Over last 12 years, I have seen Master Data Management help companies automate and improve data. It has helped companies take a strategic approach to managing data by removing processes that were mainly left manual and time-consuming for years.

We have seen an exponential increase in volume and variety of data in last 5-6 years. This change in data landscape has created new barriers to organizations looking to solve business challenges. It is no brainier that the data complexities will continue to increase and can be a significant hindrance to companies. The key to success lays in how quickly companies can turn big data into insights by leveraging technology available today. Machine learning is one such technology that is gaining momentum due to the pervasiveness of data and the seemingly infinite scalability of cloud-based compute power.

Machine Learning MDMThe manual processes for mastering, governing and stewardship of data just don’t hold up when data volumes grow exponentially. Whether you are looking to feed clean data to analytic or real-time applications, the key to timely decision making relies on how quickly you can automate processes.

I believe the silver lining for the executives is the machine learning and artificial intelligence.

When combined with data management, machine learning can accelerate and automate master data management. It can remove a lot of overhead by making stewardship activities and governance processes repeatable and scalable when a significant amount of source data is flowing into your MDM system.

While machine learning may not replace data analysts and other data management experts, the technology will make them significantly more productive by providing intelligent recommendations. This intelligence is a crucial step towards handling big data at scale and for accelerating delivery of data-driven insights.

What’s more? Machine learning can

  • Help in master data discovery (on-prem as well as cloud applications)
  • Recommend data cleansing rules based source data
  • Learn from stewardship behavior and create relevant survivorship rules
  • Automate tasks that are impossible to do at human scale such as anomaly detection
  • Detect variation in source data and suggest new rules to developers
  • Automate data cleansing, standardization, remodeling, and transformation processes
  • Enable system to make contextual and intelligent recommendations to business users

Organizations do not need a Big Data strategy; they need a business strategy that incorporates Big Data. – Bill Schmarzo 

MDM is transformational for companies, and machine learning can deliver just the right boost to help cement a competitive edge in the big data era. The possibilities are endless, but it all comes down to what you are trying to achieve with MDM and Big Data initiatives.

I love the recent quote I came across from Bill Schmarzo CTO, Dell EMC Services. Bill says – “Organizations do not need a Big Data strategy; they need a business strategy that incorporates Big Data.”

I believe that combining machine learning and MDM is the way forward. Share your thoughts, opinions about this via comments.