Self-service analytics has been a goal for data teams for years, but recent advances in AI are accelerating progress in unexpected ways. The combination of natural language interfaces and spreadsheet-like tools is lowering barriers to data access across organizations. But how do you balance the freedom of self-service with the need for governance and accuracy? What skills do analysts need to work effectively with AI systems that don't always produce the same results twice? And when AI-generated answers might be slightly off, how do you know when to trust them?

Mike Palmer is Chief Executive Officer of Sigma , where he leads the company’s strategy and growth as a cloud-native analytics and business intelligence platform. Since joining Sigma in 2020, he has focused on expanding access to cloud data by enabling business users to analyze data warehouses through familiar, spreadsheet-based workflows. Prior to Sigma, Mike served as Chief Product Officer at Druva, where he was part of the executive team scaling the company’s cloud data management platform and supporting rapid revenue growth. Before that, he was EVP and Chief Product Officer at Veritas Technologies, leading the transformation and modernization of a large enterprise data protection portfolio following its separation from Symantec. Earlier in his career, he held senior general management and executive roles at Seagate Technology and Verizon Enterprise Solutions, overseeing large-scale cloud, security, and enterprise infrastructure businesses. Mike is based in San Francisco and has spent his career building and operating enterprise data and analytics platforms at scale.

In the episode, Richie and Mike explore the journey towards self-service analytics, the role of AI in democratizing data access, the challenges of stochastic processes, the evolution of analytics applications, how businesses can leverage AI for personalized insights, the future of enterprise software, and much more.

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