Master Data Services (MDM) and Data Quality Services (DQS) are two essential components in maintaining the integrity of a database. In this article, we will delve into these concepts and understand how they work together to ensure high-quality master data.
Why Do We Need Master Data Management?
MDM plays a crucial role in business intelligence by combing through vast amounts of data and ensuring consistency, accuracy, and centralization. With MDM, employees no longer have to waste time searching for information scattered across multiple databases.
Why Do We Need Data Quality Services?
Data Quality Services consists of two parts: DQS Server and DQS Client. DQS Server acts as the hardware component, while DQS Client provides a user interface to set rules and validate data. These services help organizations achieve data accuracy, completeness, and consistency.
Implementations of MDM and DQS
Let’s explore four common implementations of Master Data Services and Data Quality Services:
- Create and build a new master data model and entity using Master Data Services and Data Quality Services.
- Update an existing master data entity in an automated lookup scenario using Integration Services, Master Data Services, and Data Quality Services.
- Include fuzzy matching in the automated update scenario to check for close matches when updating an existing master data entity.
- Perform matching on an existing entity using the Master Data Services Add-in for Excel.
By following these implementations, organizations can ensure that their master data remains accurate, consistent, and up-to-date.
Conclusion
Master Data Services and Data Quality Services are powerful tools in maintaining the integrity of a database. By implementing these services, organizations can achieve high-quality master data, leading to improved business intelligence and streamlined operations.