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Lindsay Murphy

Director, Head of Data, Hiive

Lindsay Murphy is a data leader with 13 years of industry experience. She is currently the Head of Data at Secoda (stands for Searchable Company Data) which helps data teams and business users search, discovery, and document all company data knowledge. Before Secoda, Lindsay led data teams at Maple and BenchSci. Lindsay is also a co-organizer of the Toronto Modern Data Stack Meetup, an instructor of Advanced dbt with Uplimit, and the host of a new podcast called Women Lead Data.

Lindsay Murphy

Sessions / 2025 / 1 talk

  • No More BS: How (and When) to Really Leverage AI

    Successful AI implementation hinges on a solid foundation of data quality and governance, and the current hype often overshadows the critical practical considerations needed to achieve that foundation. Moreover, while AI holds immense potential, it's crucial to evaluate whether it's truly the optimal solution for a given business problem, as simpler, more established methods may be equally or more effective. We present a practical framework to assess whether AI is the optimal solution, and encourage some good old-fashioned critical thinking. Join Colleen Tartow and Lindsay Murphy for a data-driven conversation exploring AI's true viability.

Sessions / 2024 / 1 talk

  • Cost Containment–A Critical Piece of your Data Team's ROI

    Data teams spend a lot of time measuring and optimizing the effectiveness of other teams. Unfortunately, we're not so great at doing this for ourselves. In this talk, we will dive into a big blind spot that a lot of data teams operate with–not knowing how much they're costing their business (now and in the future). Given how easy it is to rack up expensive bills in pay-as-you-go tools across the modern data stack, this can become a big problem for data teams, very fast. We'll discuss how to build your own cost monitoring metrics and reporting (and why you should make this a priority), some of the challenges you will face along the way, and suggest ways to implement cost containment best practices into your workflows to drive cost accountability across your data team and company.

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