Master Data Management

If you’re like me, you’ve been hearing a lot about Master Data Management lately. Master Data Management is not an entirely new theory; it goes back to the Master File idea from the days of the mainframe. The basic concept is to have a single ‘correct’ set of data that the entire company will use.

During this time of data marts, pivot tables made from excel spreadsheets, and data spread throughout the company, this concept has made a big comeback. Mergers and acquisitions, as well as data being managed by separate departments, contribute to the lack of data consistency across the organization. For example, you would never have your current cable provider calling to inquire if you’d like to switch your cable to… your current cable provider. This type of mishap usually occurs because there is a ‘sales lead’ database that is not reconciled with a ‘current customer’ database. Master Data Management (MDM) requires the company to first define their data and agree upon what it all means.

The objective of MDM is to ensure that all of the non-transactional data in the company (what some might call a reporting database or a data warehouse) is consistent throughout the organization. In other words, the idea is that the ‘right hand’ of the organization will always know what the ‘left hand’ is doing. Once the data definition is agreed upon, the company must ensure that all data collection and data manipulation follow the data definition perfectly. The data is then processed and stored in a single location, and all BI, reporting, CRM, ERP, and other functionality feed off of this single repository.

Virtual Master Data Management (VMDM) is considered the fourth generation of MDM solutions. VMDM uses abstraction layers in the data model to create a metadata catalog. The data is not actually consolidated into a single storage location, like it is in the more typical MDM solution. Instead, the catalog contains an index of the information and is used to make sure that all data is consistent across the organization and that the ‘true’ source of each piece of information is known and documented. The data is dynamically transformed when requested by a BI, CRM, or ERP solution.

There is an obvious time advantage in using VMDM as opposed to a typical MDM solution. The project life cycle of MDM includes the definition and analysis phase, as well as the development phase, during which ETL processes are written to transform and load the data into the newly defined structures. Since you are often storing the data both in its originating system, and also in the MDM solution, you can save on storage costs with VMDM.

Although MDM has many positive attributes, many companies have found it cumbersome to implement in its purest form. The concept of VMDM allows for data governance with a significant time and cost reduction.

Katy Park, SQL Server Team Lead


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