Microsoft: Implementing a SQL Data Warehouse (M20767)

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.

This course is also available in the On-Demand delivery format with digital Microsoft Official Courseware (dMOC). Click here to purchase.

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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

Viewing outline for:

Classroom Live 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

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

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

Viewing labs for:

Classroom Live 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 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

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

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

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

Querying Data with Transact-SQL (20761)

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.

MCSA: SQL 2016 Business Intelligence Development

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

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Implementing a SQL Data Warehouse (M20767)

Course Overview

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Classroom Live Labs

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