Monday Morning Data Chat
#149 - Why is Data Security so Hard? w/ Yoav Cohen
Nov 1, 2023
Yoav Cohen, co-founder & CTO at Satori, discusses the challenges of data security, strategies for dealing with analytics over sensitive data, compliance requirements for data teams, and the importance of data engineers as security engineers. They also dive into the concept of the death of big data, the process of data masking, and the importance of adaptability in the data domain.
58:55
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Quick takeaways
- Advancements like Databricks' Unity Catalog simplify data security by focusing on securing tables and views, removing the need for separate security models for each data manifestation.
- Organizational approaches to data security have shifted towards distributing ownership of data stewardship, empowering teams to approve data access based on their knowledge and fostering a sense of responsibility.
Deep dives
The challenge of securing data in the data lake or lake house
Securing data in a data lake or lake house presents challenges due to the different manifestations of data. Historically, organizations had to manage security for each manifestation, such as raw files and tables in the query tool, which required different security models. However, advancements like Databricks' Unity Catalog are simplifying this by focusing on securing tables and views, removing the need to provision access to the underlying files separately. This convergence around a SQL-like model is beneficial for standardization and simplification.
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