Model as You Go: A New Take on BI

Model as You Go: A New Take on BI

From The Data T by Armon Petrossian and Satish Jayanthi

June 9, 2025 · 41 min · Season 3 · Episode 27

About this episode

Colin Zima discusses reinventing business intelligence and the importance of trust in data innovation.

In this episode of The Data T podcast, Armon Petrossian and Satish Jayanthi sit down with Colin Zima, co-founder and CEO of Omni, to talk about what it takes to reinvent business intelligence. Colin shares his journey from Looker’s early days to building Omni, the lessons learned along the way, and his philosophy of ruthless pragmatism when it comes to data modeling, product development, and AI. The conversation dives deep into the evolving BI landscape, the importance of semantics in AI, and how building trust—whether with customers or stakeholders—can be the real engine of innovation. If you're into the future of data platforms, building in public, or just want to hear what happens when two modern data stack founders compare notes, this one's for you. Main topics: Early startup challenges and reflections The evolving BI landscape The evolution of the Modern Data Stack Perspectives on data modeling The role of semantic layers in AI Hot takes in data analytics Collaboration as a key to success Building trust in data teams Resources: About Omni: https://omni.co/ About Coalesce: https://coalesce.io/about/ Coalesce podcast archive (The Data T): https://coalesce.io/podcast/

People in this episode

Hosts: Armon Petrossian, Satish Jayanthi

Guest: Colin Zima

Topics covered

  • Early startup challenges
  • Evolving BI landscape
  • Modern Data Stack
  • Data modeling
  • Semantic layers in AI
  • Data analytics
  • Building trust in data teams

Keywords

  • business intelligence
  • data modeling
  • AI
  • data analytics
  • trust
  • modern data stack
  • semantics

Mentioned in this episode

Organizations: Omni, Looker, Coalesce

More episodes of The Data T

Explore listener stats, chart rankings, contacts and more on the The Data T podcast page.