Data Governance for Data Science with Adam Wood

EPISODE 578
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About this Episode

Today we’re joined by Adam Wood, Director of Data Governance and Data Quality at Mastercard. In our conversation with Adam, we explore the challenges that come along with data governance at a global scale, including dealing with regional regulations like GDPR and federating records at scale. We discuss the role of feature stores in keeping track of data lineage and how Adam and his team have dealt with the challenges of metadata management, how large organizations like Mastercard are dealing with enabling feature reuse, and the steps they take to alleviate bias, especially in scenarios like acquisitions. Finally, we explore data quality for data science and why Adam sees it as an encouraging area of growth within the company, as well as the investments they’ve made in tooling around data management, catalog, feature management, and more.

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Thanks to our sponsor Cloudera

Cloudera's Hybrid Data Platform offers a single, unified platform to power data and machine learning workflows across any private, public, multi, or hybrid-cloud deployment. CDP Machine Learning helps organizations build, deploy, and scale ML and AI applications through a repeatable, industrialized approach that streamlines the process of getting analytic workloads into production and intelligently manages machine learning use cases across the business, at scale. CDP Machine Learning lets enterprise data science teams collaborate across the full data lifecycle–with immediate access to enterprise data pipelines, scalable compute resources, and their preferred tools–without compromising the agility, security, and governance needs of the business.

To learn more about what the company is up to and how they can help, visit Cloudera’s Machine Learning resource center at cloudera.com/ml!

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