What is Master Data?
We talk about master data a lot here at HICX, but we appreciate that sometimes it’s necessary to take a step back and think about this subject from the point of view of someone who doesn’t spend their entire day wading through pools of data.
Master data, as you’d probably expect, refers to the key bits of information that are used in many different business processes. In other words, the data that many organisations simply wouldn’t be able to function well without.
Gartner’s master data definition refers to it 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.”
Why is master data management (MDM) important?
Given the changeable nature and high volume of information you’re working with in order to do your job, it stands to reason that this data in isolation isn’t going to give you the competitive edge you need in order to succeed.
You don’t just need high-quality data. You also need an effective way to govern how that master data is managed. Otherwise, what’s the point of having the information if you can’t use it? This is where master data management comes into play.
Picture a bookcase, on which you have your collection of rare first editions, collected over many years. Every time you get a new one, you simply put it straight on a shelf in any space that’s available.
What you’ll end up with is an undeniably high-quality collection of attributes, but one without any order or structure. If you want to find a particular book quickly, you’ll have to check along every shelf until you come across it. Doing this every time you want to find one is not an efficient process.
However, if you were to sort and segment them alphabetically, the process becomes far easier. Now all you need to do is check the part of the bookcase you know the book will be in. Of course, you can also choose to segment your books in different ways – by title, author or genre, for example – using whichever methodology best suits your needs.
Putting in a place a logical and defined structure not only allows you to find what you need when you need it – it also makes it far easier to manage and govern going forward.
Defining your master data management strategy
The steps you need to go through in order to define your master data management strategy include:
- Data governance
- Data migration
- Data cleansing
The first two steps – governance and migration – involve defining your data standards, and then putting in place the master data management tools required to transform your data so that it reaches the standards you’ve just defined.
Going back to the analogy above, you need to check that any books you add to the collection are indeed first editions. Otherwise you risk watering down the quality of your collection, which defeats the objective.
This is where governance comes into play – ensuring that the quality of anything you add is high enough to justify its inclusion. The same goes for master data governance; you need to be sure that the data you’re adding is of a high quality.
Finally, once you’ve completed the above steps, you’ll be able to cleanse the data you already have to meet your newly-defined standards, which includes consolidation, de-duplication and so on.
To get more insights into master data management and governance, take a look through some of our other resources below: