This course provides students with the knowledge and skills to provision a Microsoft SQL Server database. The course covers SQL Server provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.
After completing this course, students will be able to:
- Describe the key elements of a data warehousing solution.
- Describe the main hardware considerations for building a data warehouse.
- Implement a logical design for a data warehouse.
- Implement a physical design for a data warehouse.
- Create columnstore indexes.
- Implementing an Azure SQL Data Warehouse.
- Describe the key features of SSIS.
- Implement a data flow by using SSIS.
- Implement control flow by using tasks and precedence constraints.
- Create dynamic packages that include variables and parameters.
- Debug SSIS packages.
- Describe the considerations for implement an ETL solution.
- Implement Data Quality Services.
- Implement a Master Data Services model.
- Describe how you can use custom components to extend SSIS.
- Deploy SSIS projects.
- Describe BI and common BI scenarios.
The primary audience for this course are 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.
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
- Basic knowledge of the Microsoft Windows operating system and its core functionality.
- Working knowledge of relational databases.
- Some experience with database design.
- Course 20761 Querying Data with Transact-SQL.
Module 1: Introduction to Data Warehousing
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
Module 2: Planning Data Warehouse Infrastructure
- Considerations for data warehouse infrastructure.
- Planning data warehouse hardware.
Module 3: Designing and Implementing a Data Warehouse
- Data warehouse design overview
- Designing dimension tables
- Designing fact tables
- Physical Design for a Data Warehouse
Module 4: Columnstore Indexes
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
- Working with Columnstore Indexes
Module 5: Implementing an Azure SQL Data Warehouse
- Advantages of Azure SQL Data Warehouse
- Implementing an Azure SQL Data Warehouse
- Developing an Azure SQL Data Warehouse
- Migrating to an Azure SQ Data Warehouse
- Copying data with the Azure data factory
Module 6: Creating an ETL Solution
- Introduction to ETL with SSIS
- Exploring Source Data
- Implementing Data Flow
Module 7: Implementing Control Flow in an SSIS Package
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
- Managing consistency.
Module 8: Debugging and Troubleshooting SSIS Packages
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in an SSIS Package
Module 9: Implementing a Data Extraction Solution
- Introduction to Incremental ETL
- Extracting Modified Data
- Loading modified data
- Temporal Tables
Module 10: Enforcing Data Quality
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Match Data
Module 11: Using Master Data Services
- Introduction to Master Data Services
- Implementing a Master Data Services Model
- Hierarchies and collections
- Creating a Master Data Hub
Module 12: Extending SQL Server Integration Services (SSIS)
- Using scripting in SSIS
- Using custom components in SSIS
Module 13: Deploying and Configuring SSIS Packages
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
Module 14: Consuming Data in a Data Warehouse
- Introduction to Business Intelligence
- An Introduction to Data Analysis
- Introduction to reporting
- Analyzing Data with Azure SQL Data Warehouse
- MCSA: SQL 2016 Business Intelligence Development (Exam 70-767)