Implementing a SQL Data Warehouse

Duration : 5 Days

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.

Job role: Database Administrator

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

Lab : Exploring a Data Warehouse Solution

Exploring data sources
Exploring an ETL process
Exploring a data warehouse

After completing this module, you 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

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

Lessons

Considerations for data warehouse infrastructure.
Planning data warehouse hardware.

Lab : Planning Data Warehouse Infrastructure

Planning data warehouse hardware

After completing this module, you 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

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 : Implementing a Data Warehouse Schema

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

After completing this module, you will be able to:

Implement a logical design for a data warehouse
Implement a 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

Lab : Using Columnstore Indexes

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, you will be able to:

Create Columnstore indexes
Work 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

Lab : Implementing an Azure SQL Data Warehouse

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, you 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

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 : Implementing Data Flow in an SSIS Package

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

After completing this module, you will be able to:

Describe ETL with SSIS
Explore Source Data
Implement a 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.

Lab : Implementing Control Flow in an SSIS Package

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

Lab : Using Transactions and Checkpoints

Using transactions
Using checkpoints

After completing this module, you will be able to:

Describe control flow
Create dynamic packages
Use containers

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

Lab : Debugging and Troubleshooting an SSIS Package

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

After completing this module, you 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

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 : Extracting Modified Data

Using a datetime column to incrementally extract data
Using change data capture
Using the CDC control task
Using change tracking

Lab : Loading a data warehouse

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, you will be able to:

Describe incremental ETL
Extract modified data
Load modified data
Describe 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

Lab : Cleansing Data

Creating a DQS knowledge base
Using a DQS project to cleanse data
Using DQS in an SSIS package

Lab : De-duplicating Data

Creating a matching policy
Using a DS project to match data

After completing this module, you 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

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 : Implementing Master Data Services

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, you 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)

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

Lessons

Using scripting in SSIS
Using custom components in SSIS

Lab : Using scripts

Using a script task

After completing this module, you will be able to:

Use custom components in SSIS
Use scripting 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

Lab : Deploying and Configuring SSIS Packages

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, you will be able to:

Describe an SSIS deployment
Deploy an SSIS package
Plan 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

Lab : Using a data warehouse

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

After completing this module, you 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

Skills gained

Describe the key elements of a data warehousing solution
Describe the main hardware considerations 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 a data flow by using 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 Master Data Services model
Describe how you can use custom components to extend SSIS
Deploy SSIS projects
Describe BI and common BI scenarios

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.

Regular Price : ~~$3000.00~~
Special Price :$1500.00

Implementing a SQL Data Warehouse

Audience profile

Module 1: Introduction to Data Warehousing

Lessons

Lab : Exploring a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure

Lessons

Lab : Planning Data Warehouse Infrastructure

Module 3: Designing and Implementing a Data Warehouse

Lessons

Lab : Implementing a Data Warehouse Schema

Module 4: Columnstore Indexes

Lessons

Lab : Using Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse

Lessons

Lab : Implementing an Azure SQL Data Warehouse

Module 6: Creating an ETL Solution

Lessons

Lab : Implementing Data Flow in an SSIS Package

Module 7: Implementing Control Flow in an SSIS Package

Lessons

Lab : Implementing Control Flow in an SSIS Package

Lab : Using Transactions and Checkpoints

Module 8: Debugging and Troubleshooting SSIS Packages

Lessons

Lab : Debugging and Troubleshooting an SSIS Package

Module 9: Implementing a Data Extraction Solution

Lessons

Lab : Extracting Modified Data

Lab : Loading a data warehouse

Module 10: Enforcing Data Quality

Lessons

Lab : Cleansing Data

Lab : De-duplicating Data

Module 11: Using Master Data Services

Lessons

Lab : Implementing Master Data Services

Module 12: Extending SQL Server Integration Services (SSIS)

Lessons

Lab : Using scripts

Module 13: Deploying and Configuring SSIS Packages

Lessons

Lab : Deploying and Configuring SSIS Packages

Module 14: Consuming Data in a Data Warehouse

Lessons

Lab : Using a data warehouse

Skills gained

This course includes: