Unified Data Migration: How it Works

Migrating your data to new software is like moving to a new house. You don’t just throw everything into the truck. You take stock of what you have. You decide what to keep and what to donate. And you clean. You want to start fresh and get the most out of the new place.

That’s the role played by Tamr’s data unification and cleaning services during a migration. You want to impress and empower your users, especially those who will touch the new system all day long. Plus, the system’s everyday users can contribute their expertise to Tamr Unify’s machine learning algorithms, so the users feel invested in the result.

Unifying and cleaning your data during a migration sounds like making a hard project harder, but the moving analogy holds: you’ve already set aside the time to touch everything in your house and the money to ship it. Likewise, for your software migration, the database designers and data engineers are already assembled. Tamr works with these teams to find new relationships in your data, endow the new system with reliable results, and develop a repeatable process to keep it that way.

Case Study: Auto Sales and Service

For these reasons, when a major automaker migrated their customer, vehicle, and company contract data to Salesforce, they turned to Tamr. Working with an integration partner, Tamr ensured the new Salesforce instances were trustworthy and clean. Tamr consolidated customer data volume by 55% by clustering together records that represent the same person. Vehicle and company records were consolidated 44%.

Tamr Dedup Results

How it Works

Tamr Unify builds these clusters of records by first identifying pairs of records that represent the same entity. For example, the same vehicle may appear with multiple owners, or the same company many appear with multiple shipping addresses. Because Unify is a machine learning solution, it presents your CRM experts with pairs of customer records where it needs the most guidance to determine similarity, and it asks the experts a single question: “match” or “no match”? When accuracy reaches a target level, the experts are done.

This process dramatically reduces the time and technical resources required to get to business-ready data, and it improves the quality of results by tightly integrating data consumers and experts into the process.

Tamr’s Professional Services team works with your data engineers to integrate Unify into your migration pipelines. In Unify, a schema mapping interface is available that makes it easy to map old columns to new columns, apply cleansing and validation transformations, and preserve the original data for provenance.

Move-in Ready

A system like Salesforce has to look good on day one. In the case of the automaker, Tamr’s continual touchpoints with data engineers and CRM users ensured everyone felt like they contributed to its success. In the moving analogy, it’s as if everyone loves the new layout and decor, because everyone played a role in the transition.

With Tamr’s help, the automaker unified and mastered seven customer sources, three vehicle sources, and three company sources into the Salesforce instance, in six months. This success encouraged the automaker to clean and consolidate other sales and marketing systems with Unify, building a personalized experience for each customer. In this way, unifying your data with Tamr during a migration amplifies the productivity and possibilities in its new home.

To learn more about Tamr’s data migration services, download our full white paper, Migration, Unified, below. And as always, please contact us with any questions or request a demo to see Tamr’s Unify solution in action.

Migration, Unified

Whitepaper

The process of migrating your data to new software is a lot like moving into a new house: you want to consolidate and clean. That’s the role played by Tamr’s data unification and cleaning services during a migration.

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As the Federal Field Engineer for Tamr, Harlan Kadish deploys precise and performant machine learning solutions to unify data from a variety of sources, to make government and industry more efficient and our nation more secure. Previously, he built and optimized data pipelines for the largest enterprises in the world. His mathematics research at Texas A&M University and the University of Michigan concerned the relationships between algebra, geometry, and computational complexity.