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Implementing a SQL Data Warehouse (M20767)

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      EXCLUSIVE BENEFITS:

      This course comes with 12 months access to the following benefits:

      • Practice Labs
      • 24×7 Mentoring
      • Indexed Class Recordings
      • Unlimited Retakes
      • Digital Courseware

      COURSE INFORMATION

      Implementing a SQL Data Warehouse (M20767) Course Overview:

      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.

      This course uses Microsoft SQL Server 2016 and incorporates material from the Official Microsoft Learning Product 20767: Implementing a SQL Data Warehouse.

      Who Should 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.

      Implementing a SQL Data Warehouse (M20767) Course Prerequisites:

      Before attending this course, you must have the following:

      • Basic knowledge of the Microsoft Windows operating system and its core functionality
      • Working knowledge of relational databases
      • Some experience with database design
      • Attended Querying Data with Transact-SQL (M20761)

      Implementing a SQL Data Warehouse (M20767) Course Objectives:

      After successfully completing this course, you will be able to:

      • 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.

      Implementing a SQL Data Warehouse (M20767) Course Outline:

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

      Implementing a SQL Data Warehouse (M20767) Course 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 7A: Implementing Control Flow in an SSIS Package
      • Lab 7B: Using Transactions and Checkpoints
      • Lab 8: Debugging and Troubleshooting an SSIS Package
      • Lab 9A: Extracting Modified Data
      • Lab 9B: Loading Incremental Changes
      • Lab 10A: Cleansing Data
      • Lab 10B: De-duplicating Data
      • Lab 11: Implementing Master Data Services
      • Lab 12: Using Scripts and Custom Components
      • Lab 13: Deploying and Configuring SSIS Packages
      • Lab 14: Using Business Intelligence Tools

      Average Salary for Skill: Microsoft SQL Server

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