20767 : Implementing a SQL Data Warehouse

The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role.  They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. 

Module 1: Introduction to Data Warehousing

This module describes data warehouse concepts and architecture consideration.

Lessons

·      Overview of Data Warehousing

·      Considerations for 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 data warehouse infrastructure.

·      Planning data warehouse hardware.

 

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

·      Data warehouse design overview

·      Designing dimension tables

·      Designing fact tables

·      Physical Design for a Data Warehouse

 

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.

Lessons

·      Introduction to Columnstore Indexes

·      Creating Columnstore Indexes

·      Working with 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

·      Copying data with the Azure data factory

 

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

 

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

·      Managing consistency.

 

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

 

Module 9: Implementing a Data Extraction Solution

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

·      Loading modified data

·      Temporal Tables

 

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

 

Module 11: Using Master Data Services

This module describes how to implement master data services to enforce data integrity at source.

Lessons

·      Introduction to Master Data Services

·      Implementing a Master Data Services Model

·      Hierarchies and collections

·      Creating a Master Data Hub

 

Module 12: Extending SQL Server Integration Services (SSIS)

This module describes how to extend SSIS with custom scripts and components.

Lessons

·      Using scripting in SSIS

·      Using custom components in SSIS

 

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

 

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.

Lessons

·      Introduction to Business Intelligence

·      An Introduction to Data Analysis

·      Introduction to reporting

·      Analyzing Data with Azure SQL Data Warehouse

MCSA: SQL 2016 BI Development

This 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. Earning an MCSA: SQL 2016 Business Intelligence Development certification qualifies you for a position as a BI developer.

Required Exams : 70-767 & 70-768

This certification retires on January 31, 2021. You will no longer be able to earn this certification after this date. 

In addition to their professional experience, students who attend this training should already have the following technical knowledge:

·      Basic knowledge of the Microsoft Windows operating system and its core functionality.

·      Working knowledge of relational databases.

·      Some experience with database design.