TIETOJA TÄSTÄ JAKSOSTA
Today I’m joined by Vishal Singh, Head of Data Products at Starburst and co-author of the newly published e-book, Data Products for Dummies. Throughout our conversation, Vishal explains how the variations in definitions for a data product actually led to the creation of the e-book, and we discuss the differences between our two definitions. Vishal gives a detailed description of how he believes Data Product Managers should be conducting their discovery and gathering feedback from end users, and how his team evaluates whether their data products are truly successful and user-friendly.
Highlights/ Skip to:
- I introduce Vishal, the Head of Data Products at Starburst and contributor of the e-book Data Products for Dummies (00:37)
- Vishal describes how his customers at Starburst all had a common problem, but differing definitions of a data product, which led to the creation of his e-book (01:15)
- Vishal shares his one-sentence definition of a data product (02:50)
- How Vishal’s definition of a data product differs from mine, and we both expand on the possibilities between the two (05:33)
- The tactics Vishal uses to useful feedback to ensure the data products he develops are valuable for end users (07:48)
- Why Vishal finds it difficult to get one on one feedback from users during the iteration phase of data product development (11:07)
- The danger of sunk cost bias in the iteration phase of data product development (13:10)
- Vishal describes how he views the role of a DPM when it comes to doing effective initial discovery (15:27)
- How Vishal structures his teams and their interactions with each other and their end users (21:34)
- Vishal’s thoughts on how design affects both data scientists and end users (24:16)
- How DPMs at Starburst evaluate if the data product design is user-friendly (28:45)
- Vishal’s views on where Designers are valuable in the data product development process (35:00)
- Vishal and I discuss the importance of ensuring your products truly solve your user’s problems (44:44)
- Where you can learn more about Vishal’s upcoming events and the e-book, Data Products for Dummies (49:48)
- Starburst: https://www.starburst.io/
- Data Products for Dummies: https://www.starburst.io/info/data-products-for-dummies/
- “How to Measure the Impact of Data Products with Doug Hubbard”: https://designingforanalytics.com/resources/episodes/080-how-to-measure-the-impact-of-data-productsand-anything-else-with-forecasting-and-measurement-expert-doug-hubbard/
- Trino Summit: https://www.starburst.io/info/trinosummit2023/
- Galaxy Platform: https://www.starburst.io/platform/starburst-galaxy/
- Datanova Summit: https://www.starburst.io/datanova/
- LinkedIn: https://www.linkedin.com/in/singhsvishal/
- Twitter: https://twitter.com/vishal_singh
Englanti
Yhdysvallat
TRANSKRIPTIO 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
HAE EDELLISIÄ EPISODEJA
Hae kanavan Experiencing Data w/ Brian T. O’Neill vanhoja jaksoja.
MUITA jaksoja TÄSSÄ PODCASTISSA
I’ve seen this challenge again and again with teams building analytics and AI products: nobody can define what quality to the end user means or how to measure. The answer? “Adoption.” The problem is that “amount of usage” tells you nothing useful about your customer’s experience with your product …
If you’re hoping that adding AI to your analytics product or capabilities is going to unlock new revenue, sales, and greater user adoption, but you’re not sure what’s involved in this transformation, this episode is for you!
Today, I’m talking with Juan Sequeda today, an expert in knowledge graphs…
It’s a common pattern for teams building B2B analytics and AI products: the proof-of-concept goes well, the buyers sound excited, and everyone assumes the deal is about to close—until it quietly stalls out. The assumption is usually that sales needs to follow up harder or marketing needs more enabl…
I've been seeing a recurring pattern with companies selling APIs, MCPs, data feeds, and other developer-focused AI products. While the technology is often sound if not impressive, sales momentum sometimes slows when prospects have to imagine how the product will create value in their own environmen…
Speed is often confused with good product thinking. The idea is that if teams can ship prototypes, dashboards, and models faster, they will automatically learn faster. But execution speed alone doesn’t ensure a clearer understanding of what’s actually worth building.
Instead, teams often fall into…
Vastuuvapautusilmoitus: Tälle sivulle upotettu podcast ja kuvitus ovat peräisin Brian T. O’Neill from Designing for Analytics:ltä, joka on sen omistajan omaisuutta, eikä se ole sidoksissa Listen Notes, Inc:n tukemaan.
MUOKKAA
Kiitos, kun autoit pitämään podcast-tietokantaa ajan tasalla.
