Master Data Management (MDM) arose as a niche because of the increasing necessity for businesses to improve the consistency and quality of their key data assets.

Many businesses today, especially global ones, have hundreds of separate applications and systems gathering data – which can then become duplicated, fragmented, and out of date quite easily. When this happens, answering any question about any type of performance metric of your business can become an issue.

When you want answers to questions such as “how many employees do we have?”, “what products have the best margins?”, or “who are our most profitable customers?”, then you need the data, that the answers are based on, to be accurate.

The need for accurate and timely information is growing, especially as sources of data are increasing on a daily basis, and so managing it consistently is an ever-changing challenge. This is where Master Data Management (MDM) fits in.

What is Master Data?

Gartner defines Master Data as “the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts.”

There are usually six types of data found within most businesses:

  1. Hierarchical Data – data that stores the relationships between other data
  2. Metadata – data about other data
  3. Reference Data – used to categorise other data or relate information beyond the boundaries of the enterprise
  4. Transactional Data – about business events that have historical significance or are needed for analysis by other systems
  5. Unstructured Data – found in emails, product specification, marketing collateral, and so on
  6. Master Data – describes objects around which business is conducted

Within Master Data, therefore, there are also four general data domains, and these are:

  1. Customers – with customer, employee and salesperson subdomains
  2. Products – with the product, part, store and asset subdomains
  3. Locations – with office location and geographic division subdomains
  4. Other – things such as contract, licence and warranty subdomains

Some of these subdomains can also be further divided, which is helpful. For example, the Create Read Update and Delete cycle (CRUD), lifecycle and requirements for a product in the clothing industry, are going to be very different to those in the Consumer Packaged Goods sector (CPG).

How do companies decide what Master Data to manage?

Although it may not seem like it, identifying master data entities is pretty straightforward – although not all data that fits the definition of what master data is should be managed as such.

For most businesses, master data is usually just a small portion of all of your data, from a volume perspective, but it is some of the most complex data to manage and maintain, and also the most valuable.

Why do you need to manage Master Data?

As master data is used by multiple applications across your business, an error in the data in one place can cause an error in all of the applications that use it.

Let’s say you have the wrong address for a customer. This can lead to bills, orders and marketing materials being sent to the wrong place. Or if you have an incorrect price listed for an item you could end up with a marketing disaster.

What is Master Data Management?

What all this means is that Master Data Management (MDM) is the technology, tools and processes that ensure your master data is coordinated correctly across your business.

Depending on the technology used to manage the data, it may cover a single domain (such as customers or products), or multiple domains. The benefits of a multi-domain MDM strategy are:

  • Ability to share reference data across domains
  • Consistent data stewardship experience
  • Higher return on investment
  • Minimised technology footprint
  • Total lower cost of ownership

When it comes to Master Data Management, there are three core roles that you need to have within your team:

  • Data governance individuals to drive the definition, requirements and solution
  • IT administrators who set up and configure the solution
  • Data stewards responsible for fixing, cleaning and managing the data within the solution directly

There are also a variety of other MDM roles which will vary by organisation and project type, and these are:

  • Programme managers to own the data management strategy and platform
  • Project managers responsible for risk and issue management and escalation
  • System administrators and DBA for occasional support
  • Developers to implement custom SDK and workflow solutions to extend MDM platforms
  • ETL Developers to batch data loading from source systems
  • Business analysts who are familiar with the data and the business processes
  • Data architects and data modellers to oversee the enterprise conceptual, logical and physical data models
  • End users and data stewards
  • Governance council for decision and policy-making

If you have gaps in your MDM team or want to power your career in any of the above roles, please contact the Agile Recruit team today.

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