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Partially Redacted: Data, AI, Security, and Privacy

Partially Redacted: Data, AI, Security, and Privacy

Technology

Data Access Control with lakeFS’s Adi Polak

Data Access Control with lakeFS’s Adi Polak

2023-05-03
Download

Data access control is becoming increasingly important as more and more sensitive data is being stored and processed by businesses and organizations. In this episode, the VP of Developer Experience at lakeFS, Adi Polak, joins to help define data access control and give examples of sensitive data that requires access control.

Adi also talks about the concept of role-based access control (RBAC), which differs from traditional access control methods and provides several advantages. The steps involved in implementing RBAC are discussed, as well as best practices and challenges. Real-world examples of RBAC implementation and success stories are provided, and lessons learned from RBAC implementation are shared.

We also discuss lakeFS, an open-source platform that provides a Git-like interface for managing data lakes. In particular, we get into the data management controls, the security and privacy features, and the future of the product.

Topics:

  • What are some common types of data access controls?
  • Why are these types of controls important?
  • How can RBAC help organizations better manage and secure their data?
  • What are some challenges in implementing effective data access controls?
  • How can organizations balance data security with the need to provide employees with the information they need to do their jobs?
  • What are some best practices for managing data access control?
  • How do you ensure that data access controls remain effective over time as your organization grows and changes?
  • What is lakeFS?
  • What model of data access management does lakeFS support?
  • What are some of the other privacy and security features of lakeFS?
  • What’s next for lakeFS? Anything you can share?
  • Where do you see data access control going in the next 5-10 years?

Resources:

  • lakeFS Roadmap
  • Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch
view more

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