Master Data Management
Master Data Management (MDM) is the collective application of governance, business processes, policies, standards and tools facilitate consistency in data definition.
Master Data Management (MDM) refers to the process of creating and managing data that an organization must have as a single master copy, called the master data. Usually, master data can include customers, vendors, employees, and products, but can differ by different industries and even different companies within the same industry. MDM is important because it offers the enterprise a single version of the truth. Without a clearly defined master data, the enterprise runs the risk of having multiple copies of data that are inconsistent with one another.
MDM has the objective of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and applied use of this data.
Traditionally, Master Data could be code tables, a "master file", reference data, dimensions. Master Data (when established) should feed downstream data systems like Data Marts, data applications etc...
MDM is typically more important in larger organizations. In fact, the bigger the organization, the more important the discipline of MDM is, because a bigger organization means that there are more disparate systems within the company, and the difficulty on providing a single source of truth, as well as the benefit of having master data, grows with each additional data source. A particularly big challenge to maintaining master data occurs when there is a merger/acquisition. Each of the organizations will have its own master data, and how to merge the two sets of data will be challenging. Let's take a look at the customer files: The two companies will likely have different unique identifiers for each customer. Addresses and phone numbers may not match. One may have a person's maiden name and the other the current last name. One may have a nickname (such as "Bill") and the other may have the full name (such as "William"). All these contribute to the difficulty in creating and maintain in a single set of master data.
At the heart of the master data management program is the definition of the master data. Therefore, it is essential that we identify who is responsible for defining and enforcing the definition. Due to the importance of master data, a dedicated person or team should be appointed. At the minimum, a data steward should be identified. The responsible party can also be a group -- such as a data governance committee or a data governance council.
The key driver for MDM is to resolve inconsistencies in data from multiple systems, silos.
Master Data Management vs. Data Warehousing Based on the discussions so far, it seems like Master Data Management and Data Warehousing have a lot in common. For example, the effort of data transformation and cleansing is very similar to an ETL process in data warehousing, and in fact they can use the same ETL tools. In the real world, it is not uncommon to see MDM and data warehousing fall into the same project. On the other hand, it is important to call out the main differences between the two:
Common topics on MDM include:
- MDM Benefits
- MDM Selection Criteria
- MDM Features
- MDM Maturity
- Master Data Categories
- MDM Implementation Patterns
- Master Data Management Solutions
- Master Data Management Technology