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20767-Implementing a SQL Data Warehouse
This 4-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.
Lesson objectives help students become comfortable with the course, and also provide a means to evaluate learning. Upon successful completion of 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
To ensure successful completion of this course, we recommend the following: · 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.
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 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 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 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 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 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 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 Package · Lab : Using Transactions and Checkpoints 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 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 Data · Lab : Loading Incremental Changes 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 Data · Lab : De-duplicating Data 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 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 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 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
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