In this episode, Naveen sits down with Colleen Hayes for a practical, no-fluff conversation on breaking into data, staying employable as tools change, and what AI really means for analytics and BI roles.
Colleen shares her unconventional path into data: starting in the early 2000s at a law firm—before “data analyst” was even a common job title—she became the “tech girl” in marketing and kept saying yes to projects others avoided. That mindset earned her a seat at the table on early web + database projects (web forms, backend databases, reporting), and over time, those “extra” assignments became a full career in analytics. Her core lesson: don’t wait for permission—say yes, learn on the job, and stick with it.
The conversation also dives into what Colleen sees as the most common mistake in analytics today: people sprinting toward Python/AI before building fundamentals like SQL. She emphasizes that sophisticated modeling only works when the underlying data is prepared—and that “old school” data work (cleaning, structuring, ETL, governance) still powers everything downstream.
On hiring and career growth, Colleen makes a clear distinction:
For career durability over the next five years, her message is simple: tools will change—mindset and fundamentals matter most. Learn transferable concepts, expect platforms to evolve, and lean into the reality that “the only constant is change.” She also shares an optimistic take on AI in BI: dashboards won’t disappear overnight, because teams still need people to prep data, configure tools, and validate outputs (hallucinations and trust are still real constraints). AI may handle the “basic 80%,” but analysts will increasingly focus on the more sophisticated 20%.
They also touch on Colleen’s work in the community, including her data governance meetup (with upcoming sessions on storytelling, process automation, and AI) and her podcast, Team City Calculations, with upcoming episodes on data privacy and data manipulation.
Key takeaway: If you want a career in data, start building—learn the fundamentals (especially SQL), create a portfolio, meet people in the field, and keep saying yes to the projects that stretch you.
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