By Sam Johnson –
The English language has a deceptive air of simplicity. Take the sentence “I need a lift.” Depending on where you are, this innocuous sentence can take on different meanings. In North America, it could mean “I need a morale booster.” Across the pond, it would mean “I need a ride.” They are both correct. But depending on what side of the planet you live on, you could be either in need of a picker upper or a plain old car ride. What makes the meaning unambiguous is the context in which it is used. In this case, the context is geographic. My linguistic meandering on the different perspectives of a sentence is to shed some light on a key concept of Master Data Management (MDM) – a single version of the truth – and how it relates to big data.
Context is still King
Today’s Information Highway is choking with structured, semi-structured, and unstructured data. The Internet of Things (IoT) is exploding in popularity as companies exploit new ways to use sensor-generated data to digitally transform their business or to amplify existing systems. However, despite the frenzy of activity, many businesses are not sure as to how this information can be harnessed and integrated into existing systems. The context in which IoT data is used becomes very relevant to businesses wanting to gain value from these new capabilities. As a result, it becomes important to be able to harmonize big data with other data sources across the enterprise, both as it is generated and when it is analyzed.
At first blush, Master Data and big data might seem at odds with each other. Big data encompasses enormous amounts of data while Master Data governs a smaller universe. A large portion of big data is unstructured, whereas Master Data revolves around structured data. Big data shepherds external data from the cloud, IoT and other devices outside the confines of the corporation, whereas MDM systems deal with intrinsic data that is trusted and very valuable to it, such as customer data or product data. Shall the twain then ever meet? The answer lies in the context offered by big data and the trust offered by Master data.
The context provided by big data can enhance an organization’s Master Data Management. Nowhere is this more exemplified than with customer data. What was once a staid customer record with the usual name, phone number and address now comes alive with contextual information from big data about social media, likes, dislikes, and various other customer touch points. On the other hand, Master Data can be effectively used to gauge the trustworthiness of big data. Granted, it is easier said than done. But vendors are working on ways to effectively sniff out nuggets from the big data deluge that specifically relate to master data.
Big Data and Master Data enjoy a symbiotic relationship
This symbiotic relationship between big data and Master Data cannot be ignored. Big data provides a rich, contextual backdrop for Master Data while the latter ensures the trustworthiness of the former. They are both “joined at the hip” – a phrase, which, given the right context, would have the same meaning on both sides of the pond.
#IdeasRealized