The CDO's Guide to Data Mastering at Scale

 

As a new Chief Data Officer, you recognize that the way enterprises have been managing their data through traditional Master Data Management (MDM) is a dated process. And while MDM might have worked well for data mastering challenges that existed 15 years ago when the solution came about, today’s data challenges require a different approach.

This guide is your resource for Data Mastering at scale, exploring topics such as: 

  • Why traditional approaches to data mastering, such as MDM and ETL, don't scale

  • The benefits of Agile Data Mastering and why this approach offers a more effective solution

  • Why modern data mastering challenges require both machine learning and human expertise

What are the key areas of focus for the modern CDO? Download this guide to find out.

 

 

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Reference data management refers to the hundreds of high-quality data sources available to financial institutions in order to enrich customer information. This data is used for various purposes — from maintaining more complete records to evaluating risk and monitoring market trends. Although 90% of institutions already use external sources to enrich customer data, 85% of these organizations are apprehensive of bringing in new sources and systems for two primary reasons — speed of implementation and accuracy.

During this webinar, we’ll discuss:

  • The role of reference data in regulation and compliance
  • How to integrate reference data into your organization’s KYC program
  • Why accurate counter-party identification and risk assessment requires external data
  • How to use machine learning to leverage accurate reference data quickly, at scale
  • Steps to consider when preparing for mergers & acquisitions
  • How to mitigate risk and reduce costs by improving vendor intelligence

About the Author

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Andy Palmer
CEO and Co-Founder at Tamr

Andy Palmer specializes in founding and accelerating the growth of innovative technology organizations. During his career as an entrepreneur, Andy has served as founding investor, Board of Directors member or advisor to more than 50 start-up companies across a variety of industries – a number of them engaged in solving big data challenges for customers.  Most recently, he co-founded Tamr with renowned database researcher Michael Stonebraker, PhD. Tamr enables enterprises to connect and leverage all their data, and is backed by more than $16 million in financing led by Google Ventures and New Enterprise Associates.