The Data Stack Show
The Data Stack Show
223: End-of-Year Product Trends: The Cost of Rushing Features with The Cynical Data Guy
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223: End-of-Year Product Trends: The Cost of Rushing Features with The Cynical Data Guy

This week on The Data Stack Show, John is joined by the Cynical Data Guy (Matt Kelliher-Gibson) as they look back on Christmas and New Year’s as they delve into the evolving data landscape. They discuss trends in AI, the year-end rush for product releases dubbed "12 days of shipments," and the dynamics between data engineers and analysts. The conversation also highlights the importance of data warehousing and open-source data formats, reflecting on the industry's shift towards more accessible and flexible data practices. The episode concludes with reflections on 2024 and hopes for continued progress in data management in this new year. Don’t miss it!

Highlights from this week’s conversation include:

  • Christmas and New Year Edition of Cynical Data Guy (0:28)

  • Discussion on AI (0:42)

  • 12 Days of Shipments (1:04)

  • Attention-Grabbing Strategies (2:01)

  • Founder Mode vs. Manager Mode (3:11)

  • Technical Debt Remediation (5:03)

  • LinkedIn Posts Discussion (6:05)

  • Cultural Impact on Roles (8:03)

  • Investment in Modernization (12:07)

  • Reflection on Company Strategies (15:03)

  • Gratitude for Data Trends (16:18)

  • Future of Data Access (19:14)

  • Looking Forward to 2025 in Data (21:45)

  • Final Thoughts and Takeaways (22:11)

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

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The Data Stack Show
The Data Stack Show
Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.