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🚀 Data Forward: Building Reliable Data Systems in the Age of AI In this episode, Joe Murphy, Principal Architect at Acceldata sits down with Jay Sivasamy, Principal, Enterprise Data & AI at Workday to explore how enterprises can build trustworthy, reliable data systems in today’s AI-driven world. They dive into: 🔹 Evolving Frameworks: From ETL scripts to AI-ready pipelines 🔹 Trust & Governance: Making reliable data a business-critical asset 🔹 AI Integration: Using AI agents to maintain and improve system reliability 🎧 Tune in and learn how to future-proof your data systems: https://linktr.ee/dataforward #DataForward #DataReliability #AI #EnterpriseData #DataGovernance #MachineLearning #DataEngineering

In this episode of Data Forward, host Amy Kyleen Lute talks with Mahesh Kumar, CMO at Acceldata, about the findings of the new AI Readiness Benchmark Report - based on responses from 150+ data leaders at large enterprises. Mahesh shares why AI readiness is critical, how organizations can measure their preparedness, and the risks when data foundations lag. On this podcast you will learn: -The key metrics to use to measure AI Readiness -The contextual indicators that can help improve your key metrics -How using AI to improve data operations can give organizations a competitive edge

In this episode of Data Forward, Ramon Chen, CPO of Acceldata talks with Matthew Cox, CDO at Fusable, about turning data into a true enterprise asset. They cover how Fusable unifies siloed data, ensures trust and quality with observability and lineage, and prepares for the next wave of AI innovation. Key Takeaways -Unify Data to Unlock Insights – How Fusable delivers value by creating a single, trusted data core. -Trust & Quality First – Why lineage, observability, and governance are essential for reliable data. -AI Readiness Starts with Data – Why high-quality, well-structured data is key for Gen AI and Agentic AI.

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 stacks Avoiding vendor lock-in while controlling cloud costs Safely migrating off aging Hadoop platforms Building AI-ready, reliable platforms that deliver business value Whether 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 models What agentic data management means for data engineering and platform teams Why clean, observable, and policy-compliant data is critical to preventing hallucinations The role of AWS Bedrock, SageMaker, and DataZone in enabling trusted, scalable AI Whether 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 modernization Why observability and lineage matter more than ever How regulation impacts AI adoption across industries Accenture’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.

In this episode, Kaycee Lai, Founder of Promethium, joins host Ramon to discuss building data fabrics and products. They explore challenges in creating Instant Data Fabrics, with examples from National Grid, Quest Diagnostics, and Comcast. The conversation covers the synergy between Data Observability and data fabrics, plus best practices for starting a data fabric journey and insights on AI and GenAI's impact on data management.

In this episode of Data Forward, Rohit and Prakul Sharma, a partner at Deloitte leading the data and AI practice, discuss the evolving role of AI in data management and governance. The conversation explores how AI is reshaping data strategies, from enhancing data governance to enabling more seamless integrations and automations. Prakul also shares insights into the evolving role of the Chief Data Officer (CDO), the challenges faced by Fortune 500 companies in managing complex data landscapes, and the future of AI-driven data management. Key Takeaways:AI and Data Symbiosis: AI is transforming the way data is managed, governed, and utilized, with a focus on integrating unstructured data and embedding AI into all aspects of the data lifecycle. Evolving Role of CDOs: As AI becomes more integrated into data strategies, the role of the CDO is expanding beyond traditional responsibilities to include overseeing AI models, ensuring data quality, and serving application developers. Future of Data Management: The future of data management will rely on AI-driven tools to simplify tasks like data mapping, quality control, and lineage tracking, enabling leaner organizations with greater productivity and innovation.

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.

Merv Adrian, former Gartner analyst, BARC Fellow and CEO of IT Market Strategy joins Data Forward to discuss how organizations can prepare their data for AI innovation. Drawing on insights from a comprehensive survey of 335 AI leaders, Merv shares what distinguishes "High Readiness" companies, the critical role of data observability in ensuring trustworthy AI, and the essential steps to address obstacles like skill shortages and budget.