Data Forward: AI and Data Management News

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.

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.

Ashwin Rajeeva, Co-founder and CTO of Acceldata, shares his expertise on next-generation data management architectures. He discusses the shift to modern, cloud-native frameworks and the critical balance between structured and unstructured data management. Ashwin emphasizes the need for enterprises to adopt hybrid strategies while upskilling their workforce to navigate evolving challenges. He also highlights the importance of data observability and reassesses traditional metrics of data quality in the context of AI-generated content.

Malcome Hawker, Chief Data Officer at Profisee and host of the CDO Matters podcast, offers transformative insights on data management. He emphasizes building customer-centric data organizations and the crucial role product managers play. The conversation covers shifting towards enabling governance practices and using advanced technologies for data observability. Malcome also explores the significance of active metadata and the future of data contracts, including the prospects of blockchain in data monetization.

Industry luminary Ray Wang joins Data Forward to discuss how the breathtaking evolution in technology and innovation is impacting data management and AI.

Rohit Choudhary, CEO and expert in enterprise data and AI trends, shares invaluable insights on transforming data challenges into opportunities. He discusses the critical shift in the roles of Chief Data Officers and data engineers toward proactive data management. Choudhary elaborates on the cloud transformation journey and the necessity for robust data observability. He highlights emerging AI use cases, particularly in healthcare, and the urgent need for data leaders to embrace AI fundamentals for future success.