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The Ravit Show

Ravit Jain

The Ravit Show aims to interview interesting guests, panels, companies and help the community to gain valuable insights and trends in the Data Science and AI space! The show has CEOs, CTOs, Professors, Tech Authors, Data Scientists, Data Engineers, Data Analysts and many more from the industry and academia side.

We do live shows on LinkedIn, YouTube, Facebook and other platforms. The motto of The Ravit Show is to the Data Science/AI community grow together!

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  • 25 episodes
  • Avg 16 min
  • English

Episodes 25

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  • August 3 · 12 min

    How AtScale Extends Snowflake Semantic Views to Power BI and Excel

    AtScale's latest announcement with Snowflake highlights a reality many organizations are just beginning to realize: AI is only as smart as the business context behind it. That's where the Semantic Layer comes in. What do you think? That was one of the key takeaways from my conversation with Luis Maldonado, Chief Product Officer at AtScale, during Snowflake Summit on The Ravit Show. For years, organizations have struggled with a simple problem: different teams looking at the same data but arriving at different answers. Finance has one definition of revenue, sales has another, and operations has a third. The result is confusion, duplicated effort, and a lack of trust in analytics. The Semantic Layer changes that. It creates a common business language that sits between data and the people, applications, dashboards, and AI systems consuming it. Instead of every team building its own logic and calculations, everyone works from the same trusted definitions. What makes this particularly interesting is the collaboration between AtScale and Snowflake. As enterprises move beyond dashboards and into AI-powered decision making, trusted business context becomes critical. AI systems need more than data. They need to understand what that data actually means. The message from AtScale was clear: the future is not just about storing and processing data. It's about ensuring consistent business definitions across Power BI, Excel, analytics platforms, and AI applications. As AI adoption accelerates, I believe we'll hear a lot more about Semantic Layers. They may very well become the foundation that helps organizations move from AI experiments to trusted AI outcomes. #Data #AI #SnowflakeSummit #Snowflake #AtScale#DataAI #EnterpriseAI #AgenticAI #Analytics #TheRavitShow

  • July 30 · 10 min

    How Qlik and Snowflake Are Powering the Next Generation of Enterprise AI

    AI doesn't need more data. It needs more context!!!! That was one of the key themes from my conversation with Josh Good from Qlik at Snowflake Summit on The Ravit Show. As organizations move beyond AI experimentation, the focus is shifting toward governance, trust, and ensuring AI understands the business context behind the data. We also discussed how partnerships between Qlik, Snowflake, and platforms like ServiceNow are helping customers connect data, analytics, and AI into a more unified ecosystem. The future of enterprise AI won't be built by a single platform. It will be built through connected ecosystems working together. #Data #AI #SnowflakeSummit #Snowflake #Qlik #DataAI #EnterpriseAI #AgenticAI #Analytics #TheRavitShow

  • July 29 · 11 min

    How Qlik and Snowflake Are Helping Enterprises Become AI-Ready

    Spent a day at Snowflake Summit in San Francisco this week, and one theme came up in almost every conversation: AI is only as good as the data behind it. I had the opportunity to sit down with Andy Iyengar from Qlik on The Ravit Show, and our discussion went beyond AI hype. A few key takeaways: * Modernizing the data estate is no longer optional. Organizations need trusted, governed, and accessible data before they can scale AI initiatives * Moving data into Snowflake is only part of the journey. Data quality, integration, governance, and readiness remain some of the biggest challenges for enterprises * Agentic AI is pushing organizations toward connected ecosystems where data, analytics, and AI work together instead of operating in silos * The expanded collaboration between Qlik and Snowflake reflects where the industry is heading: helping customers accelerate AI adoption by making data easier to trust, manage, and activate What stood out to me most was the focus on outcomes rather than technology. The conversation wasn't about building AI for the sake of AI. It was about creating a foundation that allows organizations to confidently move from experimentation to real business value. #Data #AI #SnowflakeSummit #Snowflake #Qlik #DataAI #EnterpriseAI #AgenticAI #Analytics #TheRavitShow

  • July 28 · 11 min

    What Enterprise Leaders Need to Know About Hybrid Data and AI

    What happens when enterprise data lives everywhere, but AI needs a single source of truth? That was the focus of my conversation with Mark Lyons from Cloudera at Snowflake Summit on The Ravit Show. As enterprises continue to embrace AI, many are navigating increasingly complex hybrid and multi-cloud environments. The challenge isn't collecting more data. It's making data accessible, governed, and usable across the entire organization We also discussed why open architectures and interoperability are becoming so important. Customers want flexibility, not lock-in. They want to leverage the best technologies while maintaining a strong foundation for analytics and AI The Cloudera and Snowflake partnership is focused on helping customers do exactly that, creating a path toward trusted data, faster innovation, and better business outcomes. #Data #AI #SnowflakeSummit #Snowflake #Cloudera #DataAI #EnterpriseAI #HybridCloud #MultiCloud #TheRavitShow

  • July 27 · 11 min

    How Equinix Is Building the Foundation for Enterprise AI | Arun Dev

    AI is forcing companies to rethink assumptions they’ve had for years. One cloud provider. One place for data. One approved set of tools. That world is changing fast. At Cisco Live, I sat down with Arun Dev from Equinix to discuss what enterprises are getting right and wrong as they scale AI. A few themes stood out: * AI is pushing organizations beyond a single cloud strategy and into a much more connected ecosystem. * As AI becomes part of operations, trust becomes critical. Just because an answer sounds right doesn’t mean it is. * The pace of innovation is so fast that companies can’t afford to rebuild infrastructure every time a new model is released. * Employees are already using AI tools. The challenge isn’t stopping them. It’s creating the right guardrails around security, governance, and cost. * Data is no longer living in one place. As AI workloads spread across clouds, data centers, and edge environments, networks are becoming a strategic asset. One thing that really resonated with me: The AI conversation is often about models. But the bigger challenge may be building an architecture that can adapt as models, data, and business needs continue to evolve. Great conversation with Arun on the realities of enterprise AI adoption and what leaders should be thinking about today. #data #ai #ciscolive #equinix #observability #api #agents #theravitshow

Showing 21–25 of 25 episodes