Master Data Services (MDM) and Data Quality Services (DQS) go hand to hand together when they have to maintain the integrity of the database. If you are new to either of concept I suggest you to read following two articles to get an idea about them.
Why Do We Need Master Data Management:
MDM was hailed as a major improvement for business intelligence. MDM comes into play because it will comb through these mountains of data and make sure that all the information is consistent, accurate, and all placed in one database so that employees don’t have to search high and low and waste their time.
Why Do We Need Data Quality Services:
There are two parts of Data Quality Services that help you accomplish all these neat things. The first part is DQL Server, which you can think of as the hardware component of the system. DQS Client is the user interface that you can interact with to set the rules and check over your data.
MDM working along with DQS
To help you understand how Master Data Services and Data Quality Services work together to ensure high-quality master data, this paper looks at four common implementations of these tools: one for entering new master data in a new Master Data Services entity, and three for updating existing master data as new data comes in.
- Create and build a new master data model and an entity within the model that will contain the data for a field, using Master Data Services and Data Quality Services
- Update an existing master data entity in an EIM automated lookup scenario using Integration Services, Master Data Services, and Data Quality Services
- Include checks for close matches when updating an existing master data entity, by adding fuzzy matching to the EIM automated update scenario
- Perform matching on an existing entity from within the Master Data Services Add-in for Excel.
Reference: Pinal Dave (https://blog.sqlauthority.com)