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Implementing a SQL Data Warehouse (M20767)

Implementing a SQL Data Warehouse (M20767)

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

In this course, provides students with the knowledge and skills to provision a Microsoft SQL Server database. The course covers SQL Server provision both on-premise and in Azure, and covers installing from new and migrating from an existing install. This course incorporates material from the Official Microsoft Learning Product 20767: and it can assist you in your preparation for Exam 70-767: Implementing a SQL Data Warehouse.

 

Learn more about this topic. View the recorded webinar Overview of Microsoft SQL Server and High Availability Options

GK# 4398 Vendor# M20767
Vendor Credits:
  • Global Knowledge Delivered Course
  • Training Exclusives
  • GSA Eligible
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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

What You'll Learn
  • Describe the key elements of a data warehousing solution
  • Describe the main hardware consideration 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 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 Maser Data Services model
  • Describe how you can use custom components to extend SSIS
  • Deploy SSIS projects
  • Describe BI and common BI scenarios

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
  • Planning data warehouse hardware

3. Designing and Implementing a Data Warehouse

  • Data warehouse design overview
  • Designing dimension tables
  • Designing fact tables
  • 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
  • Copying data with Azue data factory

6. Creating an ETL Solution

  • Introduction 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
  • Managing consistency

8. Debugging and Troubleshooting SSIS Packages

  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in Data Flow

9. Implementing a Data Extraction Solution

  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading 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

  • Introduction to Master Data Services Concepts
  • Implementing a Master Data Services Model
  • Hierarchies and Collections
  • 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

  • Introduction to Business Intelligence
  • An Introduction to Data Analysis
  • Introduction to Reporting
  • Analyzing Data with Azure SQL Data Warehouse
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Labs Outline

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 a data warehouse

Lab 12: Cleansing Data

Lab 13: De-duplicating Data

Lab 14: Implementing Master Data Services

Lab 15: Using Scripts

Lab 16: Deploying and Configuring SSIS Packages

Lab 17: Using a Data Warehouse

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

Related Certifications

Earning an MCSA: SQL 2016 Business Intelligence Development certification validates your extract, transform, and load (ETL) and data warehouse skills, along with those for implementing BI solutions using multidimensional and tabular data models and online analytical processing (OLAP) cubes. This certification will qualify you for a position as a BI developer.

Vendor Credits

This course is eligible for Software Assurance Training Vouchers (SATVs).

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