How Data Teams Can Do 10x MORE
Key Takeaways
Describes how data teams can improve their work by designing meaning and trust in data analytics
Full Transcript
I'll tell you the biggest problem in the data team has been a shortage of talent. Every company has highly constrained data teams. Have you seen their backlogs? [music] But no human being can go through all of that because the data needs of an organization are infinite. This is the idea of having an augmented super team. Is the data analyst plus the AR agent supporter with agents are your force multipliers. So if you're a data team, you're like, "Whoa, I can now do 10x more." I mean, who doesn't want to do 10x more? >> [music] [music]
Original Description
Data and AI platforms are racing toward agentic and even autonomous analytics. But the bottleneck is rarely the model—it’s data readiness: governed metrics, clear metadata, and a semantic layer machines can read. For data engineers and analysts, this shifts work from hand-built SQL and dashboard tweaks to designing meaning and trust. If an agent can draft column descriptions, propose a model for a new business question, and build the first dashboard layout, where do you add the most value? What do you measure to prove ROI in 30 days? How do you prevent “shiny demos” from driving strategy too early.
Ketan Karkhanis is the CEO of ThoughtSpot. Prior to joining the company in September 2024, Ketan was the Executive Vice President and General Manager of Sales Cloud at Salesforce. He returned to Salesforce in March 2022 after his time as the COO of Turvo, an emerging supply-chain collaboration platform. Before that, Ketan spent nearly a decade at Salesforce, where he led product areas in Sales, Service Cloud, Lightning Platform, and finally Analytics, wherein as the Senior Vice President & GM of Einstein Analytics, he pioneered incredible innovation, customer success, and business acceleration from launch to over $300M and a 30,000 strong user community. Prior to Salesforce, Ketan was at Cisco Systems where he led various technology initiatives and initiatives spanning Customer Advocacy, Cisco Certifications & eLearning.
In the episode, Richie and Ketan explore AI agents for analytics, why “self‑service BI” often fails, using agents to answer questions, build dashboards, and automate data modeling, how analyst and engineer roles shift toward governance and agent design, how transparency, culture, and ROI drive safe adoption, and much more.
Find DataFramed on DataCamp https://www.datacamp.com/podcast
and on your preferred podcast streaming platform:
Apple Podcasts:
https://podcasts.apple.com/us/podcast/dataframed/id1336150688
Spotify:
https://open.spotify.com/show/02
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