The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Data Governance for Data Science with Adam Wood - #578
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Jun 13, 2022 
In this engaging conversation, Adam Wood, Director of Data Governance and Data Quality at Mastercard, shares his insights into the complexities of data governance on a global scale. He discusses the challenges of navigating regional regulations like GDPR and the importance of metadata management. Adam highlights the role of feature stores in data lineage and emphasizes the need to mitigate bias in data science. Moreover, he sheds light on investments in tools that enhance data quality and collaboration within data science teams.
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Amazon's GDPR Fine
- Amazon was fined $898 million for using data in data science projects without explicit user consent, highlighting the importance of clear consent practices.
- This emphasizes the need for companies to adhere to privacy regulations like GDPR and obtain proper consent for data usage.
Automated Governance Processes
- Implement highly automated and scalable governance processes to manage consent and privacy standards.
- Leverage data cataloging tools to track metadata, policies, and consent, ensuring compliance with evolving regulations.
Data Nationalism and Federation
- Data nationalism, with varying regulations across countries, introduces complexity in data governance.
- Federated learning, training models locally and building them centrally, addresses challenges posed by data localization requirements.