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Solving Data Quality Challenges with Tamr

You use Tamr projects to address data quality issues that result when siloed data is integrated from internal and external sources.

Tamr software automates core data preparation activities: combine, consolidate, and categorize. In an iterative process, it uses expert input to capture domain knowledge and assure accuracy, and then applies models to make the technology scalable.

To help you achieve different goals for your data, Tamr offers the following types of projects:

  • Schema mapping projects align disparate data sources to a unified schema, guided by recommended mappings.
  • Mastering projects match and de-duplicate records into clusters for mastered views of any entity. To complete the process of mastering data records, golden records projects use attributes in clustered data records to create unique, complete, up-to-date records for entities.
  • Categorization projects create a normalized view of data by applying a meaningful hierarchy to records.
  • Data enrichment projects (if enabled) use Tamr enrichment services to validate, standardize, and supplement your data.

You can then use the clean, unified data from one or more Tamr projects to power the analytics, data visualization, business intelligence, and other tools in use by your organization.

This Tamr Documentation set provides an overview of each project type.

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