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DatAInnovators & Builders features Chief Data Officers and data leaders sharing real strategies for conquering data complexity and building AI solutions that work. Host Saket Saurabh, CEO of Nexla, delivers practical insights on tackling data variety, moving AI from pilot to production, and making transformation actually happen.
| Episode | Date |
|---|---|
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Why most enterprise data isn't actually big data
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Jul 28, 2026 |
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Why most organizations are solving the wrong data problem for AI
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Jul 14, 2026 |
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Why a data catalog isn't ready for AI agents without a semantic layer
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Jun 30, 2026 |
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Agent management: how do you govern AI you didn't build
|
Jun 16, 2026 |
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Why fixing your data beats building an AI lab?
|
Jun 02, 2026 |
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Look before you merge: catching downstream impact before it breaks production
|
May 19, 2026 |
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How a healthcare startup migrated from Azure to GCP and kept production running
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May 05, 2026 |
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The language mistake data leaders make when presenting to executives
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Apr 21, 2026 |
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Context Is the Differentiator, Not the Model
|
Apr 07, 2026 |
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15 AI Agents and Nothing to Show for It
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Mar 24, 2026 |
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The 'no more individual contributors' framework: Managing a team of 3 with AI
|
Mar 10, 2026 |
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95% prompt cache hit rate: how LLM cost reduction actually works in production
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Feb 24, 2026 |
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How swarm intelligence solves routing problems in 20 seconds without training data
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Feb 10, 2026 |
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The delegation test for AI: If an intern can't succeed with your context, neither will your model
|
Jan 27, 2026 |
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Ortecha's Stephen Gatchell On The Data Governance Gap That's Blocking Your AI Production Deployment
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Jan 13, 2026 |
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Bigpanda's Alexander Page On Building AI Agents That Internalize Corrections
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Dec 23, 2025 |
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"AI build, Human verify, AI refine”: How CurieTech flipped the IT engineering workflow, with Ashish Thusoo
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Dec 09, 2025 |
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Databricks' Robin Sutara On Why AI Training Fails - And Persona-Based Enablement That Works
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Nov 25, 2025 |