Rapid, Unified Views Of Any Entity

While traditional data integration solutions focus on top-down, rules-based methods to integrate and clean disparate, dirty datasets, Tamr delivers a bottoms-up, machine learning-based approach. This enables the rapid construction of unified views of any entity–from customers to suppliers to products to clinical trials. The platform’s core capabilities include:

  • Connecting data sources across an organization to align relevant datasets to a unified schema;
  • Cleaning the unified dataset through entity deduplication and mastering; and,
  • Classifying records within the clean, unified dataset to a client-provided taxonomy for more robust downstream analysis.

Learn more about how Tamr is enabling customers to achieve transformative outcomes.


Connect: Align Your Datasets Into A Unified Schema

Within the “connect” phase, Tamr aligns all relevant source dataset attributes to a unified schema that is most effective and relevant for project goals. Human-guided machine learning is employed to union these datasets and offers a significant improvement in speed and scale as compared to traditional methods that rely on developers creating hard-coded rules.

Clean: Identify Unique Entities Within The Unified Dataset

Tamr’s “clean” phase deduplicates and masters the entities within the unified dataset.  The platform automates this challenge with machine learning and ensures high levels of accuracy by capturing and incorporating the expertise of data stewards. The core output of this phase is a pipeline that delivers a unified dataset containing mastered entities to feed downstream analytical and operational uses.

Classify: Categorize The Unified Dataset Records To Any Taxonomy

Once a clean, unified dataset of a particular entity has been produced by Tamr, the user has the option of “classifying” the records to a company-specific or commonly used taxonomy for more in-depth analytic capabilities downstream. Tamr’s classify phase operates in the same manner as the connecting and cleaning phases do, leveraging the product’s unique blend of human-guided machine learning to rapidly and accurately categorize records to the deepest levels of a provided taxonomy.