Systems | Development | Analytics | API | Testing

Shub Agarwal (Founder of the AI Trust Lab at USC) flips the script. Stop over-investing in massive data overhauls. Instead, reverse your approach: start with a brutal business problem, pull only the specific data needed to solve it, and build incrementally. Chief Data & AI Strategy Officer Cindi Howson agrees that true value comes from scaling immediate business impact, not waiting for a flawless architecture that will never arrive.

As organizations rush to scale AI, many are learning that better models can’t compensate for weak data foundations. AI hype is everywhere, but operational readiness still isn’t. In this episode of The AI Forecast, Paul Muller sits down with Ravit Jain, founder of The Ravit Show and one of the leading voices in the global data and AI community, to explore the trends shaping the future of enterprise AI.

Understand how to close the gap between AI experimentation and enterprise production. Shub Agarwal, Founder of the AI Trust Lab at USC and author of Successful AI Product Creation: A Nine-Step Framework, shares his AI product management framework for taking enterprise AI strategy from demo to production, drawing on two decades of product leadership at Amazon and Fortune 50 firms. He breaks down why experimentation must tie directly to business OKRs, the four mindset shifts leaders need to scale AI responsibly, and how the AI Trust Lab is building a benchmark evaluation framework for AI model trust and governance.

Welcome to Part 7 of the “Data Products for Qlik Analytics” series! In this episode, we take Data Quality to the next level by building advanced data validation rules using IF / THEN / ELSE logic within Qlik Analytics. You’ll learn how to create conditional validation logic that evaluates relationships across multiple columns, enabling smarter and more dynamic data quality checks for your data products.

Zscaler's Tiffany Blakeney shares how her team replaced fragmented tools and months-long development cycles with Snowflake's all-in-one AI platform. By consolidating all data, APIs, and AI models in one secure platform, Zscaler reduced campaign creation from months to minutes—and more importantly, gained the trustworthy, governed AI foundation a cybersecurity company demands. Learn how they're using Snowflake's integrated AI capabilities to move from POC to production faster than ever while maintaining the security posture critical to their industry.

Tableau's direction is clear. For embedded analytics teams serving customers with strict governance, data residency, or infrastructure requirements, "cloud only" constrains your product, your market, and your roadmap. In this video, we break down what Tableau Next's Hyperforce launch actually means for ISVs and SaaS vendors building embedded analytics, including: If you're doing real long-range planning, this is the conversation that matters.

Join Paul Ramsey, Product Manager at Google, for a demonstration of AlloyDB’s new Lakehouse Federation capability. Using a fictional financial services firm, Cymbal Investments, we show how analysts can research S&P 500 trends by combining real-time vector search with data in BigQuery and Google Cloud Lakehouse. In this video, you will see: Learn how AlloyDB enables cloud and AI transformation for your data platform.

Ryan Tucker, CRO & Co-Founder of Hakodaa (now an IBM company), shares how their True Blue Snowflake partnership since 2021 drives data transformation and AI value with vertical expertise. He highlights customer wins including Cortex AI-powered sentiment analysis for a UK wealth manager and Snowflake Intelligence for retail executive reporting, and discusses how the IBM acquisition amplifies their Snowflake-specialized DNA with global reach.

AI fixed the M&A data nightmare, but @SPGlobalMarketIntelligence 's Saugata Saha says the real win is shifting your mindset. Stop treating data as a byproduct...make it your competitive edge! Catch the full discussion of podcast on any podcast platform.