The What, Why, and How of Master Data Management

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What Is Master Data?

What Is Master Data?

Most software systems have lists of data that are shared and used by several of the applications that make up the system. For example, a typical ERP system as a minimum will have a Customer Master, an Item Master, and an Account Master. This master data is often one of the key assets of a company. It’s not unusual for a company to be acquired primarily for access to its Customer Master data.

In the current IT portfolio asset management project I am involved in, the master data are:

1) Hardware assets: these include data center machines, mainframe, mid-range, virtual machines, etc. Large corporations with many data centers have a need for a master data repository of these assets .

2) PC and peripheral assets, and the software installed on these assets.

3) Portfolio Applications. These are enterprise or departmental applications, such as an ERP, a CRM system, or a sales management system, a billing system. The server components of these applications are installed on server machines located a a data center.

4) Software installation and license or contract data

5) HR data

Master Data – Why

Large companies face challenges from emphasis on regulatory compliance, such as software license compliance (not mention the auditing pressure from internal organization and external vendors), consistent reporting, and mergers and acquisitions, it has made the creating and maintaining of accurate and complete master data a business imperative.

MDM in Practice

Here is an article from www.SearchSQLServer.com:

http://viewer.media.bitpipe.com/1216309501_94/1268760175_892/Master-Data-Management-Projects-in-Practice_An-Information-Difference-Research-Study.pdf

Master Data Management

Here is what Wikipedia (http://en.wikipedia.org/wiki/Master_Data_Management) defines Master Data Management:

In computing, master data management (MDM) comprises a set of processes and tools that consistently defines and manages the non-transactional data entities of an organization (which may include reference data). 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 application use of this information.

The term recalls the concept of a master file from an earlier computing era. MDM is similar to, and some would say the same as, virtual or federated database management.

Issues

At a basic level, MDM seeks to ensure that an organization does not use multiple (potentially inconsistent) versions of the same master data in different parts of its operations, which can occur in large organizations.

Other problems include (for example) issues with the quality of data, consistent classification and identification of data, and data-reconciliation issues.

One of the most common reasons some large corporations experience massive issues with MDM is growth through mergers and acquisitions. Two organizations which merge will typically create an entity with duplicate master data (since each likely had at least one master database of its own prior to the merger).

Solutions

Processes commonly seen in MDM solutions include source identification, data collection, data transformation, normalization, rule administration, error detection and correction, data consolidation, data storage, data distribution, and data governance.

The tools include data networks, file systems, a data warehouse, data marts, an operational data store, data mining, data analysis, data federation and data visualization.

The selection of entities considered for MDM depends somewhat on the nature of an organization. In the common case of commercial enterprises, MDM may apply to such entities as customer (Customer Data Integration), product (Product Information Management), employee, and vendor. MDM processes identify the sources from which to collect descriptions of these entities. In the course of transformation and normalization, administrators adapt descriptions to conform to standard formats and data domains, making it possible to remove duplicate instances of any entity. Such processes generally result in an organizational MDM repository, from which all requests for a certain entity instance produce the same description, irrespective of the originating sources and the requesting destinations.

Criticism of MDM Solutions

Large costs and low return on investment from major MDM solution providers.