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Shinji Kim, CEO of Select Star, shares her expertise in data management and governance after leading innovative projects at major tech firms. She discusses the challenges of data discoverability and how to document datasets effectively. The conversation highlights the importance of bridging communication between data and business teams to boost revenue. Shinji also explores the role of AI in streamlining data governance and enhancing documentation for clarity. Her insights provide a roadmap for organizations striving to harness their data efficiently.
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Quick takeaways
- Data governance is essential for organizations to protect privacy and ensure data is organized, accessible, and compliant with regulations like GDPR.
- Effective management of data quality requires identifying critical datasets, maintaining their integrity, and promoting knowledge-sharing to optimize resource allocation.
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Importance of Data Governance
Data governance has become increasingly significant due to the rise of generative AI and the need for organizations to comply with data privacy regulations like GDPR and CCPA. Effective governance not only protects individuals' privacy and confidential data but also ensures that data is organized and accessible for analysis. As enterprises strive to leverage their data, a well-structured governance framework allows data analysts and scientists to access the right datasets and utilize them effectively. This shift towards improved governance reflects a broader trend of transitioning from simple data collection to comprehensive data utilization across organizations.
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