Data Analytics Chat

In this episode of Data Analytics Chat, we welcome Sujit Narapareddy, Head of Data and Analytics at AWS Sales. Sujit shares his insights on AI transformation in large enterprises, likening it to the shift from paper maps to GPS. We discuss the critical role of human judgment in the age of AI, how organisations can effectively integrate AI into their workflows, and the importance of building a strong data foundation. Sujit shares his personal journey from a technical role to a leadership position, highlighting the importance of business intuition and continuous learning. The conversation covers how AI will change organisations by embedding insights into workflows and reducing the friction between knowing and acting. 00:00 Introduction to AI Transformation01:42 Guest Introduction: Sujit Nara Par02:08 Exploring AI's Impact on Organizations02:32 Sujit's Career Journey and Leadership Insights09:21 The Role of AI in Enhancing Human Roles16:17 Challenges and Strategies for AI Integration28:28 Preparing for the Future of AI30:02 Conclusion and Final ThoughtsThank you for listening!

In this episode of Data Analytics Chat, we welcome Carlos Pineda, the Head of Data Analytics and Insight at Diageo North America. Carlos shares his extensive experience in data analytics across Latin America, Asia-Pacific, Eastern Europe, and North America. They discuss the growing role of AI in both personal and corporate life, the importance of a strong data foundation, and the critical need to understand business processes and foster strong relationships. Carlos emphasises the importance of targeted AI use cases, end-to-end transformation, and continuous delivery in AI implementation. The conversation delves into effective leadership strategies, experimentation, and the value of consistent stakeholder engagement to integrate AI into business operations successfully. Key topics include data readiness, the role of generative AI, and the overall impact of AI-driven business transformations.00:00 Introduction to AI in Daily Life01:15 Welcome to Data Analytics Chat01:53 Meet Carlos Pineda02:51 Career Decisions and Growth05:30 Leadership Challenges and Lessons08:02 The Reality of AI in Business09:58 The Importance of Business Acumen13:13 Challenges in AI Implementation30:38 The Cost and Value of AI33:39 Final Thoughts and FarewellThank you for listening!

In this episode of Data Analytics Chat, we welcome Misha Trubskyy, head of Claims Data Science at Mercury Insurance. Misha shares his journey from academia to corporate life, highlighting his transition from econometrics to leading data science initiatives in insurance. He discusses the significance of continuous learning, the challenges of implementing AI and data, and the importance of hiring and retaining top talent. Misha also delves into his leadership principles, the value of technical proficiency, and the importance of empathy in managing teams. Key issues such as the evolving hiring landscape, market conditions, and strategies for organisational growth are explored in-depth.00:00 Introduction and Personal Philosophy00:14 The Importance of Continuous Learning00:44 Challenges in the AI and Data Science Field01:20 Guest Introduction: Misha Ky02:24 Misha's Career Journey03:43 Current Excitements in AI and Data Science06:09 Navigating Human Elements in Claims07:37 Leadership Challenges and Lessons11:28 The Value of Individuality in Leadership19:31 Advice for Aspiring Data Leaders29:52 Hiring Challenges in AI and Data Science37:02 Finding the Right People for the Job37:23 The Importance of Critical Thinking37:41 Authenticity in Interviews38:26 The Role of Technology in Interviews38:51 Evaluating Candidates Beyond Technical Skills41:36 The Misconception About Technical Skills42:25 Personality and Attitude in Hiring44:21 Challenges in the Job Market48:55 Investing in Junior Staff01:04:33 Retention Strategies for Top Performers01:10:03 Future of the Hiring Landscape01:13:42 Conclusion and Final ThoughtsThank you for listening!

In this episode of Data Analytics Chat, we welcome Carol Kim, Executive Director at IBM, who shares her intriguing journey from a finance background to leading technology, data, and AI at IBM's Global Real Estate organisation. Carol discusses her career transformation, the importance of curiosity and authentic leadership, and the role of storytelling in decision-making. The episode also looks into the significance of data governance and quality for data-driven decision-making and how to build effective data governance frameworks. Carol further discusses adapting to different cultures, continuous reinvention, and the hidden costs of poor data quality. 00:00 Introduction: The Power of Willingness to Learn01:12 Welcome to Data Analytics Chat02:01 Carol Kim's Career Journey02:57 The Role of Data in Real Estate03:38 Adapting to Different Cultures07:54 The Importance of Storytelling in Data09:59 Challenges in Leadership and Career Transitions15:13 The Significance of Data Governance and Quality24:06 Conclusion and Final ThoughtsThank you for listening!

In this episode of Data Analytics Chat, host Ben welcomes Ilya Meyzin, SVP Head of AI Solutions at Dun & Bradstreet. Ilya shares his career journey from management consulting to leading AI solutions, highlighting the importance of implementation, continuous learning, and cross-domain expertise. He discusses the evolution of AI agents, their capabilities, and the shift from linear models to stateful, autonomous agents. The conversation delves into the complexities of scaling AI, embedding agents in enterprise architecture, and balancing technical innovation with business value. Ilya also emphasises the necessity of high-quality data and the importance of cross-departmental collaboration for successful AI deployment.00:00 Introduction and Initial Insights01:14 Guest Introduction and Career Overview02:45 Transition from Strategy to Implementation04:15 Learning and Adapting in Consulting05:35 Defining Career Moments10:35 Handling Challenges and Stress13:03 Leadership and Team Dynamics14:45 Balancing Technical and Business Skills20:01 Focus and Credibility in Leadership23:18 Introduction to AI Agents23:39 Capabilities of AI Agents24:22 Technical Aspects of AI Agents25:39 Complex Problem Solving with AI Agents28:40 High-Value Use Cases for AI Agents32:14 Team Collaboration in AI Deployment33:19 Challenges in Scaling AI Agents37:21 Data Quality and AI Agents45:12 Future of AI Agents in Enterprises48:17 Conclusion and Final ThoughtsThank you for listening!