Data Forward: AI and Data Management News

In this special episode of Data Forward, Vivek Singh sits down with Chandrakant “Chandra” Sharma — Acceldata’s Global Field CTO and VP of Field Engineering — for a candid, practical conversation on how the world’s largest enterprises are modernizing their data platforms.Chandra shares proven, real-world strategies for:Simplifying complex, fragmented data stacksAvoiding vendor lock-in while controlling cloud costsSafely migrating off aging Hadoop platformsBuilding AI-ready, reliable platforms that deliver business valueWhether you’re a data leader, architect, or engineer, you’ll walk away with actionable lessons you can start applying immediately to improve agility, reduce costs, and future-proof your data platform.

In this episode, Ramon Chen sits down with industry veteran Dan Power to explore the evolution of data governance, quality, and management in the age of AI. From foundational lessons at Dun & Bradstreet to regulatory pressures in financial services, Dan shares what it takes to build trusted, scalable data practices—and where AI fits into the picture.Key Takeaways:- Data Products Need Discipline: Creating reliable data products requires manufacturing-like thinkingclear inputs, measurable outputs, and trust scores to drive business value.- AI Is Not a Silver Bullet—But a Power Tool: GenAI and agentic systems can automate manual data work, but only if foundational data observability is in place.- Regulations Demand Operational Readiness: Regulatory compliance increasingly depends on fast, accurate lineage, quality metrics, and the ability to prove control—not just documentation.

What does it actually take to prepare your enterprise data for the next wave of Agentic AI? In this special episode recorded live at Autonomous 25, Acceldata’s product marketing leader, Sonam Jain talks with Supratibh Srivastava, Principal Sales for ML Startups at AWS, about how companies are building a strong foundation for GenAI and agentic systems.You’ll learn:How data silos, poor governance, and unclear data strategy stall enterprise AI modelsWhat agentic data management means for data engineering and platform teamsWhy clean, observable, and policy-compliant data is critical to preventing hallucinationsThe role of AWS Bedrock, SageMaker, and DataZone in enabling trusted, scalable AIWhether you're building AI foundations, launching LLM-powered tools, or scaling GenAI infrastructure, you’ll walk away with clear next steps and practical inspiration.

In this episode of Data Forward, Acceldata CPO Ramon Chen chats with Bob Evans, founder of Cloud Wars, about how cloud giants are shifting from product-focused strategies to customer-led innovation. They explore the evolving role of data, AI, and cross-cloud partnerships—and what it means for the future of enterprise tech.

In this episode of Data Forward, Ashwin Rajeev (CTO & Co-Founder, Acceldata) talks with Adnan Khan, Managing Director of Data & AI Services (EMEA) at Accenture, about modernizing enterprise data in the age of AI.Adnan shares insights from 20+ years at Accenture—exploring how regulated industries, legacy systems, and organizational culture shape innovation. From balancing foundational systems with AI adoption, to building trust through observability and lineage, this conversation offers real-world strategies for scaling data and AI initiatives.Highlights:The two-speed path to data modernizationWhy observability and lineage matter more than everHow regulation impacts AI adoption across industriesAccenture’s approach to driving agility without breaking trust

In this episode of Data Forward, Chief Product Officer Raman Chen sits down with Tarik El Mansouri, a seasoned Chief Data Officer and digital transformation leader, to explore what it takes to build trustworthy, AI-ready data foundations in today’s enterprise. From coining the term "Proactive Data Quality" to championing Master Data Management and data observability at global organizations like Schneider Electric, Tarik shares deep insights into aligning data strategy with business outcomes, establishing trust across data supply chains, and embracing AI with responsibility and ethics. If you're navigating enterprise data transformation in the AI era, this conversation is a must-listen.

Kaycee Lai, Founder of Promethium and a pioneer in instant data fabrics, joins the conversation to delve into transformative data management strategies. They discuss the innovative concept of instant data fabrics and how generative AI is reshaping data accessibility and quality. Lai highlights real-world implementations from companies like National Grid and Comcast, emphasizing the synergy between data observability and enhanced data products. The discussion also touches on the evolving landscape of application development, necessitating a re-skilling approach to meet new demands.

Prakul Sharma, a Partner at Deloitte Consulting leading their data and AI practice, shares his expertise on the intersection of AI and data management. He discusses how AI is revolutionizing data governance and the role of Chief Data Officers is evolving to include oversight of AI models. Prakul also delves into the challenges faced by Fortune 500 companies in navigating complex data landscapes, emphasizing the necessity of rethinking data strategies with AI-driven tools for enhanced efficiency and productivity.

In this episode of Data Forward, Acceldata’s co-founders, Rohit Choudhary (CEO), Ashwin Rajeev (CTO), and Raghu Mitra (VP of Engineering), discuss how AI and cloud transformation have reshaped engineering. They highlight how these shifts boost productivity, streamline software development, and evolve the role of engineers in driving success.3 Key Takeaways:- AI and Cloud Revolutionizing Engineering: Cloud and AI integration have enabled smaller teams to drive major productivity gains, building scalable solutions.- Shift from "Build vs. Buy" in Software: Powerful tools are making it easier to buy software solutions, focusing on value and efficiency.- Engineering Craftsmanship and Problem-Solving: Great engineers stand out by deeply understanding problems, taking responsibility, and producing high-quality, thoughtful code.

In this episode Gabriel Charvat, VP Data Quality Insights explores how Dun & Bradstreet, the ultimate data products company, is modernizing operational data quality. He provides tips on best practices and how they have leveraged innovative technologies like Data Observability to replace legacy tools.Taking data quality to the next level by shifting left, speeding time to onboarding new data sources, and improving the efficiency of their pipelines. The conversation highlights key advancements, including reducing time-to-insight, gamifying data quality across global teams, and enabling proactive data quality to address issues before they reach customers.