSIS Deployment
• Deploying SSIS Projects
• Planning SSIS Package Execution
• Lab : Deploying and Configuring SSIS Packages

Module 12: Consuming Data in a Data Warehouse

• Introduction to Business Intelligence
• Introduction to Reporting
• An Introduction to Data Analysis
• Lab : Using Business Intelligence Tools

This course requires that you meet the following prerequisites:

• At least 2 years’ experience of working with relational databases, including:
• Designing a normalized database.
• Creating tables and relationships.
• Querying with Transact-SQL.
• Some exposure to basic programming constructs (such as looping and branching).

An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.

• 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.