Most organizations continue to struggle with customer data quality, resulting in the latest and greatest customer analytic tools and operational systems being fed with bad data. Read how customer mastering fixes these core problems and accelerates performance.
Learn why traditional MDM systems don’t scale to meet the needs of large, multinational financial institutions.
This guide outlines the steps needed to tackle one of Big Data’s more elusive components—data variety—to enable real-time access to accurate information across your organization.
Tamr’s Real World Evidence Integration Solution tackles the data challenge with a powerful data harmonization process that streamlines real world evidence integration for large volumes of disparate data to deliver transformational outcomes.
In this report, five data industry thought leaders explore DataOps—the automated, process-oriented methodology for delivering clean, reliable data across your organization.
Download this white paper to learn how Tamr uses machine learning to help organizations build a data-driven approach to taxonomy design.
Tamr’s CDISC Conversion Solution tackles data challenges with a powerful data harmonization process, driven by human-guided machine learning that can replace traditional in-house tools prone to delays and errors.
When it comes to data quality and availability, there is a gap between expectations and reality. Download this ebook to learn how Agile Data Mastering can solve common data challenges.
What exactly is machine learning? And, more importantly, what are its applications for common challenges that enterprises encounter with Big Data?
What is data stewardship and what are the areas where machine learning can help data stewards? Download our guide to machine learning to find out.
In this chapter from the book Making Databases Work: The Pragmatic Wisdom of Michael Stonebraker, Ihab Ilyas discusses the academic project that eventually become Tamr.