Course 20767-C: Implementing a SQL Data Warehouse

Microsoft

Course 20767-C: Implementing a SQL Data Warehouse

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This five-day instructor-led 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.

Audience Profile

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.

Prerequisites

Course outline

Module 1: Introduction to Data Warehousing

Module Overview

This module describes data warehouse concepts and architecture consideration.

Lessons

Overview of Data Warehousing
Considerations for a Data Warehouse Solution

Lab Sessions

Exploring a Data Warehouse Solution

Lab Lessons

Exploring data sources
Exploring an ETL process
Exploring a data warehouse

After completing this module, students will be able to:

Describe the key elements of a data warehousing solution.
Describe the key considerations for a data warehousing solution.

Module 2: Planning Data Warehouse Infrastructure

Module Overview

This module describes the main hardware considerations for building a data warehouse.

Lessons

Considerations for data warehouse infrastructure
Planning data warehouse hardware

Lab Sessions

Planning Data Warehouse Infrastructure

Lab Lessons

Planning data warehouse hardware

After completing this module, students will be able to:

Describe the main hardware considerations for building a data warehouse.
Explain how to use reference architectures and data warehouse appliances to create a data warehouse.

Module 3: Designing and Implementing a Data Warehouse

Module Overview

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

Lab Sessions

Implementing a Data Warehouse Schema

Lab Lessons

Implementing a star schema
Implementing a snowflake schema
Implementing a time dimension table

After completing this module, students will be able to:

Implement a logical design for a data warehouse.
Implement a physical design for a data warehouse.

Module 4: Columnstore Indexes

Module Overview

This module introduces Columnstore Indexes.

Lessons

Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes

Lab Sessions

Using Columnstore Indexes

Lab Lessons

Create a Columnstore index on the FactProductInventory table
Create a Columnstore index on the FactInternetSales table
Create a memory optimized Columnstore table

After completing this module, students will be able to:

Create Columnstore indexes.
Work with Columnstore Indexes.

Module 5: Implementing an Azure SQL Data Warehouse

Module Overview

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

Lab Sessions

Implementing an Azure SQL Data Warehouse

Lab Lessons

Create an Azure SQL data warehouse database
Migrate to an Azure SQL Data warehouse database
Copy data with the Azure data factory

After completing this module, students will be able to:

Describe the advantages of Azure SQL Data Warehouse.
Implement an Azure SQL Data Warehouse.
Describe the considerations for developing an Azure SQL Data.
WarehousePlan for migrating to Azure SQL Data Warehouse.

Module 6: Creating an ETL Solution

Module Overview

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

Lab Sessions

Implementing Data Flow in an SSIS Package

Lab Lessons

Exploring source data
Transferring data by using a data row task
Using transformation components in a data row

After completing this module, students will be able to:

Describe ETL with SSIS.
Explore Source Data.
Implement a Data Flow.

Module 7: Implementing Control Flow in an SSIS Package

Module Overview

This module describes implementing control flow in an SSIS package.

Lessons

Introduction to Control Flow
Creating Dynamic Packages
Using Containers
Managing consistency

Lab Sessions

Implementing Control Flow in an SSIS Package
Using Transactions and Checkpoints

Lab Lessons

Using tasks and precedence in a control flow
Using variables and parameters
Using containers
Using transactions
Using checkpoints

After completing this module, students will be able to:

Describe control flow.
Create dynamic packages.
Use containers.

Module 8: Debugging and Troubleshooting SSIS Packages

Module Overview

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

Lab Sessions

Debugging and Troubleshooting an SSIS Package

Lab Lessons

Debugging an SSIS package
Logging SSIS package execution
Implementing an event handler
Handling errors in data flow

After completing this module, students will be able to:

Debug an SSIS package.
Log SSIS package events.
Handle errors in an SSIS package.

Module 9: Implementing a Data Extraction Solution

Module Overview

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

Lab Sessions

Extracting Modified Data
Loading a data warehouse

Lab Lessons

Using a datetime column to incrementally extract data
Using change data capture
Using the CDC control task
Using change tracking
Loading data from CDC output tables
Using a lookup transformation to insert or update dimension data
Implementing a slowly changing dimension
Using the merge statement

After completing this module, students will be able to:

Describe incremental ETL.
Extract modified data.
Load modified data.
Describe temporal tables.

Module 10: Enforcing Data Quality

Module Overview

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

Lab Sessions

Cleansing Data
De-duplicating Data

Lab Lessons

Creating a DQS knowledge base
Using a DQS project to cleanse data
Using DQS in an SSIS package
Creating a matching policy
Using a DS project to match data

After completing this module, students will be able to:

Describe data quality services.
Cleanse data using data quality services.
Match data using data quality services.
De-duplicate data using data quality services.

Module 11: Using Master Data Services

Module Overview

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

Lab Sessions

Implementing Master Data Services

Lab Lessons

Creating a master data services model
Using the master data services add-in for Excel
Enforcing business rules
Loading data into a model
Consuming master data services data

After completing this module, students will be able to:

Describe the key concepts of master data services.
Implement a master data service model.
Manage master data.
Create a master data hub.

Module 12: Extending SQL Server Integration Services (SSIS)

Module Overview

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

Lessons

Using scripting in SSIS
Using custom components in SSIS

Lab Sessions

Using scripts

Lab Lessons

Using a script task

After completing this module, students will be able to:

Use custom components in SSIS.
Use scripting in SSIS.

Module 13: Deploying and Configuring SSIS Packages

Module Overview

This module describes how to deploy and configure SSIS packages.

Lessons

Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution

Lab Sessions

Deploying and Configuring SSIS Packages

Lab Lessons

Creating an SSIS catalog
Deploying an SSIS project
Creating environments for an SSIS solution
Running an SSIS package in SQL server management studio
Scheduling SSIS packages with SQL server agent

After completing this module, students will be able to:

Describe an SSIS deployment.
Deploy an SSIS package.
Plan SSIS package execution.

Module 14: Consuming Data in a Data Warehouse

Module Overview

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

Lab Sessions

Using a data warehouse

Lab Lessons

Exploring a reporting services report
Exploring a PowerPivot workbook
Exploring a power view report

After completing this module, students will be able to:

Describe at a high level business intelligence.
Show an understanding of reporting.
Show an understanding of data analysis.
Analyze data with Azure SQL data warehouse.

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