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Denodo Data Bites

Denodo Data Bites

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 Are you new to the world of data, trying to simplify data jargons to get a clear understanding of data concepts? Don't worry, we have got you covered!

In each episode, we interview an industry leader within the data space to discuss a variety of topics falling under the data umbrella. Our conversations aim to help newcomers & veterans navigate the complexities of the data industry with ease.

Check out our show today to hear critical insights from industry experts to learn about All Things Data!Copyright Denodo
Episodi
  • 2026 Denodo Data Predictions (Part 3): From ROI to Human Readiness - What Will Really Shape AI in 2026?

    2026 Denodo Data Predictions (Part 3): From ROI to Human Readiness - What Will Really Shape AI in 2026?
    Dec 29 2025
    We’re excited to bring you the third and final episode of Executive Spotlight, our series featuring Denodo executives and thought leaders shaping the future of data and AI.

    In this episode, we're once again joined by Alberto Pan, Executive Vice President & Chief Technology Officer and Ravi Shankar, Senior Vice President & Chief Marketing Officer to unpack the final set of predictions from Denodo’s 2026 Data Predictions Report. The discussion focuses on what will truly determine AI success in 2026 - measurable ROI, strong AI and data governance, the rise of Autonomous BI, and the often-overlooked human side of AI adoption.

    Key Insights from This Episode

    ROI Becomes the Deciding Factor for AI and Cloud Investments: As enterprises move beyond the AI hype cycle, boards and CFOs are demanding clear, measurable returns. By 2026, AI initiatives will only move forward if they demonstrate tangible business value - such as cost reduction, faster decision-making, or revenue growth. The focus shifts from “what AI can do” to “what value it delivers,” pushing organizations to prioritize technologies like Logical Data Management that connect AI models directly to trusted business data and accelerate time-to-insight.

    AI Governance Depends on Strong Data Governance: Successful AI governance cannot exist without robust data governance. As AI becomes more deeply embedded in business processes, organizations must ensure their systems are explainable, auditable, and safe. Active data governance - applying semantics, quality, privacy, and security controls dynamically at the moment of data access - becomes essential. In 2026, the dependency chain becomes clear: trusted AI outcomes require AI governance, and AI governance depends on strong, active data governance foundations.

    Autonomous BI Democratizes Analytics Through AI Agents: AI-powered analytics is entering a new phase with the rise of autonomous BI. Reasoning agents can now perform complex, multi-step analysis by creating research plans, accessing enterprise data, identifying patterns, and explaining results with full lineage. This fundamentally reshapes the role of BI teams - shifting analysts from report builders to strategic guides. At the same time, business users gain the ability to ask complex questions in natural language and receive trusted, explainable insights, dramatically expanding access to analytics across the organization.

    Human Readiness Becomes the Next AI Bottleneck: While AI innovation continues to accelerate, human adoption is emerging as the limiting factor. Organizations may deploy powerful models, but without trust, skills, and cultural readiness, value remains unrealized. Bridging this gap requires investment in enablement, upskilling, governance frameworks, and human-in-the-loop workflows. Empowering employees with self-service capabilities and business-friendly ways to interact with data allows them to collaborate effectively with AI and confidently guide its decisions.

    Why This Matters
    By 2026, successful AI adoption will no longer be defined by experimentation or technical sophistication alone. It will depend on measurable ROI, strong governance foundations, democratized intelligence, and people who are equipped to work alongside AI. Organizations that align technology, governance, and human readiness will be best positioned to scale AI responsibly and sustainably.

    🎧 Tune in to the final episode of Denodo’s 2026 Data Predictions series to learn how enterprises can move from AI ambition to real-world impact - and prepare for the next phase of intelligent transformation.

    Visit the Denodo Data Bites Podcast Series page to check out more episodes.
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    17 min
  • 2026 Denodo Data Predictions (Part 2): The Sovereign Fabric & the Physical AI Frontier

    2026 Denodo Data Predictions (Part 2): The Sovereign Fabric & the Physical AI Frontier
    Dec 23 2025
    We’re excited to bring you the second episode of Executive Spotlight, our series featuring Denodo executives and thought leaders shaping the future of data and AI. In this episode, Ravi Shankar, Senior Vice President & Chief Marketing Officer, and Alberto Pan, Executive Vice President & Chief Technical Officer, explore the next set of predictions from Denodo’s 2026 Data Predictions Report. The discussion focuses on how geopolitical pressures, regulatory mandates, and real-world AI use cases are reshaping enterprise data architectures - and why Logical Data Management is becoming essential for compliance, safety, and production-ready AI. Key Insights from This Episode
    • Geopolitics Drives the Sovereign Data Fabric As global regulations and geopolitical instability intensify, data sovereignty and portability are becoming mandatory. Logical Data Management enables enterprises to avoid cloud lock-in, comply with regulations like the EU Data Act, and share data securely across regions without replication.
    • Physical AI Moves from Concept to Reality AI is no longer confined to software. Autonomous manufacturing, robotics, and real-world AI systems demand ultra-real-time, governed data that combines sensor-level inputs with business context. Logical Data Management delivers trusted, real-time Data Products to power safe and autonomous Physical AI. Domain-Specific Language Models Reduce GenAI Risk General-purpose LLMs struggle with accuracy and hallucinations.
    • Domain-Specific Language Models (DSLMs), combined with semantic, domain-driven Data Products, enable AI systems to deliver accurate, compliant, and production-ready intelligence.
    Why This Matters As AI moves into regulated, high-risk, and real-world environments, enterprises must shift from experimentation to governed execution. Logical Data Management provides the sovereign, real-time, and semantic foundation required to scale AI safely, comply with global regulations, and unlock measurable business value. Tune in now to discover how these predictions will shape enterprise data strategies in 2026 - and how your organization can prepare for the next phase of AI-driven transformation.

    Visit the Denodo Data Bites Podcast Series page to check out more episodes.
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    17 min
  • 2026 Denodo Data Predictions (Part 1): From Autonomous AI Hype to Governed Reality

    2026 Denodo Data Predictions (Part 1): From Autonomous AI Hype to Governed Reality
    Dec 15 2025
    We’re excited to bring you a new episode of Executive Spotlight, our series featuring Denodo executives and thought leaders shaping the future of data and AI. In this episode, Ravi Shankar, Senior Vice President & Chief Marketing Officer, and Alberto Pan, Executive Vice President & Chief Technical Officer, walk us through the first three predictions from Denodo’s 2026 Data Predictions Report. Together, they explore the architectural and strategic shifts enterprises must make as AI evolves from simple copilots to fully autonomous operators. Key Insights from This Episode
    1. Autonomous AI Becomes Operational - AI is moving into agentic, decision-making roles - but only for organizations with real-time, trusted, semantically governed data.
    2. Logical Data Management Surpasses the “One Big Lakehouse” - As multi-cloud and multi-lakehouse environments become the norm, Logical Data Management emerges as the only scalable way to unify and govern distributed data without excessive replication.
    3. AI-Ready Data Becomes a Board Priority - With rising investment but low production success rates, enterprises are shifting their focus from experimenting with AI tools to strengthening the underlying data foundation.
    Why This Matters As the industry transitions from AI hype to practical, governed AI outcomes, Logical Data Management provides the foundation needed for real-time intelligence, autonomy, and business value. Tune in now to learn how these predictions will shape enterprise data strategies in 2026 - and how your organization can prepare.
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    14 min
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