MOC 20767 - Implementing a SQL Data Warehouse

Course Number: MOC20767-W

Duration: 5 days

Format: Live, online

Overview

This 5-day MOC 20767 - Implementing a SQL Data Warehouse training class describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

This course is intended for database professionals who need to fulfill a Business Intelligence Developer role and need to create BI solutions including Data Warehouse implementation, ETL, and data cleansing.

Objectives

  • Learn to describe the key elements of a data warehousing solution.
  • Learn to describe the main hardware considerations for building a data warehouse.
  • Learn to implement a logical design for a data warehouse.
  • Learn to implement a physical design for a data warehouse.
  • Learn to create columnstore indexes.
  • Learn to implementing an Azure SQL Data Warehouse.
  • Learn to describe the key features of SSIS.
  • Learn to implement a data flow by using SSIS.
  • Learn to implement control flow by using tasks and precedence constraints.
  • Learn to create dynamic packages that include variables and parameters.
  • Learn to debug SSIS packages.
  • Learn to describe the considerations for implement an ETL solution.
  • Learn to implement Data Quality Services.
  • Learn to implement a Master Data Services model.
  • Learn to describe how you can use custom components to extend SSIS.
  • Learn to deploy SSIS projects.
  • Learn to describe BI and common BI scenarios .

Prerequisites

  • At least 2 years’ experience of working with relational databases, including:.
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.

Attendee Setup Instructions

For details about what is required when attending this class, please refer to the these instructions (will open in a seperate browser window).

Outline

  • Introduction to Data Warehousing
    • Overview of Data Warehousing
    • Considerations for a Data Warehouse Solution
    • Lab: Exploring a Data Warehouse Solution
  • Planning Data Warehouse Infrastructure
    • Considerations for Building a Data Warehouse
    • Data Warehouse Reference Architectures and Appliances
    • Lab: Planning Data Warehouse Infrastructure
  • Designing and Implementing a Data Warehouse
    • Logical Design for a Data Warehouse
    • Physical Design for a Data Warehouse
    • Lab: Implementing a Data Warehouse Schema
  • Columnstore Indexes
    • Introduction to Columnstore Indexes
    • Creating Columnstore Indexes
    • Working with Columnstore Indexes
    • Lab: Using Columnstore Indexes
  • 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
    • Lab: Implementing an Azure SQL Data Warehouse
  • Creating an ETL Solution
    • Introduction to ETL with SSIS
    • Exploring Source Data
    • Implementing Data Flow
    • Lab: Implementing Data Flow in an SSIS Package
  • Implementing Control Flow in an SSIS Package
    • Introduction to Control Flow
    • Creating Dynamic Packages
    • Using Containers
    • Lab: Implementing Control Flow in an SSIS Package and Lab: Using Transactions and Checkpoints
  • Debugging and Troubleshooting SSIS Packages
    • Debugging an SSIS Package
    • Logging SSIS Package Events
    • Handling Errors in an SSIS Package
    • Lab: Debugging and Troubleshooting an SSIS Package
  • Implementing an Incremental ETL Process
    • Introduction to Incremental ETL
    • Extracting Modified Data
    • Temporal Tables
    • Lab: Extracting Modified DataLab: Loading Incremental Changes
  • Enforcing Data Quality
    • Introduction to Data Quality
    • Using Data Quality Services to Cleanse Data
    • Using Data Quality Services to Match Data
    • Lab: Cleansing DataLab: De-duplicating Data
  • Using Master Data Services
    • Master Data Services Concepts
    • Implementing a Master Data Services Model
    • Managing Master Data
    • Creating a Master Data Hub
    • Lab: Implementing Master Data Services
  • Extending SQL Server Integration Services (SSIS)
    • Using Custom Components in SSIS
    • Using Scripting in SSIS
    • Lab: Using Scripts and Custom Components
  • Deploying and Configuring SSIS Packages
    • Overview of SSIS Deployment
    • Deploying SSIS Projects
    • Planning SSIS Package Execution
    • Lab: Deploying and Configuring SSIS Packages
  • Consuming Data in a Data Warehouse
    • Introduction to Business Intelligence
    • Introduction to Reporting
    • An Introduction to Data Analysis
    • Analyzing Data with Azure SQL Data Warehouse
    • Lab: Using Business Intelligence Tools

Schedule

Date / Time Price (USD)  
Nov 1 - 5
10 AM - 6 PM ET
$2,975 Register
Dec 6 - 10
10 AM - 6 PM ET
$2,975 Register
Jan 24 - 28
10 AM - 6 PM ET
$2,975 Register
Feb 28 - Mar 4
10 AM - 6 PM ET
$2,975 Register
Apr 4 - 8
11 AM - 7 PM ET
$2,975 Register
May 9 - 13
11 AM - 7 PM ET
$2,975 Register
Jun 13 - 17
11 AM - 7 PM ET
$2,975 Register
Jul 18 - 22
11 AM - 7 PM ET
$2,975 Register
Aug 22 - 26
11 AM - 7 PM ET
$2,975 Register
Sep 26 - 30
11 AM - 7 PM ET
$2,975 Register
Oct 31 - Nov 4
11 AM - 7 PM ET
$2,975 Register
Dec 5 - 9
10 AM - 6 PM ET
$2,975 Register
$2,975 USD
Nov 1 - 5
10 AM - 6 PM ET
Register
Dec 6 - 10
10 AM - 6 PM ET
Register
Jan 24 - 28
10 AM - 6 PM ET
Register
Feb 28 - Mar 4
10 AM - 6 PM ET
Register
Apr 4 - 8
11 AM - 7 PM ET
Register
May 9 - 13
11 AM - 7 PM ET
Register
Jun 13 - 17
11 AM - 7 PM ET
Register
Jul 18 - 22
11 AM - 7 PM ET
Register
Aug 22 - 26
11 AM - 7 PM ET
Register
Sep 26 - 30
11 AM - 7 PM ET
Register
Oct 31 - Nov 4
11 AM - 7 PM ET
Register
Dec 5 - 9
10 AM - 6 PM ET
Register
Learn faster

Our live, instructor-led lectures are far more effective than pre-recorded classes

Satisfaction guarantee

If your team is not 100% satisfied with your training, we do what's necessary to make it right

Learn online from anywhere

Whether you are at home or in the office, we make learning interactive and engaging

Multiple Payment Options

We accept check, ACH/EFT, major credit cards, and most purchase orders



Recent Training Locations

Alabama

Birmingham

Huntsville

Montgomery

Alaska

Anchorage

Arizona

Phoenix

Tucson

Arkansas

Fayetteville

Little Rock

California

Los Angeles

Oakland

Orange County

Sacramento

San Diego

San Francisco

San Jose

Colorado

Boulder

Colorado Springs

Denver

Connecticut

Hartford

DC

Washington

Florida

Fort Lauderdale

Jacksonville

Miami

Orlando

Tampa

Georgia

Atlanta

Augusta

Savannah

Hawaii

Honolulu

Idaho

Boise

Illinois

Chicago

Indiana

Indianapolis

Iowa

Cedar Rapids

Des Moines

Kansas

Wichita

Kentucky

Lexington

Louisville

Louisiana

New Orleans

Maine

Portland

Maryland

Annapolis

Baltimore

Frederick

Hagerstown

Massachusetts

Boston

Cambridge

Springfield

Michigan

Ann Arbor

Detroit

Grand Rapids

Minnesota

Minneapolis

Saint Paul

Mississippi

Jackson

Missouri

Kansas City

St. Louis

Nebraska

Lincoln

Omaha

Nevada

Las Vegas

Reno

New Jersey

Princeton

New Mexico

Albuquerque

New York

Albany

Buffalo

New York City

White Plains

North Carolina

Charlotte

Durham

Raleigh

Ohio

Akron

Canton

Cincinnati

Cleveland

Columbus

Dayton

Oklahoma

Oklahoma City

Tulsa

Oregon

Portland

Pennsylvania

Philadelphia

Pittsburgh

Rhode Island

Providence

South Carolina

Charleston

Columbia

Greenville

Tennessee

Knoxville

Memphis

Nashville

Texas

Austin

Dallas

El Paso

Houston

San Antonio

Utah

Salt Lake City

Virginia

Alexandria

Arlington

Norfolk

Richmond

Washington

Seattle

Tacoma

West Virginia

Charleston

Wisconsin

Madison

Milwaukee

Alberta

Calgary

Edmonton

British Columbia

Vancouver

Manitoba

Winnipeg

Nova Scotia

Halifax

Ontario

Ottawa

Toronto

Quebec

Montreal

Puerto Rico

San Juan