Data Analytics Chat

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With Carol Kim — Executive Director, IBM

Can an organisation really be data-driven if its data can't be trusted?

In this episode, Ben Parker speaks with Carol Kim about why Data Governance and Data Quality are fundamental to better decision-making and what happens when organisations fail to get them right.

Carol explores how poor-quality data affects far more than technology, creating hidden costs across decision-making, operations and the wider business.

Drawing on her journey from finance into technology and Data and AI leadership, Carol also discusses the importance of curiosity, storytelling and authentic leadership — and the lessons she's learned navigating transformation across different cultures and environments.

You’ll hear practical insights on:

• Why trusted data is essential for better decision-making 
• The hidden business costs of poor Data Quality 
• Where Data Governance typically breaks down 
• How people, process and technology need to work together 
• What organisations need to build effective Data Governance 
• Why storytelling matters for Data leaders 
• The importance of curiosity and continuous learning in leadership 

Chapters

00:00 The importance of continuous learning
02:01 Carol's career and leadership journey
07:54 Why storytelling matters in Data
09:59 Leadership and career transformation
15:13 Why Data Governance & Data Quality matter
24:06 Final thoughts

Thank you for listening! 

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With Ilya Meyzin — SVP, Head of AI Solutions at Dun & Bradstreet

Are AI agents genuinely the next major shift in enterprise AI or are many still sophisticated workflows wrapped around LLMs?

In this episode, Ben Parker speaks with Ilya Meyzin about what AI agents can actually do today and what it takes to turn experimentation into real business value.

Ilya explores how agents differ from traditional AI systems, where the strongest use cases are emerging, and why many promising pilots struggle when organisations attempt to scale them.

The conversation also examines data quality, enterprise architecture, cross-functional collaboration and whether AI agents will become a fundamental part of how organisations operate.

You’ll hear practical insights on:

• What AI agents can do that traditional LLMs cannot 
• How to identify genuinely valuable agentic use cases 
• Why AI agent pilots struggle to scale 
• The difference between orchestration and genuine intelligence 
• Why data quality remains critical 
• How teams need to collaborate to deploy agents successfully 
• Whether agents will become embedded in enterprise architecture 

Chapters

00:00 Introduction
01:14 Ilya's career and leadership journey
14:45 Balancing technical expertise with business understanding
23:18 What AI agents actually are
28:40 Where AI agents create real value
32:14 Building and scaling agents in the enterprise
37:21 Why data quality matters
45:12 The future of AI agents

Thank you for listening! 

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With Allison Olson — SVP, Analytics Solutions at Merkle

How much of what we buy is influenced by AI without us even realising it?

In this episode, Ben Parker speaks with Allison Olson about how AI and real-time data are transforming personalisation and changing the way brands understand, influence and interact with their customers.

Allison explores the shift from static recommendations to dynamic experiences that adapt to customer behaviour in real time, the data required to make this possible, and where personalisation can cross the line from helpful to intrusive.

The conversation also examines how Generative AI could transform customer experiences further and what the next generation of personalisation might look like.

You’ll hear practical insights on:

• How AI influences the decisions customers make 
• The shift from static to dynamic personalisation 
• How real-time data creates adaptive customer experiences 
• Balancing personalisation with privacy and trust 
• The challenges of personalising experiences at scale 
• How Generative AI could reshape customer interactions 
• What the future of personalisation could look like 

Chapters

00:00 Introduction
02:12 Allison's career and leadership journey
08:37 Learning from failure and taking risks
13:45 Lessons in leadership
21:01 How AI is changing personalisation
23:23 Static vs dynamic personalisation
30:42 Balancing personalisation with privacy
35:12 Delivering personalisation at scale
38:16 How Generative AI changes what's possible
43:57 Final thoughts

Thank you for listening! 

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With Viji Krishnamurthy — VP & Head of AI and Generative AI at Oracle

Why do some organisations turn Generative AI into real business value while others struggle to move beyond experimentation?

In this episode, Ben Parker speaks with Viji Krishnamurthy about what it really takes to implement and scale Generative AI inside the enterprise.

Drawing on more than two decades across research, startups, Samsung and Oracle, Viji explores the technical, cultural and organisational challenges that emerge as companies move GenAI into production.

The conversation examines how organisations can demonstrate real business value, manage risks such as hallucinations and bias, build trust in AI systems, and prepare for a future where people increasingly work alongside AI agents.

You’ll hear practical insights on:

• Why Generative AI initiatives struggle to scale 
• Where GenAI is creating real business value 
• Moving from experimentation into production 
• Managing hallucinations, bias and trust 
• The cultural changes required for successful AI adoption 
• How the role of Data and AI professionals is evolving 
• Why AI agents could change how we work 
• What enterprise AI could look like over the next 3–5 years 

Chapters

00:00 The emerging world of AI agents
02:08 Viji's career and leadership journey
07:41 From scientist to product leader
18:19 How Data & AI roles are evolving
27:43 Staying ahead as AI changes
41:08 Why Generative AI is difficult to scale
44:08 Where GenAI is delivering business value
48:52 Managing hallucinations, bias and trust
52:09 The organisational shift required for GenAI
57:05 AI agents and the future of work

Thank you for listening! 

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With Michael Shaw — SVP, Data & AI at Dow Jones

How should organisations measure the real value of their Data and AI investments?

In this episode, Ben Parker speaks with Michael Shaw about one of the biggest challenges facing Data and AI leaders: defining what success actually looks like.

Drawing on experience at Dow Jones, Google, Facebook and Instacart, Michael explores how organisations can connect Data initiatives to business objectives, balance quick wins with long-term value, and set realistic expectations with stakeholders.

The conversation also examines why ROI goes beyond financial returns, the importance of strong data foundations and adoption, and how AI is changing expectations around the value Data teams are expected to deliver.

You’ll hear practical insights on:

• How to define success for Data and AI initiatives 
• Connecting Data investments to business outcomes 
• Balancing quick wins with long-term value 
• Why Data Quality and Governance affect ROI 
• Driving adoption across the wider organisation 
• Measuring value beyond direct financial returns 
• How AI is changing expectations of ROI 

Chapters

00:00 Introduction
01:58 Michael's career and leadership journey
28:08 Defining success and ROI in Data
32:04 Why strong Data foundations matter
33:05 Balancing stakeholder expectations and quick wins
44:31 Driving adoption and cultural change
54:31 How AI is changing expectations of ROI

Thank you for listening! 

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With Priya Gopal — Founder, Inferential Data LLC | Former Takeda & GSK

Why are strong data standards so important in pharma and why are they so difficult to implement consistently?

In this episode, Ben Parker speaks with Priya Gopal about what it takes to build and implement effective data standards across complex pharmaceutical organisations.

Drawing on her experience across clinical research and major pharma companies including Takeda and GSK, Priya explores the importance of cultural readiness, the challenges of implementing standards across global teams, and how organisations can balance regulatory requirements with internal Data Governance.

The conversation also examines how better data standards can enable innovation, the growing role of AI and automation, and why greater collaboration across the industry could help pharma move faster.

You’ll hear practical insights on:

• Why data standards matter in pharma 
• The biggest barriers to implementing standards consistently 
• Balancing global regulation with internal Data Governance 
• Why culture matters when driving Data transformation 
• How stronger standards can enable innovation 
• The role of AI and automation 
• Why cross-industry collaboration matters 

Chapters

00:00 Introduction
01:23 Priya's career and leadership journey
10:20 Lessons from Data transformation in pharma
20:34 Building effective Data standards
28:42 Balancing regulation and Data Governance
34:18 AI and automation in pharma
39:42 Collaboration and the future of pharma Data

Thank you for listening! 

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In this episode of Data Analytics Chat, we welcome Shourabh Mukherji, a data and analytics expert with 25 years of experience at major firms such as Chubb and JPMorgan Chase. 

Shourabh shares his journey from starting a small enterprise in India to working with senior executives in the United States. The discussion examines his career milestones, key challenges, and the vital leadership skills required in the industry. 

The data topic explores essential data management principles, the importance of aligning data strategies with business objectives, and the role of AI and new technologies in modern enterprises. Shourabh emphasises the significance of building strong data foundations and fostering empathy within teams to drive successful data-driven decisions.

00:00 A Defining Moment: Leap of Faith
01:19 Introduction to Data Analytics Chat
02:08 Shourabh Mukherji's Career Journey
07:07 Challenges and Defining Moments
09:47 Building Trust and Stakeholder Management
15:57 Key Skills for Leadership
22:32 Core Data Management Principles
25:38 Understanding Business Needs Before Data Management
26:42 Centralised vs. Embedded Data Quality Ownership
28:09 The Importance of Needs Analysis in Data Management
31:54 Identifying and Prioritising Business Needs
34:15 Building a Strong Data Solution Framework
40:05 Effective Data Distribution for Decision Making
42:53 Aligning Business Objectives with Data Initiatives
44:42 Evolving Data Management Strategies with AI

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In this episode of Data Analytics Chat, we sit down with Juan Gorricho, a leader in data analytics with experience at top companies like Walt Disney, Visa, and TD Bank. 

Now the founder of Strategic Data Transformation, Juan shares his journey in the data field, the challenges of delivering data projects, the importance of aligning data projects with business goals, and managing expectations amid the AI hype. 

He also provides leadership lessons, emphasising the value of empathy, listening, and team growth. 

00:00 Introduction to Data Analytics Chat

00:07 Guest Introduction: Juan Gorricho Career Journey

01:00 Early Career and Education

01:37 The Intersection of Data, Technology, and Business

06:05 Challenges and Success in Data Projects

11:46 Managing Expectations in the AI Hype Cycle

15:25 Leadership Lessons and Team Management

23:36 Influences and Principles of Leadership

27:22 Breaking into Leadership: Overcoming Fears and Embracing Change

29:56 The Importance of Servant Leadership

30:45 Challenges in Data Projects: Business Alignment and Adoption

34:23 Human and Cultural Roadblocks in Data Projects

43:22 The Role of Communication in Data Project Success

52:03 Overcoming Obstacles and Achieving Success in Data Projects

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9In this episode of Data Analytics Chat, we sit down with Dushyanth Sekhar, Head of AI and Data Platforms at S&P Global. Dush shares key insights from his career journey, emphasising the importance of learning from failures in the AI space. 

He discusses his transition from a non-technology background to leading AI and data initiatives, the role of continuous learning, and the significance of setting a vision and promoting a risk-taking culture in leadership. 

The conversation highlights the strategic implementation of generative AI and agents in transforming data workflows and enhancing company growth. 

00:00 Embracing Failures in AI
01:07 Introduction to the Podcast and Guest
01:50 Career Journey and Early Beginnings
03:03 Transition to AI and Key Learnings
04:19 Defining Moments and Career Decisions
05:33 Moving to the US and Professional Growth
10:16 Leadership Insights and Risk-Taking
17:19 Staying Updated in a Fast-Paced Field
19:36 Excitement for the Future of AI
21:10 Overestimating Risk and Underestimating Opportunity
21:54 The Evolution of Language Models at S&P
23:49 Integrating AI into Workflows
28:31 Enhancing and Creating New Products with LLMs
30:54 Future-Proofing and Optimising with AI
37:19 The Role of Agents in AI
40:19 Lessons Learned from AI Integration
41:40 Conclusion and Final Thoughts

Thank you for listening! 

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In this episode of Data Analytics Chat, we welcome Sundip Gorai, Global Head of Data Science and AI at Global Payments, a Fortune 500 company. Sundip shares insights from his expansive career journey, which spans across various industries like banking and manufacturing, and discusses how agentic AI is revolutionising business. 

He offers insight into AI strategy, the challenges of adopting AI, and the importance of striking a balance between technology and ethics and social responsibility. Sundip also reflects on the future of work, the impact of AI on jobs, and the need for continuous learning in this rapidly evolving field.

00:00 Introduction and Initial Thoughts on Leadership
01:04 Welcome to Data Analytics Chat
02:18 Sundip Gorai's Career Journey
08:11 Defining Moments and Challenges in Career
17:17 Leadership Skills and Attributes
19:47 Meditation and Stress Management
24:10 Approaching AI Strategy
28:54 Choosing the Right Tools for AI Strategy
29:04 The Unchanging Layers of AI Strategy
30:01 The Obsession with Tools and Technologies
31:07 Understanding Agent AI
34:07 Industries Adopting Agent AI
39:01 Challenges in Deploying AI
43:15 Impact of AI on Jobs and Skills
49:10 Future of Business and Mankind with AI

Thank you for listening!