The Data Stack Show
The Data Stack Show
193: Introducing the Cynical Data Guy: Is Data-Driven a Myth?
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193: Introducing the Cynical Data Guy: Is Data-Driven a Myth?

This week on The Data Stack Show, Eric and John chat with Matthew Kelliher-Gibson, the deemed “cynical data guy,” in a candid discussion about the realities of data work in large organizations. They explore the skepticism surrounding metadata's value, the myth of a data-driven culture, and the challenges of shifting executive mindsets to trust data over intuition. Additionally, the group delves into the practicality of no-code and low-code solutions for data operations, emphasizing the importance of discipline and understanding the limitations of these tools. The conversation also covers the misuse of tools like Jupyter notebooks in production and the need for clear guidelines to prevent inefficiencies and manage tool usage at an enterprise scale. Don’t miss the battle of the cynical and the agreeable on this week’s episode! 

Highlights from this week’s conversation include:

  • Introducing a special edition of the show with the cynical data guy (0:19)

  • Metadata and LLMs (2:32)

  • Data-driven culture (8:44)

  • No-code orchestration tools (17:09)

  • No Code vs. Low Code (19:58)

  • Enterprise Challenges with No Code Solutions (20:08)

  • No Code Tools for Small Companies (21:40)

  • Inappropriate Use of Tools (23:06)

  • Final thoughts and takeaways (24:05)

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.