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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.
Course Length: 5 days
Audience: 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.
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.
What You're Going To Learn
- Learn to describe data warehouse concepts and architecture considerations.
- Learn to select an appropriate hardware platform for a data warehouse.
- Learn to design and implement a data warehouse.
- Learn to implement Data Flow in an SSIS Package.
- Learn to implement Control Flow in an SSIS Package.
- Learn to debug and Troubleshoot SSIS packages.
- Learn to implement an ETL solution that supports incremental data extraction.
- Learn to implement an ETL solution that supports incremental data loading.
- Learn to implement data cleansing by using Microsoft Data Quality Services.
- Learn to implement Master Data Services to enforce data integrity.
- Learn to extend SSIS with custom scripts and components.
- Learn to deploy and Configure SSIS packages.
- Learn to describe how BI solutions can consume data from the data warehouse.
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Introduction to Data Warehousing
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
- Lab: Exploring a Data Warehousing Solution
Data Warehouse Hardware Considerations
- Considerations for building a Data Warehouse
- Data Warehouse Reference Architectures and Appliances
- Lab: Planning Data Warehouse Infrastructure
Designing and Implementing a Data Warehouse
- Logical Design for a Data Warehouse
- Physical design for a data warehouse
- Lab: Implementing a Data Warehouse Schema
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
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
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
Implementing an Incremental ETL Process
- Introduction to Incremental ETL
- Extracting Modified Data
- Loading Modified data
- Lab: Extracting Modified DataLab: Loading Incremental Changes
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
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
Extending SQL Server Integration Services
- Using Scripts in SSIS
- Using Custom Components in SSIS
- Lab: Using Custom Components and Scripts
Deploying and Configuring SSIS Packages
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
- Lab: Deploying and Configuring SSIS Packages
Consuming Data in a Data Warehouse
- Introduction to Business Intelligence
- Introduction to Reporting
- An Introduction to Data Analysis
- Lab: Using Business Intelligence Tools