As a Distinguished Architect at Dun & Bradstreet it’s my job to understand how industry trends are impacting our customers and the solutions we offer them. Over the last few years there’s been no bigger trend than Big Data, and in the last decade it has gone from relative obscurity to what IDC estimates will be a 203 billion dollar market by 2020. While Big Data has clearly moved beyond just pure hype, I would assert that a significant percentage of organizations are not yet fully realizing the broadest possible benefits of their investments in Big Data. In fact, Gartner reports that the actual number of companies that have deployed big data in a production context is relatively small (13% of those engaging with it), with varying levels of success in application to business value.1 This gives overwhelming support to the idea that the vast majority of companies are struggling to derive insights and return on investment (ROI) from Big Data. I believe this ROI challenge is particularly acute for larger business-to-business (B2B) companies. One potential reason for this challenge is that many of these companies struggle with integrating their Big Data with the Master Data.
For many larger B2B companies, the key to unlocking customer insights captured in their Big Data environments is finding a way to connect untrusted and unstructured Big Data with highly trusted and structured customer/account master records, each with unique identifiers, sitting in their Master Data Management (MDM) hubs. On the surface, making this connection may appear to require a tradeoff most CIO’s would be unwilling to make: sacrifice the quality and trust inherent to a fully governed master data environment by allowing potentially billions of rows of un-mastered data into their MDM hubs, or spend millions of dollars trying to apply more governance into an environment completely ill-suited to support it.
Software vendors in both the MDM and Big Data worlds would have you believe they’ve solved for the problem of allowing for governance of enterprise Master Data in Big Data environments, but, in reality these solutions are completely separate applications as compared to what most organizations are already using for MDM. If the goal of MDM is to have a single trusted source of Master Data, implementing a completely separate application to manage and govern Master Data in a Big Data environment would seem to defeat the primary purpose of MDM.
So, does the fact MDM and Big Data environments remain completely distinct infrastructures mean that B2B companies who rely on structured master customer data will struggle to realize the full value of their investments in Big Data? This question is explored in much greater detail in a recently published whitepaper, which you can download below.