For decades, organizations have been using Master Data Management (MDM) solutions to ensure that all data records have a single, authoritative version of truth, regardless of where the data comes from.
As more organizations look to leverage data as an asset, however, the limitations of traditional MDM solutions have become a pressing challenge. Traditional MDM solutions solve the data mastering problem using deterministic, rule-based approaches that do not easily accommodate the increasing flow of messy, diverse data that comes from disparate data systems.
This paper will:
- Explore Tamr’s agile, machine learning approach to data mastering
- Explain how human-guided machine learning removes IT and data resource bottlenecks
- Show how agile data mastering enables organizations to overcome the challenges of MDM solutions to accelerate their digital transformation