Colin Zima

Colin Zima, CEO of Omni and former Chief Analytics Officer at Looker, discusses the evolution of business intelligence. He explores how modern BI tools must adapt to fluid data schemas and varying analysis needs. Colin emphasizes the importance of semantic layers for AI integration and challenges of navigating SQL complexity. He also highlights the shift from spreadsheets to BI tools, curating effective dashboards, and the role of language in data interpretation. The conversation reveals the need for flexibility and governance in today’s data landscape.

Colin Zima, co-founder and CEO of Omni, shares insights from his journey in data analytics, transitioning from Looker to his own venture. He discusses the evolution of business intelligence and the necessity of balancing data modeling with practicality. Colin emphasizes the importance of semantic layers in AI, highlighting their role in governance and efficiency. Trust-building in teams and with customers is noted as a crucial driver of innovation. This engaging conversation delves into the future of data platforms and collaboration in the ever-changing data landscape.

Colin Zima, former Looker executive and current Omni CEO, shares insights from his unique management style that thrives on minimal bureaucracy. He argues that founders should roll up their sleeves and tackle tough tasks directly. Colin explains his unconventional approach of operating without an HR or G&A team, valuing engagement over traditional roles. He discusses the cultural pitfalls from acquisitions, like the Google-Listener experience, and emphasizes the need for leaders to adapt their strategies in a hybrid work environment.

Colin Zima, former Chief Analytics Officer and VP of Product at Looker, discusses lessons from Looker, investing in white-glove customer support, scaling high-touch customer support, intuition-based approach to product, Looker's goal achievement streak, founding story of Omni, and hot takes on startups and hiring PMs.

Colin Zima, an expert in data modeling and data engineering, chats about data modeling in 2023 and beyond, covering topics such as real ETL, semantic layers, and the challenges in business intelligence.