Why? Because MDM gives companies the context and trust they need to drive insight—and, ultimately, actions—from the Big Data they’re mining and analyzing.

HOW BIG DATA DISRUPTED A “DISRUPTOR”

Master Data Management is defined as a “comprehensive method of enabling an enterprise to link all of its critical data to one […] master file that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments. In addition, MDM can facilitate computing in multiple system architectures, platforms, and applications.”

MDM aims to use one master file as a single source of truth which brings full value to operational and analytical data inside the business.

That’s not as easy as it sounds, with all the impacts that acquisitions, mergers, organic growth and business change bring to customer, product, supplier/vendor and site data. And most companies were just beginning to adjust to the concept of a disciplined MDM approach when a new disruptive technology, Big Data, came along.

Big Data is a broad term for data sets so large or complex that they’re difficult to process using traditional applications. It affects multiple data science disciplines: data management (capture, aggregation, storage, curation, sharing, security), visualization (querying) and analysis.

In other words, MDM is a method; Big Data is a term, a concept. That’s an important distinction.

• Big Data management allows companies to handle the three “V’s” of data (Volume, Velocity and Variety) in a cost-effective, scalable manner when their data stretches the boundaries of traditional database platforms. “How are my equipment and buildings performing across the world?” or “What are people saying about my company, products and services on social media?” are some questions Big Data analysis can answer that go beyond what internal enterprise systems can.

• MDM is a foundation for answering those questions. It also helps you move to the next level: determining courses of action that improve business performance, customer satisfaction, market share and profitability.

CONTEXT AND INTEGRITY: ESSENTIAL TO BIG DATA ANALYTICS

New technology comes with a learning curve. These days, many companies are trying to understand how they can drive value from Big Data analytics. What’s more is that massive amounts of information are flooding their databases—but should it flow into their data lake, or down the drain?

Companies need to focus on context. All data analysis requires context to transform data into meaningful information. And that’s the value that master data and MDM can offer: a frame of reference, a way of determining relationships and setting high-level priorities. It’s this contextual view that can transform insight into powerful, actionable information.

Trustworthiness may even be more important than context. Errors and inconsistencies in data, and information silos, lead to faulty analysis and ill-conceived action. MDM exists to minimize those issues, and offer greater data integrity and a basis for master data, that single source of truth.

In the meantime, ask yourself:

Have I considered MDM as part of my Big Data strategy? How can an integrated MDM/Big Data initiative improve my business performance?