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.
Do you want to try out some of the tools and applications that you heard about on Podcast.__init__? Do you have a side project that you want to share with the world? With Linode’s managed Kubernetes platform it’s now even easier to get started with the latest in cloud technologies. With the combined power of the leading container orchestrator and the speed and reliability of Linode’s object storage, node balancers, block storage, and dedicated CPU or GPU instances, you’ve got everything you need to scale up. Go to pythonpodcast.com/linode today and get a $100 credit to launch a new cluster, run a server, upload some data, or… And don’t forget to thank them for being a long time supporter of Podcast.__init__!
- Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
- When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
- 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.
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
- Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
- 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 firstname.lastname@example.org) with your story.
- To help other people find the show please leave a review on iTunes and tell your friends and co-workers
- Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
- Google App Engine
- Apache Superset
- Data Warehouse
- Data Lake
- Redash Funnel Visualization
- Stephen Few
- Django ORM
- Redash Query Results Data Source
- IBM DB2
- Forest Admin