Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera


March 27th, 2022

1 hr 2 mins 35 secs

Your Host

About this Episode


Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor. Privacera is an enterprise grade solution for cloud and hybrid data governance built on top of the robust and battle tested Apache Ranger project. In this episode Balaji Ganesan shares how his experiences building and maintaining Ranger in previous roles helped him understand the needs of organizations and engineers as they define and evolve their data governance policies and practices.


  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
  • This episode is brought to you by Acryl Data, the company behind DataHub, the leading developer-friendly data catalog for the modern data stack. Open Source DataHub is running in production at several companies like Peloton, Optum, Udemy, Zynga and others. Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at
  • RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at
  • The most important piece of any data project is the data itself, which is why it is critical that your data source is high quality. PostHog is your all-in-one product analytics suite including product analysis, user funnels, feature flags, experimentation, and it’s open source so you can host it yourself or let them do it for you! You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms. Give it a try today with their generous free tier at
  • Your host is Tobias Macey and today I’m interviewing Balaji Ganesan about his work at Privacera and his view on the state of data governance, access control, and security in the cloud


  • Introduction
  • How did you get involved in the area of data management?
  • Can you describe what Privacera is and the story behind it?
  • What is your working definition of "data governance" and how does that influence your product focus and priorities?
  • What are some of the lessons that you learned from your work on Apache Ranger that helped with your efforts at Privacera?
  • How would you characterize your position in the market for data governance/data security tools?
  • What are the unique constraints and challenges that come into play when managing data in cloud platforms?
  • Can you explain how the Privacera platform is architected?
    • How have the design and goals of the system changed or evolved since you started working on it?
  • What is the workflow for an operator integrating Privacera into a data platform?
    • How do you provide feedback to users about the level of coverage for discovered data assets?
  • How does Privacera fit into the workflow of the different personas working with data?
    • What are some of the security and privacy controls that Privacera introduces?
  • How do you mitigate the potential for anyone to bypass Privacera’s controls by interacting directly with the underlying systems?
  • What are the most interesting, innovative, or unexpected ways that you have seen Privacera used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on Privacera?
  • When is Privacera the wrong choice?
  • What do you have planned for the future of Privacera?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

  • Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
  • If you’ve learned something or tried out a project from the show then tell us about it! Email with your story.
  • To help other people find the show please leave a review on iTunes and tell your friends and co-workers


The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast