Introduction to Data Warehousing
This module provides an introduction to the key components of a data warehousing
solution and the high-level considerations you must take into account when you embark
on a data warehousing project.
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
- LAB: Inspecting an SSIS Solution
Planning Data Warehouse Infrastructure
This module discusses considerations for selecting hardware and distributing SQL Server facilities across
- Considerations for Data Warehouse Infrastructure
- Planning Data Warehouse Hardware
Designing and Implementing a Data Warehouse
This module describes the key considerations for the logical design of a data warehouse, and then discusses best
practices for its physical implementation.
- Data Warehouse Design Overview
- Designing Dimension Tables
- Designing Fact Tables
- Physical Design for a Data Warehouse
- LAB: Implementing dimension and fact tables in SQL Server
Indexing is crucial for performance. Typical BI queries have different indexing needs that operational queries.
This module explains how to create and maintain columnstore indexes, which are ideal suited for most BI needs.
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
- Working with Columnstore Indexes
- LAB: creating and querying ColumnStore Indexes in SQL Server
Implementing a Data Warehouse on Azure Synapse Analytics
This module introduces how to host a data warehouse in Azure using provisioned databases in Azure Synapse
Analytics, formerly known as Azure SQL Data Warehouse.
- Advantages of Azure Synapse Analytics
- Provisioning an Azure Synapse Analytics Workspace
- Basics of developing on Azure Synapse Analytics Provisioned SQL Pool
Creating an ETL Solution
This module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server
Integration Services (SSIS) as a platform for building ETL solutions.
- Introduction to ETL with SSIS
- Exploring Data Sources
- Implementing Data Flow
- LAB: Developing an SSIS data flow in Visual Studio
Implementing Control Flow in an SSIS Package
This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
- Managing Consistency
- LAB: Creating an SSIS package control flow
Debugging and Troubleshooting SSIS Packages
This module describes how you can debug packages to find the cause of errors that occur during execution. It
then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting
purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in an SSIS Package
- LAB: Debugging, logging and event handlers in SSIS
Implementing a Data Extraction Solution
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
- Planning Data Extraction
- Extracting Modified Data
- LAB: Implementing an incremental data load
Enforcing Data Quality
Ensuring the high quality of data is essential if the results of data analysis are to be trusted. SQL Server
includes Data Quality Services (DQS) to provide a computer-assisted process for cleansing data values, as well
as identifying and removing duplicate data entities. This process reduces the workload of the data steward to a
minimum while maintaining human interaction to ensure accurate results.
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Cleanse Data
- LAB: Data Quality Services
Master Data Services
Master Data Services provides a way for organizations to standardize and improve the quality, consistency, and
reliability of the data that guides key business decisions. This module introduces Master Data Services and
explains the benefits of using it.
- Introduction to Master Data Services
- Implementing a Master Data Services Model
- Managing Master Data
- Creating a Master Data Hub
- LAB: Working with Master Data Services
Extending SQL Server Integration Services
This module describes the techniques you can use to extend SSIS. The module is not designed to be a
comprehensive guide to developing custom SSIS solutions, but to provide an awareness of the fundamental steps
required to use custom components and scripts in an ETL process, based on SSIS.
- Using Scripts in SSIS
- Using Custom Components in SSIS
- LAB: Using the Script task and Script component
Deploying and Configuring SSIS Packages
Microsoft SQL Server Integration Services (SSIS) provides tools that make it easy to deploy packages to another
computer. The deployment tools also manage any dependencies, such as configurations and files that the package
needs. In this module, you will learn how to use these tools to install packages and their dependencies on a
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
- LAB: Deploying packages in project and in package deployment mode
Consuming Data in a Data Warehouse
This module introduces BI, describing the components of Microsoft SQL Server that you can use to create a BI
solution, and the client tools with which users can create reports and analyze data.
- Introduction to Business Intelligence
- Enterprise Business Intelligence
- Self-Service BI and Big Data