20767 - Implementing a SQL Data Warehouse (2016)


20767 - Implementing a SQL Data Warehouse (2016)


Price
Length : 5 days
$3,095.00

Learn to implement a data warehouse platform with Microsoft SQL Server 2016

In this course, you will learn how to implement a data warehouse platform to support a business intelligence (BI) solution. You will discover how to create a data warehouse, how to implement extract, transform, and load (ETL) with SQL Server Integration Services (SSIS), and how to validate and cleanse data with Data Quality Services (DQS) and Master Data Services.

What You'll Learn

• Overview of data warehousing
• Considerations for building a data warehouse
• Design and implementation for a data warehouse
• Columnstore indexes
• Azure SQL Data Warehouse
• ETL with SSIS
• Implement control flow in an SSIS package
• Debug and troubleshoot SSIS packages
• Incremental ETL and modified data extraction
• Microsoft DQS
• Master Data Services concepts and implementation
• Extend SSIS
• Deploy and configure SSIS packages
• BI tools with Azure SQL Data Warehouse

Prerequisites

• Basic knowledge of the Microsoft Windows operating system and its core functionality.
• Working knowledge of relational databases.
• Some experience with database design

Who Needs to Attend

• Database professionals who need to fulfill a BI developer role focused on hands-on work by creating BI solutions, including data warehouse implementation, ETL and data
cleansing
• Database professionals responsible for implementing a data warehouse, developing SSIS packages for data ETL, enforcing data integrity using Microsoft Data Services and
cleansing data using Data Quality Services

Course Outline

1. Introduction to Data Warehousing
• Overview of Data Warehousing
• Considerations for a Data Warehouse Solution
2. Planning Data Warehouse Infrastructure
• Considerations for Building a Data Warehouse
• Data Warehouse Reference Architectures and Appliances
3. Designing and Implementing a Data Warehouse
• Logical Design for a Data Warehouse
• Physical Design for a Data Warehouse
4. Columnstore Indexes
• Introduction to Columnstore Indexes
• Creating Columnstore Indexes
• Working with Columnstore Indexes
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
6. Creating an ETL Solution
• ETL with SSIS
• Exploring Source Data
• Implementing Data Flow
7. Implementing Control Flow in an SSIS Package
• Introduction to Control Flow
• Creating Dynamic Packages
• Using Containers
8. Debugging and Troubleshooting SSIS Packages
• Debugging an SSIS Package
• Logging SSIS Package Events
• Handling Errors in an SSIS Package
9. Implementing an Incremental ETL Process
• Introduction to Incremental ETL
• Extracting Modified Data
• Temporal Tables
10. Enforcing Data Quality
• Introduction to Data Quality
• Using Data Quality Services to Cleanse Data
• Using Data Quality Services to Match Data
11. Using Master Data Services
• Master Data Services Concepts
• Implementing a Master Data Services Model
• Managing Master Data
• Creating a Master Data Hub
12. Extending SQL Server Integration Services (SSIS)
• Using Custom Components in SSIS
• Using Scripting in SSIS
13. Deploying and Configuring SSIS Packages
• Overview of SSIS Deployment
• Deploying SSIS Projects
• Planning SSIS Package Execution
14. Consuming Data in a Data Warehouse
• Business Intelligence
• Reporting
• Data Analysis
• Analyzing Data with Azure SQL Data Warehouse

Labs

Lab 1: Exploring a Data Warehouse Solution
Lab 2: Planning Data Warehouse Infrastructure
Lab 3: Implementing a Data Warehouse Schema
Lab 4: Using Columnstore Indexes
Lab 5: Implementing an Azure SQL Data Warehouse
Lab 6: Implementing Data Flow in an SSIS Package
Lab 7: Implementing Control Flow in an SSIS Package
Lab 8: Using Transactions and Checkpoints
Lab 9: Debugging and Troubleshooting an SSIS Package
Lab 10: Extracting Modified Data
Lab 11: Loading Incremental Changes
Lab 12: Cleansing Data
Lab 13: De-duplicating Data
Lab 14: Implementing Master Data Services
Lab 15: Using Scripts and Custom Components
Lab 16: Deploying and Configuring SSIS Packages
Lab 17: Using Business Intelligence Tools

Class Dates:

Classes being scheduled,
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