From Master Data Management to Master Data Enablement

We’ve all heard the statistics: data practitioners, from analysts to data scientists, spend anywhere between 50% to 80% of their time cleaning and prepping data. And as a former practitioner, I’ve experienced the frustration of spending the bulk of my time on these tasks, not the value-added ones I was hired to do.

As a company’s data continues to grow, the task of keeping that data clean and enriched becomes more difficult and even more time-consuming. And what many organizations are finding is that their traditional methods of cleaning and mastering data using a rules-based approach no longer scale, nor are they cost-effective.

Time and time again, we’ve seen companies struggle to bring together multiple systems and data sources, both internal and external, and integrate them in a way that delivers value to the business. They lack both the right technology and the right data to truly accelerate their master data journey and reap meaningful business results. 

Technology + Data = Meaningful Results

This summer, Tamr announced our collaboration with Dun & Bradstreet to launch Master Data as a Service. We’re combining the world’s most powerful engine for continuous data mastering and the world’s most comprehensive business data and analytical insights into a joint solution that improves data quality and makes it more complete. 

Our joint solution is unique in that it allows companies to master critical data like customers or products without the heavy lift of a traditional master data management (MDM) project. Instead, our solution does the heavy lifting for you so that you can focus on the last mile of getting clean, accurate data.

How Dun & Bradstreet and Tamr Work Together

Think of it like putting your data mastering on autopilot. Here’s how it works.

You start by connecting your raw sources to Tamr. The data could be from a single source system or from multiple systems. We match this data to a Dun & Bradstreet D-U-N-S® number which allows you to enrich the data with greater insights. Using machine learning, Tamr creates clusters that help you to deduplicate the data and create mastered records. 

Over the past few months, we’ve been training Tamr’s machine learning models using Dun & Bradstreet data, so there is a high level of automation and confidence in the models. However, humans still have a role to play. By keeping humans in the loop, they can identify anomalies in the clusters to improve data quality even further. We also give you the ability to configure the confidence scores you’re willing to accept, so you’re only taking action on data that you trust.

This is game-changing, as it dramatically reduces the amount of time needed to get up and running – weeks, not months or years as in the past. As well, data practitioners need to spend less of their time cleaning and curating the data. Instead, these valuable resources can spend their time adding business value. 

This approach to data mastering also reduces cost. In the past, MDM projects required lots of time and lots of expensive technology. But through automation, today, mastering data is fast. And the technology needed to support it is more affordable. 

Manage Nuances, not Exceptions 

We see customers across the spectrum of maturity when it comes to data mastering. But for many organizations, they’re operating in a world of exceptions. And as their data changes, not only do the number of exceptions grow, but it becomes nearly impossible for their rules to keep up.

Machine learning alone can dramatically reduce the number of exceptions. But when you pair machine learning with the rich Dun & Bradstreet data set, that’s when the real magic happens. By training the model with the D&B data, organizations can shift their focus away from managing exceptions and instead managing nuances. Data experts can focus their time looking for major anomalies or biases, not exceptions that fall outside a set of predefined rules. 

We know that the master data journey hasn’t been easy for many organizations. When you combine the power of cloud-native, machine learning-driven data mastering from Tamr with external data enrichment through Dun & Bradstreet, you’ll enable your business to reap the promises of mastered data and use it to drive better, more insightful business decisions. It’s time we stop spending 50%+ of our time making our data usable and start reaping its benefits.

To learn more, I encourage you to listen to my conversation with Liz Barrette, from Dun & Bradstreet.