By including master data management as a part of your data governance strategy, any data related ambiguity or risks can be mitigated. This blog tells us why master data management is important and should be a part of your data governance strategy.
“Abundance is our future.” – Peter Diamandis
In his TED Talk, Diamandis – founder and chairman of the X Prize Foundation – spoke about how, “Every second of every day, our senses bring in way too much data than we can possibly process in our brains.” He might as well have been talking of modern organizations and their hunger for capturing every bit of data as they try to deliver greater value to customers and shareholders.
Think about it for a second. The business world processes quintillions of bytes a day, and that’s a figure that’s constantly climbing. This data is not falling into an infinite pool; instead, every day, millions of professionals like you all over the world are playing your roles keeping the engine moving.
Data centers count among organizations’ most valuable assets because they contain not only the records of everything they’ve ever done, but also the key to everything they ever will.K
Keeping up with the Joneses, Inc.
There are two types of organizations in the world now – the ones that can handle the data they collect, and the ones that will collapse because they can’t.
It’s almost a given certainty that the former will have a culture of dynamic data governance, keeping themselves agile, ready to scale up or across as needed. The latter ones that are unable to keep up with the data that’s being channeled to them will fall behind, unable to derive neither value nor validation from it. Drill deep enough, and you will see that it boils down to one essential indicator.
Successful organizations are those that will have mastered the art of master data management. The others are the ones that haven’t.
Why is master data management (MDM) important?
Master data is your purest form of data, the bytes that cannot be (or at least should not be) broken down into smaller, simpler datapoints.
Think of your customers, the core products or services that you sell, the rate-cards and transactions you have built your business streams around. These records might be used in multiple databases and/or contexts across your organization, but the last thing you want, for instance, is for your data to consider the same client as two different entities.
Master data management is what helps you keep your data straight and avoid such ambiguities. As organizations evolve and grow, it is essential that there is discipline where your data is concerned. It gives your system architects a stable reference point to build from and fall back on. It is your last resort against fallible validation techniques, injection exploits and extract-transform-load (ETL) errors.
Why do you need MDM?
It is not the size of the organization that determines the need for master data management within its data governance policies. In fact, there is a case to be made for data governance and the purpose of master data management in any company that deals with even the bare minimum of data about its products, people or processes. However, in certain situations, like the ones given below, master data management really shows returns on investment and effort:
1. Multi-national expansion
Organizations extending their operations to foreign shores have to deal with data formats that are localized, such as currency, date, even location. If designed properly, the master data can still be used to act as the skeleton for enterprise-wide use and analysis, reducing – if not eliminating completely – the possibility of errors.
2. Mergers and acquisitions
When two organizations become one, the master data of each can be used to set reference points to unify the data systems as well. It simplifies what can otherwise be a gargantuan exercise in finding, matching and equating.
3. Migration / Upgradation
Moving from one system (for instance, legacy systems like mainframe) to another (say, the cloud) can be fraught with risks even with well-planned migrations. Without master data sets, it will nearly be impossible to ensure that column-level integrity is maintained during the move.
One of the biggest risks for an organization is when key personnel leave, taking their knowledge with them. Master data management mitigates this risk by documenting the master data in detail, including not only its structure but also the various ways in which it can be used or adapted.
What exactly is master data? How is it stored or transmitted?
In the next edition of this three-part series, we’ll discuss the various kinds of master data. We’ll also get into how master data can be stored, how they’re transmitted, before we delve into MDM strategy in part three.
Come back for more.