Master Data Management, Data Models and Enterprise Applications

Wikipedia defines Master Data Management (MDM), also known as Reference Data Management, as a discipline that focuses on the management of reference or master data that is shared by several disparate IT systems and groups.

MDM is required to warrant consistent computing between diverse system architectures and business functions.

The Challenge

Examples of master data items are customer numbers, product codes, account numbers and currency codes, so by definition, master data describes the core data about an organization.

But despite being of vital importance to any company, master data is often wildly inconsistent across different divisions and systems. Data values that should uniquely describe entities are often different in different business units. Relationships between entities such as products and suppliers are often defined differently in different information systems. Further, identifiers that are supposed to be unique to each entity are sometimes either used multiple times or used incorrectly.

The cost of such inconsistencies can be enormous.  Perhaps the most critical area where data inconsistency shows itself is in affecting an organization's ability to comply with data governance/compliance regulations such as Sarbanes-Oxley.

The Data Modeling Challenge

The first step for any MDM initiative is to select a set of entities to be analyzed. Typically, these will include entities that represent key business concepts such as customers, suppliers, products and finances.

The next step should be to analyze each entity across the companies various information systems, checking the data items chosen for a range of factors including accuracy, completeness, and consistency.

There is no immediate quick fix to this metadata challenge - it is an ongoing process of discovery, documentation and debate between technical & business communities in the organisation.

Enterprise Applications - adding to the Challenge

Enterprise Applications such as SAP, Siebel, PeopleSoft etc only add to this challenge due to the complexity & opaqueness of their data architectures.

Given that such packages are now probably the major sources of operational and analytical data within companies, it is critical that they can be integrated into any data modeling or metadata management strategy in support of MDM initiatives.

Most EA vendors will have an approach to MDM but Saphir technology remains the only toolset dedicated to delivering such EA metadata intelligence and directly interfacing to the leading data modeling tools.

Saphir is therefore a vital tool for any organization that has Master Data residing in one or more Enterprise Application, allowing exploration and comparison of data structures from these complex application environments.