Master Data Management: Taking data from ‘valuable’ to ‘invaluable’

Master Data Management (MDM) is undoubtedly one of the most powerful tools you can have in your business toolkit today. It allows enterprises to gain a single view (or ‘single version of truth’) of the data held across the organization and use this to materially improve processes and decision making, in turn helping meet growth, efficiency and cost aims. And that helps you take data from a valuable business asset to an invaluable one.
Businesses know that it’s time to get off the fence, when it comes to tackling data in an organized, trusted and value-adding way. As the deluge of data created and stored shows no sign of abating, it has never been more important to hone a solid MDM approach, establish the process and governance that will guide it, and commit. That’s why Capgemini shone a light on MDM at the recent IBM Insight event, sharing our perspectives on how and where to get started with MDM—and achieve those tangible business gains, fast.
Alongside partner IBM®, we shared our MDM Proof of Concept (PoC) approach, which we have mobilized for a major investment bank, helping it jumpstart the build and implementation of their MDM system, with IBM. When facing the complex task of establishing MDM in an organization, our PoC is a powerful way of getting it right, because it draws upon pre-defined use cases and scenarios, proven IBM technologies and tested Capgemini solution architecture and tests it through simulations and scoring, analyzing results and drawing conclusions, to make sure that the solution and set up is truly fit for purpose.
Differing business models, regulatory requirements, growth objectives and the existing enterprise technology landscape all demand a joined up and informed approach to MDM. Today, when faced with myriad technology options for managing and using data, it is vital to look at the bigger picture of your organization’s business needs and operational parameters.
The technology is there to make data an invaluable business asset—but one size does not necessarily fit all.

Related Posts

AI and analytics

Spotlight on Capgemini NA @ Informatica World 2018 | May 21–24 in Las Vegas

Jackson, Dusty
July 10, 2018
Spotlight on Capgemini NA @INFA World 2018 with key representation from Dusty Jackson, Scott Sweet, Keith Reid, Steve Jones, Goutham Belliappa and Mansoor Aleem
Consumer Analytics

Bullwhip effect applied to a data supply chain

Denis Sproten
June 22, 2018
Take a look at how the bullwhip effect translates into the data supply chain built for your organization.
Artificial Intelligence

Even the artificial intelligence you buy is prejudiced

Reinoud Kaasschieter
June 21, 2018
When wrong data is fed into the algorithms, they also make the wrong decisions. Learn why do bots contain biases.

By continuing to navigate on this website, you accept the use of cookies.

For more information and to change the setting of cookies on your computer, please read our Privacy Policy.


Close cookie information