Simplify Data Security For Sensitive Inf...

Summary

The best way to make sure that you don’t leak sensitive data is to never have it in the first place. The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems. In this episode Sean Falconer explains the idea of a data privacy vault and how this new architectural element can drastically reduce the potential for making a mistake with how you manage regulated or personally identifiable information.

Announcements

• Hello and welcome to the Data Engineering Podcast, the show about modern data management
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• Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. By the time errors have made their way into production, it’s often too late and damage is done. Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production. No more shipping and praying, you can now know exactly what will change in your database! Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold.
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• Your host is Tobias Macey and today I’m interviewing Sean Falconer about the idea of a data privacy vault and how the Skyflow team are working to make it turn-key

Interview

• Introduction
• How did you get involved in the area of data management?
• Can you describe what Skyflow is and the story behind it?
• What is a "data privacy vault" and how does it differ from strategies such as privacy engineering or existing data governance patterns?
• What are the primary use cases and capabilities that you are focused on solving for with Skyflow?
  • Who is the target customer for Skyflow (e.g. how does it enter an organization)?
• How is the Skyflow platform architected?
  • How have the design and goals of the system changed or evolved over time?
• Can you describe the process of integrating with Skyflow at the application level?
• For organizations that are building analytical capabilities on top of the data managed in their applications, what are the interactions with Skyflow at each of the stages in the data lifecycle?
• One of the perennial problems with distributed systems is the challenge of joining data across machine boundaries. How do you mitigate that problem?
• On your website there are different "vaults" advertised in the form of healthcare, fintech, and PII. What are the different requirements across each of those problem domains?
  • What are the commonalities?
• As a relatively new company in an emerging product category, what are some of the customer education challenges that you are facing?
• What are the most interesting, innovative, or unexpected ways that you have seen Skyflow used?
• What are the most interesting, unexpected, or challenging lessons that you have learned while working on Skyflow?
• When is Skyflow the wrong choice?
• What do you have planned for the future of Skyflow?

Contact Info

• LinkedIn
• @seanfalconer on Twitter
• Website

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.
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Links

• Skyflow
• Privacy Engineering
• Data Governance
• Homomorphic Encryption
• Polymorphic Encryption

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