As a result of data management tools rising to prominence in the 1980s and coming into use in the 1990s, Master Data Management is not a new concept by any stretch of the imagination, it is, however, far more integral to the continued success of any organisation that holds large quantities of data.

What is MDM and why is it so important? In this blog post, we’ll take a look at what MDM is, why it’s essential for businesses and how it can be linked with Data Quality to improve the maturity of your organisation’s data management.

What is Master Data & MDM?

There are many different definitions of Master Data Management, but all centre on the consistent management of data that is vital to the effective use of an organisation’s master data.

Master data is core data to help manage business processes, providing context around the data assets that an organisation holds around particular data domains. For instance, its customers, products, employees, partners, suppliers and more. Typically, master data is a uniform set of identifiers about these data assets that are referred to as the Golden Record or Golden Nominal and can help inform Single Customer Views.

Master Data Management, then, is the tools, processes and people that ensure this master data is complete, accurate & able to be used to inform business decision-making capabilities across the organisation.

How is MDM useful for my organisation?

As we can see from our definitions above, Master Data and its management is no small undertaking and many frameworks exist to help implement it. It’s an ongoing task that is multidisciplinary in nature.

Data is the lifeblood of every organisation and managing it effectively is absolutely critical to success in 2022 and beyond as we continue to rely more and more on the timeliness and accuracy of ever-increasing amounts of data.

Take for example, a supermarket chain. Vast amounts of product data from different stores must be available across the entire organisation and it needs to be accurate, consistent and without duplication. It is likely that this supermarket chain will need a solution that can store and centrally manage all this data in one place, making it accessible to the people who need it when they need it.

Product Master Data Management (PMDM) brings all the product data into one place to create a single source of truth. This allows you to feed your systems, customers, retailers and partners with consistent, accurate and timely product data. PMDM ensures your customers find correct and rich product details in your catalog, webshop and sales channels^.

How do MDM and Data Quality connect?

Whilst we know that both MDM and Data Quality (DQ) are ongoing processes, not one-offs, we can see DQ as an enabler of MDM and vice versa, for MDM, clearly demonstrates the business case – the need – for high-quality data.

Many of the features and outputs of DQ can enhance an ongoing MDM project.

Standardisation ensures uniformity across multiple data sources and business views of data, transforming the data into consistent formatting that is beneficial for all who intend to use it. In the case of PMDM we can help organisations maintain a consistent representation of their product assets.

Cleansing of data is another vital component for any successful MDM project and will correct inaccurate, incomplete, or otherwise erroneous data by either removing or fixing it.

Validation of the data post-cleanse can be used to ensure that, for instance, email addresses, phone numbers and addresses are verified as capable of receiving messages and therefore improve the quality of the data even further. These capabilities are highly relevant for customer mastering.

Customer data mastering is achieved first by consistently and continuously integrating customer data across various enterprise sources to track the journey of the customer from lead to sale to after-sale service. This requires customer records across systems to be validated, matched and unified in a cluster, providing a golden record customer view and unique ID for persistent customer 360.*

Matching is important for detecting and rectifying duplication issues, or pinning/linking important data records that can then be merged if needed.

Combining these two data management disciplines can have a transformative impact on an organisation’s data maturity and help it climb up the curse towards Optimised & Governed, bringing a host of business benefits including:

  • Faster decision-making
  • Accessible, timely data
  • Profiling
  • Creation of a “Single Source Of Truth” the whole business can use

Experian’s Aperture Data Studio can help any size organisation get started with MDM and Data Quality. Complete your details below to find out more.


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