Data Quality and Master Data Management with SQL Server 2016


Data Quality Services, Master Data Services, and other SQL Server tools for data quality. Dealing with data quality issues is one of the most complex tasks in IT business. Learn how to raise and maintain data quality with SQL Server tools.


What does this course cover?

Data is the key asset of any organization. Companies want to gather information from the data, so they start business intelligence (BI) projects. However, most of the BI projects also have to deal with data quality problems. Data quality can represent a tremendous obstacle to the success of any BI project. Line of business (LOB) applications will certainly suffer from poor data quality as well.

Every company has some data that is used everywhere, in every process, in every transaction, such as customer or product data. This type of data is referred to as master data. People in charge of managing master data are usually referred to as data stewards. The processes and activities required to maintain master data is collectively referred to as master data management (MDM). In this course, you are going to learn about typical MDM problems and solutions. You will also become familiar with Microsoft tools for data quality and MDM, including Data Quality Services (DQS) and Master Data Services (MDS).

Author and Instructor

Dejan Sarka, MCT and SQL Server MVP, is an independent trainer and consultant that focuses on development of database & business intelligence applications.  Besides projects, he spends about half of the time on training and mentoring. He is the founder of the Slovenian SQL Server and .NET Users Group. Dejan Sarka is the main author or coauthor of thirteen books about databases and SQL Server. Dejan Sarka also developed many courses and seminars for Microsoft, SolidQ and Pluralsight.

Delivery format

Instructor-led training in class, with maximum number of attendees 12, 16 training hours spread in 2 days.

Technical Prerequisites

Every attendee should work on a dedicated virtual machine with the following software installed:

  • Windows Server 2012 R2
  • SQL Server 2016 Database Engine
  • SQL Server Integration Services
  • Master Data Services
  • Data Quality Services
  • SQL Server Data Tools
  • SQL Server Management Studio
  • AdventureWorks and AdventureWorksDW demo databases
  • Microsoft Excel 2013 or 2016 with Power Pivot enabled
  • Microsoft Excel Office Data Mining Add-ins
  • All the necessary Lab files copied in the virtual machine

“The instructor has an incredible amount of knowledge and gives a very polished presentation”

WHEN and WHERE is this course running?

Delivery format

Instructor-led training in class, with maximum number of attendees 12, 16 training hours spread in 2 days.


Attendees should understand relational databases and have a working knowledge with SQL Server.

Course format

This course contains about 60% theory and demos explained by the Trainer. About 40% of the time attendees perform practical exercise. After every module the group discuss the results of the lab to make sure that the concept and the practical scenarios are well understood.


Who is this course designed for?

  • Data stewards
  • BI application developers
  • Advanced administrators

Course Material

Every attendee gets a .PDF printout of all slides and detailed lab instructions. In addition, attendees are welcome to copy the demo and lab solutions for further reference.

Knowledge Assessment

To evaluate the knowledge of the attendees we developed 40 different questions. The questions can be split into two halves to assess the knowledge before and after the training.

All our courses can be offered as a private delivery and tailored for your team's specific needs

Course outline

Module 01: Introduction to Data Quality and Master Data Management

Lab 01: Checking for Data Quality Issues and Defining Master Data

Module 02: Installing and Maintaining Data Quality Services

Lab 02: Installing and Administering DQS

Module 03: Installing and Implementing Master Data Services

Lab 03: Installing MDS and Creating and Populating an MDS Model

Module 04: Managing Master Data with MDS

Lab 04: Importing and Exporting Data, Managing Security, and Using the MDS Add-in for Excel

Module 05: Data Cleansing with DQS

Lab 05: Creating a DQS Knowledge Base and Project and Using the DQS Cleansing Transformation

Module 06: Data Profiling with SQL Server Tools

Lab 06: Using the Linear Regression and Regression Trees algorithms


Module 07: Identity Mapping and De-Duplicating

Lab 07: DQS Matching and the SSIS Fuzzy Lookup Transformation

Module 08: Data Quality and Master Data Management with Excel

Lab 08: DQS Matching and Data Profiling with PowerPivot

WHEN and WHERE is this course running next?

This course may be scheduled in more than one region. Please check availability in your country.