Opis
This 5-day instructor led 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® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.
Poželjno predznanje
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.
Plan obuke
Module 1: Introduction to Data Warehousing
This module describes data warehouse concepts and architecture consideration.
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.
- Considerations for data warehouse infrastructure.
- Planning data warehouse hardware.
Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.
- Data warehouse design overview
- Designing dimension tables
- Designing fact tables
- Physical Design for a Data Warehouse
Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
- Working with Columnstore Indexes
Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.
- 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
At the end of this module you will be able to implement data flow in a SSIS package.
- Introduction to ETL with SSIS
- Exploring Source Data
- Implementing Data Flow
Module 7: Implementing Control Flow in an SSIS Package
This module describes 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
This module describes how to debug and troubleshoot SSIS packages.
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in an SSIS Package
Module 9: Implementing a Data Extraction Solution
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.
- Introduction to Incremental ETL
- Extracting Modified Data
- Loading modified data
- Temporal Tables
Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Match Data
Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.
- 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)
This module describes how to extend SSIS with custom scripts and components.
- Using scripting in SSIS
- Using custom components in SSIS
Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.
- Introduction to Business Intelligence
- An Introduction to Data Analysis
- Introduction to reporting
- Analyzing Data with Azure SQL Data Warehouse
