|
Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.Lessons
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
Lab : Exploring a Data Warehouse Solution
After completing this module, you will be able to:
- Describe the key elements of a data warehousing solution
- Describe the key considerations for a data warehousing solution
Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.Lessons
- Considerations for Building a Data Warehouse
- Data Warehouse Reference Architectures and Appliances
Lab : Planning Data Warehouse Infrastructure
After completing this module, you will be able to:
- Describe the main hardware considerations for building a data warehouse
- Explain how to use reference architectures and data warehouse appliances to create a data warehouse
Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.Lessons
- Logical Design for a Data Warehouse
- Physical Design for a Data Warehouse
Lab : Implementing a Data Warehouse Schema
After completing this module, you will be able to:
- Implement a logical design for a data warehouse
- Implement a physical design for a data warehouse
Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.Lessons
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
- Working with Columnstore Indexes
Lab : Using Columnstore Indexes
After completing this module, you will be able to:
- Create Columnstore indexes
- Work with Columnstore Indexes
Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.Lessons
- 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
Lab : Implementing an Azure SQL Data Warehouse
After completing this module, you will be able to:
- Describe the advantages of Azure SQL Data Warehouse
- Implement an Azure SQL Data Warehouse
- Describe the considerations for developing an Azure SQL Data Warehouse
- Plan for migrating to Azure SQL Data Warehouse
Module 6: Creating an ETL Solution
At the end of this module you will be able to implement data flow in a SSIS package.Lessons
- Introduction to ETL with SSIS
- Exploring Source Data
- Implementing Data Flow
Lab : Implementing Data Flow in an SSIS Package
After completing this module, you will be able to:
- Describe ETL with SSIS
- Explore Source Data
- Implement a Data Flow
Module 7: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.Lessons
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
Lab : Implementing Control Flow in an SSIS PackageLab : Using Transactions and Checkpoints
After completing this module, you will be able to:
- Describe control flow
- Create dynamic packages
- Use containers
Module 8: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.Lessons
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in an SSIS Package
Lab : Debugging and Troubleshooting an SSIS Package
After completing this module, you will be able to:
- Debug an SSIS package
- Log SSIS package events
- Handle errors in an SSIS package
Module 9: Implementing an Incremental ETL Process
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.Lessons
- Introduction to Incremental ETL
- Extracting Modified Data
- Temporal Tables
Lab : Extracting Modified DataLab : Loading Incremental Changes
After completing this module, you will be able to:
- Describe incremental ETL
- Extract modified data
- Describe temporal tables
Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.Lessons
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Match Data
Lab : Cleansing DataLab : De-duplicating Data
After completing this module, you will be able to:
- Describe data quality services
- Cleanse data using data quality services
- Match data using data quality services
- De-duplicate data using data quality services
Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.Lessons
- Master Data Services Concepts
- Implementing a Master Data Services Model
- Managing Master Data
- Creating a Master Data Hub
Lab : Implementing Master Data Services
After completing this module, you will be able to:
- Describe the key concepts of master data services
- Implement a master data service model
- Manage master data
- Create a master data hub
Module 12: Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.Lessons
- Using Custom Components in SSIS
- Using Scripting in SSIS
Lab : Using Scripts and Custom Components
After completing this module, you will be able to:
- Use custom components in SSIS
- Use scripting in SSIS
Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.Lessons
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
Lab : Deploying and Configuring SSIS Packages
After completing this module, you will be able to:
- Describe an SSIS deployment
- Deploy an SSIS package
- Plan SSIS package execution
Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.Lessons
- Introduction to Business Intelligence
- Introduction to Reporting
- An Introduction to Data Analysis
- Analyzing Data with Azure SQL Data Warehouse
Lab : Using Business Intelligence Tools
After completing this module, you will be able to:
- Describe at a high level business intelligence
- Show an understanding of reporting
- Show an understanding of data analysis
- Analyze data with Azure SQL data warehouse
|