Data Engineering Podcast

This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

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Aligning Data Security With Business Productivity To Deploy Analytics Safely And At Speed

Summary

As with all aspects of technology, security is a critical element of data applications, and the different controls can be at cross purposes with productivity. In this episode Yoav Cohen from Satori shares his experiences as a practitioner in the space of data security and how to align with the needs of engineers and business users. He also explains why data security is distinct from application security and some methods for reducing the challenge of working across different data systems.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management
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Your host is Tobias Macey and today I'm interviewing Yoav Cohen about the challenges that data teams face in securing their data platforms and how that impacts the productivity and adoption of data in the organization

Interview

Introduction
How did you get involved in the area of data management?
Data security is a very broad term. Can you start by enumerating some of the different concerns that are involved?
How has the scope and complexity of implementing security controls on data systems changed in recent years?
- In your experience, what is a typical number of data locations that an organization is trying to manage access/permissions within?
What are some of the main challenges that data/compliance teams face in establishing and maintaining security controls?
- How much of the problem is technical vs. procedural/organizational?
As a vendor in the space, how do you think about the broad categories/boundary lines for the different elements of data security? (e.g. masking vs. RBAC, etc.)
- What are the different layers that are best suited to managing each of those categories? (e.g. masking and encryption in storage layer, RBAC in warehouse, etc.)
What are some of the ways that data security and organizational productivity are at odds with each other?
- What are some of the shortcuts that you see teams and individuals taking to address the productivity hit from security controls?
What are some of the methods that you have found to be most effective at mitigating or even improving productivity impacts through security controls?
- How does up-front design of the security layers improve the final outcome vs. trying to bolt on security after the platform is already in use?
- How can education about the motivations for different security practices improve compliance and user experience?
What are the most interesting, innovative, or unexpected ways that you have seen data teams align data security and productivity?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on data security technology?
What are the areas of data security that still need improvements?

Contact Info

Yoav Cohen

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 shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
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Links

Satori
- Podcast Episode
Data Masking
RBAC == Role Based Access Control
ABAC == Attribute Based Access Control
Gartner Data Security Platform Report

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