Gartner has recognized Tamr for the first time in its Magic Quadrant for Master Data Management! We believe this is a strong indicator that the market is ready to embrace a modern, augmented approach to master data management. Inclusion in the Magic Quadrant is a reflection of the success we’ve had making customers successful with our approach & filling the unmet needs of Master Data Management.
The goal when starting Tamr almost 10 years ago wasn’t simply to build a better master data management solution. Mike Stonebraker and his research team at MIT recognized that companies were struggling to get value out of their data because it was trapped in disconnected silos that required herculean efforts to integrate.
By focusing on the customer problem rather than the category, our approach is different from our peers in the industry. When you have data coming from many sources, it is an impossible data integration challenge. Legacy MDM tools have tried to overwhelm it with human effort — people to create governance rules, people to create match rules, people to manually review exceptions & steward the data, and people to continuously revise the process as new data is introduced.
If every business leader wants their company to be data-driven, but few have realized this goal, something needs to change. Companies have been burned in the past by MDM, but now is the time for a fresh approach based on modern technology. The landscape is completely different than when legacy solutions established themselves:
Big data is no longer the primary problem. We have nearly unlimited storage and compute resources available inexpensively in the cloud.
Innovation is no longer limited to a few big vendors. Your MDM vendor doesn’t need to also be your ETL vendor and your data warehouse. Best-of-breed works.
Every business is a data business. Your IT department cannot prepare data in a silo and expect broad adoption when so many functional managers are data hungry.
What hasn’t changed? Clean, curated, and comprehensive data is still the cornerstone of every digital initiative.
Our modern approach to Master Data Management addresses this need from first principles, taking advantage of the benefits of key innovations over the last 5-10 years. The four primary elements of that approach are:
1. Machine learning does the heavy lifting
As Gartner asserts in the Magic Quadrant, “By 2025, 50% of CDOs will achieve digital acceleration goals using augmented data management practices across MDM, data hubs, data quality and integration.” We’ve pioneered the concept for the category, as demonstrated by over a dozen patents.
We believe that machine learning isn’t something you can simply bolt-on at the end to inform how humans write rules. Instead, it needs to be at the foundation of any modern data mastering solution. Without this shift, humans will always be the bottleneck, needing to constantly review outputs & revise rules.
Humans should be used to guide the machine, and build trust in the data through ‘bottom-up’ feedback, not build ‘top-down’ rules that ignore the context of how data is being consumed. Data leaders can’t compromise on this point if they want to get different results than they have been from MDM.
2. Built for the Cloud
It’s not enough to simply be able to execute an MDM solution in the cloud. A modern MDM solution needs to be tightly integrated with the underlying componentry of the cloud providers to ensure that, as more workloads move to the cloud, the elasticity of the cloud is fully utilized. The reason for this is simple: scale.
We’ve built Tamr cloud-natively on GCP, AWS, and Azure to support data leaders’ need for flexibility and scalability as they rebuild their data architecture with the cloud at the center. We’ve also partnered closely with those three cloud providers and SAP & Snowflake to ensure that Tamr is tightly integrated with the systems creating and managing a business’s most important data assets. It’s essential for a modern MDM solution to not only recognize where the critical mass of data is headed, but also embrace it, and not try to become yet another data silo.
3. Enrichment is a must-have
One of the biggest reasons that legacy MDM solutions aren’t known for delivering clean, curated, and comprehensive data is because the best data – whether it’s customers, suppliers, or parts – often lives outside of the company’s four walls. For example, when GitHub gets acquired by Microsoft or VMWare is spun out of EMC Dell, should it be the job of every data steward to manually update their MDM with this information? Of course not.
Tamr has native capabilities to connect to a library of enrichment services that we’ve developed through a mix of third-party integrations and our own first-party datasets. This simplifies the process of bringing external data into the mastering process to a few clicks.
4. Real-time required
Finally, a modern MDM solution needs to keep pace with today’s business requirements. That means real-time reading and writing of master data. Open-source technologies like Kafka have made streaming data a commodity. Real-time MDM is about much more than that. It requires a machine-first approach so that there are no human bottlenecks anywhere in the pipeline. After all, if you’re just streaming garbage in & out, what’s the point?
Ready to see what a modern MDM solution can do for you?
Master Data Management is the cornerstone of a digital transformation. More importantly, a modern approach to MDM is essential to realize the value promised by the category.