Smarter insights, cleaner data, better connections—discover the latest Tamr updates designed to enrich customer data, boost data quality, and improve usability.

Understanding the differences between AI-native MDM and AI-enhanced MDM is critical to choosing the right solution. Discover what makes AI-native MDM stand out.

Persistent identifiers provide a holistic view of entities across multiple data sources. See why a Tamr ID is critical for successful master data management.

Business cases for AI-native MDM need more than a list of technical features. They must also demonstrate real business value. Learn more in our how-to guide.

First-party data is collected by an organization about its audience, while third-party data is collected by external entities. Both are valuable for data analysis and decision-making.

Data enrichment improves data quality by enhancing existing, internal datasets with information from reputable, generally external sources. Learn more.

Connecting people, accounts, and interactions in B2C data uncovers revenue-generating and risk-mitigating opportunities. See how Tamr’s AI-native MDM can help.

Overcoming manual processes and fragmented data sources is critical to increase effectiveness of KYC programs. Discover how AI-driven entity resolution helps.

From hallucinations and false predictions to misleading correlations, faulty AI insights can fool you into making bad decisions. See how AI-native MDM can help.

AI-native MDM delivers accurate, consistent Customer 360 views that build trust, power personalization, and drive business success. See how it works.

Give your data a deep cleaning to clear the clutter and ensure critical entities are accurate, complete, up-to-date. Discover five ways to improve data quality.

From AI agents and technology investments to AI literacy and trustworthy data, explore five key themes from the 2025 Gartner Data & Analytics Summit. Read more.

Discover what makes Tamr AI-native and how the use of AI, at the core of the platform, is disrupting the MDM category, which has traditionally relied on rules.

Mizuho and AMN Healthcare reveal six lessons learned on their MDM journeys. Read to understand common pitfalls and how AI-native MDM helps you to overcome them.

Increasing the number of women in data-related careers is an industry imperative. Discover how to inspire the next generation of women in data.

Enhance data quality with 5 techniques: format standardization, filling missing values, deduplication, error correction, and outlier handling using data products.

Discover how AI-powered semantic search, integrated into MDM, provides the context needed to match data entities reliably and at scale.

From entity resolution and data governance to data quality, discovery, and integration, learn how AI helps data leaders improve master data management.

Learn what entity resolution is, why it’s important, and how businesses can use AI to reduce duplicates, improve data quality, and produce golden records.

Celebrate Valentine's Day by nurturing your data with these 5 love languages. Learn how to show your data you care for improved data quality and a data-driven culture.

Discover how AI, data quality, and entity resolution are reshaping data science. Explore key trends and insights in our blog post.