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Podcast.__init__

Building A Business On Building Data Driven Businesses

Summary

In order for an organization to be data driven they need easy access to their data and a simple way of sharing it. Arik Fraimovich built Redash as a way to address that need by connecting to any data source and building attractive dashboards on top of them. In this episode he shares the origin story of the project, his experiences running a business based on open source, and the challenges of working with data effectively.

Announcements

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
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  • You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
  • Your host as usual is Tobias Macey and today I’m interviewing Arik Fraimovich about Redash, an open source business intelligence platform that helps you make sense of your data.

Interview

  • Introductions

  • How did you get introduced to Python?

  • Can you start by describing what Redash is and its origin story?

    • What are the primary ways that it is used?

    • The business intelligence market is quite mature and has many commercial and open source projects to choose from. What are the aspects of Redash that have allowed you to be successful?

    • What would you consider to be your closest competitors?

  • What was your background with data before starting on Redash?

    • What are some of the most notable lessons that you have learned about business intelligence since starting the project?
    • How has the landscape for business intelligence and data analysis changed since you began the project?

  • Beyond just accessing data, Redash focuses on enabling visualization of the results. What types of visualizations do you support and how do you support users in choosing the most effective ways to represent the information?

  • What are some of the common challenges that your users and customers encounter when communicating with data?

  • One of the critical aspects of enabling data access in an organization is the ability to collaborate on asking and answering questions. How do you approach that challenge in Redash?

  • How is Redash implemented and how has the overall design and architecture evolved since you first started working on it?

    • How do you manage the complexity of supporting so many different data sources?
    • If you were to start over today, what would you do differently?

  • Beyond the code of Redash, you also have a business around providing it as a hosted service. What are some of the most interesting, challenging, or unexpected lessons that you have learned in the process of building and growing that service?

  • How do you approach the direction and governance of the open source project and balance that against the wants and needs of the community?

  • What are some of the most interesting, innovative, or unexpected ways that you have seen Redash used?

  • When is Redash the wrong platform to use?

  • What do you have planned for the future of the Redash business and project?

Keep In Touch

Picks

Closing Announcements

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Links

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Episode source