Roberto Maranca, The Path to Chief Decision Officer

The Praxi Pod

34:01

I think you could probably go back and track the stages of grief, probably that is what I went through. But I think if you do it right, you end up at acceptance. And that's where I ended up. And that's not to say that I've fully accepted the idea that the golden toad is extinct. Personally, I do still hold out hope that it could still be out there in those forests." - Trevor Ritland This conversation is with Trevor Ritland, who—along with his twin brother Kyle—authored The Golden Toad . The book chronicles their remarkable journey into Costa Rica’s cloud forest, once home to hundreds of brilliant golden toads that would emerge for just a few weeks each year—until, one day, they vanished without a trace. What began as a search for a lost species soon became something much more profound: a confrontation with ecological grief, a meditation on hope, and a powerful call to protect the natural world while we still can. Links: SpeciesUnite.com Kyle and Trevor: https://kyleandtrevor.com/ Instagram: https://www.instagram.com/adventureterm/ Goodreads - https://www.goodreads.com/book/show/222249677-the-golden-toad Amazon - https://www.amazon.com/Golden-Toad-Ecological-Mystery-Species/dp/163576996…

about a year ago 35:18

MP3•Episode home

In this episode, Andrew speaks with Roberto Maranca, Data Officer at an energy business, about the challenges and considerations of implementing new technology and data-driven processes. They discuss the limitations of viewing new technology as a panacea and emphasize the importance of having a well-designed architecture. They also explore the resistance to change and the difficulty of switching off old systems. Additionally, they highlight the value of lean thinking and streamlining processes to create more customer value. Finally, they stress the significance of effective communication and understanding in data initiatives.

Takeaways

Data plays a crucial role in business and should be treated as a product that requires continuous improvement.
Agile data modeling is essential for adapting to the complexity and changing demands of the business environment.
Sustainability and the impact of data centers on CO2 emissions are important considerations for data leaders.
The concept of a digital twin and enterprise intelligence can provide valuable insights and support decision-making.
The hype surrounding AI and GenAI should be approached with caution, and the focus should be on translating these technologies into tangible business outcomes.
The role of a Chief Data Officer evolves from focusing on dashboards to data to decision-making, with a strong emphasis on understanding the business and translating data initiatives into business value. Viewing new technology as a panacea is a mistake; it is important to have a well-designed architecture and consider the limitations of any new tool.
Resistance to change is common, and organizations often struggle with switching off old systems.
Applying lean thinking and streamlining processes can help create more customer value and improve efficiency.
Effective communication and understanding are crucial in data initiatives to avoid miscommunication and alignment issues.

Chapters

00:00 Introduction and Background

02:10 The Role of Data in Business

06:24 The Importance of Agile Data Modeling

09:12 The Challenges of Sustainability and Data Centers

11:19 The Need for a Digital Twin and Enterprise Intelligence

15:22 The Hype Cycles and the Role of AI and GenV

20:47 The Journey of a Chief Data Officer

25:49 The Importance of People and Business Outcomes

28:57 Key Takeaways

31:47 The Limitations of New Technology

32:33 Resistance to Change

33:18 Lean Thinking and Streamlining Processes

33:47 The Importance of Communication and Understanding

With almost 30 years of IT and data experience, Roberto worked at Nissan, Ford, General Electric Capital, Lloyds Banking Group, and Schneider Electric. In 2023, he became Schneider Electric Energy Management BU's Data Officer, focusing on sustainability. He holds a master's degree in Aeronautical Engineering from "Federico II" Naples University and enjoys sailing, gardening, and cooking.

21 episodes

The Praxi Pod

Roberto Maranca, The Path to Chief Decision Officer

The Praxi Pod

published about a year ago

MP3•Episode home

Takeaways

Data plays a crucial role in business and should be treated as a product that requires continuous improvement.
Agile data modeling is essential for adapting to the complexity and changing demands of the business environment.
Sustainability and the impact of data centers on CO2 emissions are important considerations for data leaders.
The concept of a digital twin and enterprise intelligence can provide valuable insights and support decision-making.
The hype surrounding AI and GenAI should be approached with caution, and the focus should be on translating these technologies into tangible business outcomes.
The role of a Chief Data Officer evolves from focusing on dashboards to data to decision-making, with a strong emphasis on understanding the business and translating data initiatives into business value. Viewing new technology as a panacea is a mistake; it is important to have a well-designed architecture and consider the limitations of any new tool.
Resistance to change is common, and organizations often struggle with switching off old systems.
Applying lean thinking and streamlining processes can help create more customer value and improve efficiency.
Effective communication and understanding are crucial in data initiatives to avoid miscommunication and alignment issues.

Chapters

00:00 Introduction and Background

02:10 The Role of Data in Business

06:24 The Importance of Agile Data Modeling

09:12 The Challenges of Sustainability and Data Centers

11:19 The Need for a Digital Twin and Enterprise Intelligence

15:22 The Hype Cycles and the Role of AI and GenV

20:47 The Journey of a Chief Data Officer

25:49 The Importance of People and Business Outcomes

28:57 Key Takeaways

31:47 The Limitations of New Technology

32:33 Resistance to Change

33:18 Lean Thinking and Streamlining Processes

33:47 The Importance of Communication and Understanding

21 episodes

All episodes

The Praxi Pod

1
Andrew Ahn, Beyond the Model: Why the Future of AI Is a Data Curation Economy 21:05

5 weeks ago21:05

21:05

In this episode of the Praxi Pod, Andrew Turner and Andrew Ahn discuss the recent $15 billion investment by Meta in Scale AI, exploring its implications for the AI market. They delve into the importance of data quality over model size, the challenges of reinforcement learning, and the advantages of expert-driven data curation. The conversation also highlights compliance as a competitive advantage in AI development and offers insights on future-proofing AI strategies for organisations. Takeaways Meta's investment in Scale AI signifies a shift in AI focus. Data quality is crucial for effective AI and ML. Reinforcement learning assumes data is trustworthy, which is often not the case. Expert-driven data curation enhances model training and outcomes. Compliance should be integrated throughout the AI process, not just at the end. Specialisation in AI tools can lead to better productivity and effectiveness. High-quality data is essential for making informed decisions. Organisations need to adapt quickly to new data sources. Data curation can significantly improve operational efficiency. The future of AI lies in the data curation economy. Chapters 00:00 Introduction to AI Investment Trends 06:09 Reinforcement Learning and Its Challenges 11:56 Compliance as a Competitive Advantage 17:57 The Role of Data Curation in AI Success…

The Praxi Pod

1
Ali Khan, The Strategic Importance of Data in Business 1:18:22

6 weeks ago1:18:22

1:18:22

In this conversation, Andrew Turner and Ali Khan discuss the evolving role of Chief Data Officers (CDOs) in the context of AI and data management. They explore the recognition of CDOs, the challenges they face, and the importance of data in decision-making. Ali shares insights on the transformation of data roles, the balance between transformation and line management, and the growing trust in AI for decision-making. The discussion highlights the significance of data as a core asset in organizations and the need for continuous evolution in data practices. Ali covers the evolution of AI, particularly in relation to the Turing Test and its implications for businesses. He emphasises the importance of understanding the risks associated with AI integration, the growing customer expectations, and the fear of missing out (FOMO) in adopting AI technologies. The discussion also covers the critical role of data quality, the challenges of explainability and bias in AI, and the skills gap in AI development. Overall, the conversation highlights the complexities and considerations businesses must navigate in the rapidly evolving AI landscape. We also discuss the rapid evolution of AI in software development, the implications for the future of work, and the critical importance of AI ethics and governance. Highlighting the shift towards hybrid organszations where AI and human workers collaborate, the need for responsible AI practices, and the challenges of establishing ethical frameworks for AI behaviour. Emphasizing the transformative potential of AI while acknowledging the ethical dilemmas it presents. Takeaways The CDO role is gaining recognition but still faces challenges. Data management is crucial for making informed decisions. Transformation in data roles is necessary for organizational success. AI is reshaping the landscape of data management. Trust in AI is built through demonstrated value and results. Gut decisions are valid but should be supported by data. The CDO role involves both transformation and ongoing management. Data is a fundamental asset for organizations. Continuous evolution in data practices is essential. Collaboration and education are key in adopting AI solutions. The Turing Test has evolved, and AI can now mimic human interaction convincingly. Understanding the business value of AI is crucial for successful implementation. AI introduces risks and uncertainties that must be managed carefully. Customer expectations for AI capabilities are rising, making it essential for businesses to adapt. FOMO is driving many organizations to adopt AI without fully understanding its implications. Data quality is the most significant factor in the success of machine learning models. Explainability in AI remains a challenge, complicating trust and accountability. Bias in AI models can have serious ethical implications that need to be addressed. Integrating traditional models with AI can enhance robustness but requires careful planning. The skills gap in AI development is a significant barrier that organizations must overcome. AI can autonomously add code to existing software. The future is hybrid with augmented organizations. AI ethics is crucial for our future. Responsible AI is ethics in practice. AI governance encompasses ethics, safety, and accountability. Data governance should extend to AI governance. AI will become ubiquitous like big data. Philosophy is going to eat AI. We need a common ethical framework for AI agents. AI ethics is moving faster than our understanding. Sound Bites "It's about data. It's about this thing called AI." "There's a good understanding of the CISO role." "It's not a one and done, right?" "Gut decisions are real, and I rely on that." "We need to take our colleagues on that journey." "We're approaching that point, aren't we?" "If you don't have it now, it's just table stakes." "The FOMO is of a couple of flavors." "The biggest consideration is the data." "AI is not some sort of fairy dust." "You have to fight the urge to over-engineer." "AI ethics is crucial for our future." "Responsible AI is ethics in practice." "Data governance should extend to AI governance." "AI will become ubiquitous like big data." "Philosophy is going to eat AI.” Chapters 00:00 Introduction and Background 03:08 Recognition and the Role of CDOs 05:54 The Evolution of the CDO Role 09:13 Transformation vs. Line Management in Data Roles 11:57 The Importance of Data in Decision Making 14:57 AI and Its Impact on Data Management 18:11 The Journey of Trusting AI in Decision Making 28:14 The Evolution of AI and the Turing Test 30:08 Business Implications of AI 33:37 Understanding AI Risks and Uncertainties 35:13 Customer Expectations and AI Integration 37:26 FOMO in AI Adoption 39:19 Data Quality and Machine Learning 40:58 The Challenge of Explainability in AI 42:00 Bias and Ethical Considerations in AI 48:26 Integrating Traditional Models with AI 49:44 The Skills Gap in AI Development 56:28 The Evolution of AI in Software Development 01:00:08 The Future of Work: Hybrid Organisations 01:02:59 AI Ethics and Governance: Navigating the New Landscape Ali is a veteran multi-industry Data & AI thought leader with over 25 years of experience, including senior leadership positions at Scholastic, Verizon and Experian Consumer Services. He has started, scaled and operated multiple organisations and is an expert in all aspects of running a successful Data & AI practice - cultural, organisational and technical - ensuring that the group aligns precisely with business outcomes for maximal impact. Ali has led world-class, mission-driven teams of 100+ to deliver transformational data platforms and innovative products - realizing $100m+ in revenue uplift through optimisation, personalisation and monetisation. He is highly competent at data strategy, AI ethics, platform architecture, personalization and privacy compliance. As a recognised industry leader, Ali is also engaged in executive advisory for industry organisations, startups and venture capital firms. You cannot connect with Ali here https://www.linkedin.com/in/khana/…

The Praxi Pod

1
Ako Sabir, Transforming Business with Data and AI 1:03:05

7 weeks ago1:03:05

1:03:05

In this episode of Praxi Pod, host Andrew Turner speaks with Ako Sabir about his extensive career in business transformation, focusing on the role of data and technology, particularly in the insurance sector. They discuss the unique challenges and opportunities within insurance, the critical importance of data in risk assessment, and the impact of AI on underwriting and claims processes. The conversation also touches on the necessity of regulatory compliance, the evolving awareness of leadership regarding technology, and the balance between innovation and risk management. Ako shares insights on the importance of educating leadership on AI and the cautious approach needed for proof of concepts in integrating new technologies. In this conversation, the speakers delve into the complexities of implementing AI and technology in business, emphasising the importance of understanding use cases, operationalisation, and governance. They discuss the challenges faced in regulated industries and the necessity of a structured approach to data and technology strategies. The conversation also touches on the future of AI, the need for responsible use, and the significance of engaging leadership in driving transformation. Takeaways - Ako emphasises the importance of change and transformation in his career. - He has worked across various sectors, focusing on data and technology for business transformation. - Insurance presents unique challenges and opportunities for innovation. - Data is fundamental in understanding risk and pricing in the insurance industry. - AI can significantly enhance underwriting and claims processes. - Regulatory compliance is a major challenge for insurance companies. - Leadership in organisations is increasingly aware of the need for data and AI. - There is a balance to be struck between innovation and risk management. - Organisations must educate their leadership on the implications of AI. - Proof of concepts should be approached with caution, focusing on practical applications. Invest time in understanding use cases before proof of concept. - Operationalising AI requires a clear governance framework. - Engage stakeholders early in the process for successful implementation. - Data quality and trust are critical for AI initiatives. - Business transformation is essential for successful AI adoption. - Leadership engagement amplifies the impact of AI projects. - Avoid chasing trends; focus on practical applications of AI. - Incremental scaling of AI solutions is more effective than large-scale rollouts. - AI should augment human decision-making, not replace it. - The future of AI involves navigating complexities and ensuring accountability. Chapters 00:00 Introduction to Ako Sabir and The Praxi Pod 03:01 Career Journey and Transformation Focus 06:00 Insights on the Insurance Sector 09:06 Data's Role in Insurance 11:59 Challenges in Financial Processes 14:58 Adoption of AI in Underwriting and Claims 18:03 Navigating Regulatory Compliance 21:04 Leadership and Technology Awareness 24:09 Balancing Innovation and Risk 27:11 Proof of Concepts and AI Integration 36:11 Navigating Technology Implementation Challenges 43:12 Operationalising AI in Regulated Industries 50:55 Transforming Business Through Data and AI 59:29 The Future of AI and Business Transformation…

The Praxi Pod

1
Gaurav Chawla and Vrashank Jain from Dell Technologies joining The Praxi Pod LIVE from DTW Las Vegas 20:59

9 weeks ago20:59

20:59

In this conversation, Andrew Turner hosts Vrashank Jain and Gaurav Chawla from Dell Technologies to discuss the evolution of AI solutions, particularly focusing on the AI Factory 2.0. They explore how Dell is bridging the gap between AI and data, the importance of decentralised data processing at the edge, and the rise of generative AI. The discussion also highlights Dell's internal transformation, the prioritisation of use cases, and the future of AI and data management. Takeaways - AI Factory 2.0 focuses on bringing AI closer to data. - Decentralised data processing is essential for effective AI. - Generative AI is becoming more accessible to various industries. - Data is the fuel for AI, requiring seamless integration. - Companies should prioritise use cases that align with their core business. - AI is impacting all aspects of life, from industry to personal use. - Dell's AI solutions are designed for both large enterprises and smaller companies. - The transition to unstructured data is crucial for generative AI. - Internal transformation at Dell is guiding customer solutions. - The future of AI involves curating and managing diverse data types. Chapters 00:00 Introduction to Dell Technologies and AI Factory 02:08 AI Factory 2.0: Bridging Data and AI 06:10 Decentralised Data Processing and AI at the Edge 10:00 The Rise of Generative AI and Its Impact 13:57 Internal Transformation and Use Case Prioritisation 17:57 The Future of AI and Data Management…

The Praxi Pod

1
Angus Gow, The Art of Programming in the Age of AI 58:18

10 weeks ago58:18

58:18

In this episode of the Praxi Pod, Andrew Turner spends time with Angus Gow, exploring his extensive background in AI, data integrity, and the evolving landscape of technology. Angus shares insights from his career, emphasising the importance of data quality in AI applications and the integration of AI in logistics. The conversation delves into the current state of AI, its rapid growth, and the creative aspects of programming, highlighting the need for innovation and adaptability in the tech industry. In this conversation, Andrew and Angus explore the multifaceted implications of AI in society, focusing on ethical considerations, the evolution of human-AI interaction, and the future of entrepreneurship. They discuss the potential for AI to manipulate human behaviour, the importance of ethical development practices, and the contrasting visions of AI's future as depicted in popular culture. The dialogue also touches on the consolidation of AI tools in business, the impact on development teams, and the transformative potential of AI for aspiring entrepreneurs. Takeaways AI has been a long-standing interest for Angus. Data integrity is crucial for successful AI applications. The evolution of AI has been rapid in recent years. Logistics presents unique challenges that AI can help solve. Creativity is essential in programming and technology development. The current state of AI is reminiscent of the early internet days. Understanding data management is key to leveraging AI effectively. AI's limitations include a lack of divine inspiration. The hype around AI can be overwhelming and distracting. Future job skills will focus on creativity and adaptability. AI can manipulate human behavior, raising ethical concerns. The ethics of AI should focus on its potential to manipulate. AI technologies are powerful but must be used responsibly. Future AI may resemble Star Trek more than Terminator. Consolidation of AI tools is essential for effective business use. AI can enhance productivity but requires skilled developers. Junior developers may struggle with AI tools without experience. Prototyping with AI can lead to rapid development but may create technical debt. AI can lower barriers to entrepreneurship, enabling more people to start businesses. Creativity will differentiate businesses in an AI-driven future. Sound Bites "AI goes long, a long way back for me." "It's so much cheaper to get data right at the start." "We're still figuring out the best use of AI." "Programming is an art form." "AIs are not good at divine inspiration." "It's trying to make you happy as well." "These are powerful technologies." "I think it's actually Star Trek." "We've already rebranded it, it's Dreamcoding now." "AI will be all over that." "It's good, it's good, it's good. Fantastic." "You start again. You go, you just get them." Chapters 00:00 Introduction and Background 04:01 The Evolution of AI and Personal Journey 12:01 Data Integrity and Its Importance 18:04 Logistics and AI Integration 23:58 Current State of AI and Future Prospects 29:56 The Creative Aspect of Programming and AI Limitations 32:20 The Ethics of AI Manipulation 34:12 The Role of AI in Human Interaction 36:36 Future of AI: Star Trek vs. Terminator 42:49 Consolidation of AI in Business 49:39 The Impact of AI on Development Teams 55:09 The Future of Entrepreneurship with AI Angus Gow is a highly respected CTO and technology strategist with over 25 years’ experience leading digital transformation across fintech, insurance, supply chain, and e-commerce sectors . He has built and scaled complex systems across a wide range of organisations—from high-growth startups to global enterprises—delivering platforms that power financial products, real-time analytics, and AI-driven decision-making. Angus is the founder of FlowFoundry.io, a product lab, advisory and services business focused on applying emerging AI and open-source technologies to deliver scalable, cost-efficient systems. His work bridges deep technical expertise—including enterprise architecture, data engineering, and cybersecurity—with commercial insight, having guided companies through trade sales, platform overhauls, and product innovation. With a hands-on approach to leadership and delivery, Angus has led global engineering teams of over 200 people and managed multi-million-pound technology budgets. His recent work focuses on developing methodologies and architectural patterns for safe, scalable AI in enterprise settings. Links https://flowfoundry.io https://anjin.digital…

The Praxi Pod

1
🔥 Insurance Data Roast Event, Where data disasters meet expert insights 48:08

19 weeks ago48:08

48:08

Welcome to the Praxi Insurance Data Roast with our expert panel of Alasdair Anderson, Edosa Odaro, Andrew Ahn and hosted by Andrew Turner. The conversation evolves around humorous anecdotes and insights from the insurance industry, focusing on data mishaps, algorithmic failures, and the challenges of legacy systems. The panelists share their experiences in a light-hearted roast format, discussing topics such as correlation versus causation, bizarre insurance claims, and the ongoing struggle with outdated technology. The session aims to entertain while shedding light on serious issues within the industry This conversation delves into the complexities of the insurance industry, focusing on the interplay between traditional actuarial practices and modern data science. It highlights the challenges of data management, the quirks of data usage in insurance, and the evolving role of technology in shaping the future of the industry. The discussion also touches on the dynamics between underwriters and data scientists, emphasizing the need for collaboration to enhance outcomes. Finally, it explores and explains Praxi Curation as a Service, which aims to improve data quality and accessibility for insurance companies. Chapters 00:00 Introduction to the Insurance Data Roast 04:51 When Algorithms Go Wild 09:57 Correlation vs. Causation 10:27 Claims Hall of Fame 14:05 Digital Dinosaurs 18:01 Data Privacy: The Emperor's New Clothes 22:13 Navigating Insurance and Financial Apps 24:30 The Quirky Side of Data and Death Lists 26:14 Interdepartmental Dynamics: Underwriters vs. Data Scientists 29:26 The Philosophy of Interdepartmental Warfare 32:56 Curation as a Service: Transforming Data Management 44:17 Future Trends in Insurance and AI Adoption…

The Praxi Pod

1
Love your Data with Praxi, CaaS Launch Event 46:26

23 weeks ago46:26

46:26

The Love Your Data event, hosted by Andrew Turner, features a panel of data experts discussing the future of data and AI. The event included an interactive Kahoot quiz to engage the audience and insights from panelists about the transformative impact of generative AI in business. The conversation delves into the integration of AI into management practices, emphasising the importance of data quality and ethical considerations. It discusses the current hype cycle surrounding AI technologies and the evolution of Agentic AI. The speakers highlight the need for a balance between innovation and responsibility, particularly in regulated industries. The introduction of Curation as a Service (CaaS) is presented as a solution for effective data management and classification, aiming to enhance productivity and governance in organisations. Expert panel is Morgane Calenca, Angus Gow and Andrew Ahn. Chapters 00:00 Introduction to the Love Your Data Event 03:04 Expert Panel Introductions and Backgrounds 07:04 Kahoot Quiz: Engaging the Audience 20:04 Panel Discussion: Future of Data and AI 22:01 Integrating AI into Management Mindset 26:20 Navigating the AI Hype Cycle 30:00 The Evolution of Agentic AI 35:10 Balancing Innovation with Responsibility 39:52 The Inspiration behind Curation as a Service 46:49 Introducing Praxi Curation as a Service (CaaS)…

The Praxi Pod

1
The Gift of Insight Series with Andrew Ahn 16:05

28 weeks ago16:05

16:05

We recorded a series of episodes with our Praxi Advisory Board and Andrew Ahn, our Founder & CEO to discuss what were their main takeaways from 2024, what they see as the learnings and what's happening in 2025. Enjoy this episode with Andrew Ahn recorded in early January 2025. In this episode of the Praxi - The Gift of Insight Series, Andrew Turner speaks with Andrew Ahn about the significant insights gained from 2024, particularly in the realm of generative AI and its maturation within various industries. They discuss the realistic expectations surrounding AI technology, the importance of data quality, and the evolving landscape of the insurance industry. Looking ahead to 2025, they share predictions about productivity, compliance, and the necessity for businesses to adapt to new realities. The conversation emphasises the critical role of data quality in achieving successful outcomes in analytics and decision-making. Chapters 00:00 Introduction and Overview of 2024 Insights 02:55 Generative AI: Maturation and Realistic Expectations 05:58 Looking Ahead: Predictions for 2025 09:00 Data Quality: The Foundation for Success 11:52 Insurance Industry: Adapting to New Realities 14:56 Final Thoughts and Predictions for the Future…

The Praxi Pod

1
The Gift of Insight Series with Morgane Calenca 19:56

28 weeks ago19:56

19:56

We recorded a series of episodes with our Praxi Advisory Board and Andrew Ahn, our Founder & CEO to discuss what were their main takeaways from 2024, what they see as the learnings and what's happening in 2025. Enjoy this episode with Morgane Calenca recorded in early January 2025. In this conversation, Andrew Turner and Morgane Calenca discuss the evolving landscape of data management and AI as they transition from 2024 to 2025. Morgane emphasises that while AI is becoming ubiquitous, it is not a panacea; rather, it is a tool that requires high-quality data to be effective. They explore the challenges of data quality, the importance of change management, and the need for collaboration across various teams to ensure successful data initiatives. Morgane also highlights the significance of defining ROI for data projects and the necessity of top management support in driving data transformation. Chapters 00:00 Introduction and Insights from 2024 03:00 The Role of AI in Data Management 05:55 Challenges of Data Quality and Legacy Systems 09:06 The Importance of Change Management in Data Strategy 11:54 Defining ROI in Data Initiatives 14:55 Collaboration Across Teams for Data Success…

The Praxi Pod

1
The Gift of Insight Series with Edosa Odaro 23:31

30 weeks ago23:31

23:31

We recorded a series of episodes with our Praxi Advisory Board and Andrew Ahn, our Founder & CEO to discuss what were their main takeaways from 2024, what they see as the learnings and what's happening in 2025. Enjoy this episode with Edosa Odaro recorded in late December 2024. In this episode of the Praxi - Gift of Insight Series, host Andrew Turner engages with Edosa Odaro to discuss the significant insights and challenges of 2024, particularly in the realms of technology and AI. They explore the overwhelming noise of information and the need for focus and value in 2025. The conversation delves into the adaptability of technology, the importance of partnerships, and the necessity of problem-solving in a rapidly changing environment. The episode concludes with reflections on the future outlook and the importance of prioritising meaningful objectives. Chapters 00:00 Introduction and Overview of 2024 02:47 The Noise of 2024: Insights and Challenges 05:55 Focus and Value in 2025 08:57 Tech Adaptability and Problem-Solving 11:45 Navigating the Chaos: Executive Challenges 15:08 Partnerships and the Future of Tech 17:58 Value-Driven Problem Solving 21:09 Conclusion and Future Outlook…

The Praxi Pod

1
The Gift of Insight Series with Alasdair Anderson 19:23

31 weeks ago19:23

19:23

We recorded a series of episodes with our Praxi Advisory Board and Andrew Ahn, our Founder & CEO to discuss what were their main takeaways from 2024, what they see as the learnings and what's happening in 2025. Enjoy this episode with Alasdair Anderson recorded in late December 2024. In this episode of Praxi - The Gift of Insight Series, host Andrew Turner engages with Alasdair Anderson to discuss the evolving landscape of AI and its implications for various industries. They reflect on the challenges faced in 2024, particularly the slow adoption of AI technologies in enterprises, and the economic hurdles anticipated in 2025. The conversation also delves into the upcoming DORA regulation and its potential impact on the financial services sector, emphasising the need for organisations to adapt to new compliance requirements. The episode concludes with insights on the future of AI and the importance of understanding its practical applications. Chapters 00:00 Introduction and Christmas Greetings 01:11 Reflections on AI Progress in 2024 07:25 Navigating Economic Challenges in 2025 11:30 Understanding DORA Regulation and Its Impact 19:54 Conclusion and Future Insights…

The Praxi Pod

1
The Gift of Insight Series with Roberto Maranca 16:44

31 weeks ago16:44

16:44

We recorded a series of episodes with our Praxi Advisory Board and Andrew Ahn, our Founder & CEO to discuss what were their main takeaways from 2024, what they see as the learnings and what's happening in 2025. Enjoy this episode with Roberto Maranca recorded in late December 2024. In this episode of the Praxi - The Gift of Insight series, Andrew Turner and Roberto Maranca discuss the significant insights and challenges surrounding data and AI as we approach 2025. They explore the rapid advancements in generative AI, the importance of resilience in data management, and the critical role of human decision-making in leveraging data effectively. The conversation emphasises the need for data leaders to translate data quality into actionable business value and foster critical thinking within their organisations. Chapters 00:00 Introduction to the Praxi - Gift of Insight Series 01:06 Insights on Data and AI in 2024 06:20 The Importance of Resilience in Data Management 10:10 The Role of Human Decision-Making in Data 12:55 Translating Data Quality into Business Value…

The Praxi Pod

1
Patrick Debois, Navigating the evolving intersection of human intelligence, automation, and AI Native Development 1:05:48

31 weeks ago1:05:48

1:05:48

In this episode of the Praxi Pod, host Andrew Turner speaks with Patrick Dubois about the evolving landscape of AI and technology. They discuss the hype surrounding generative AI, the importance of understanding its practical applications, and the need for organizations to adapt to new technologies. Patrick shares his journey through various roles in tech, emphasizing the significance of continuous learning and the intersection of AI with software engineering. The conversation also touches on the organizational structures needed to support AI initiatives and the implications for business operations. In this conversation, Andrew and Patrick delve into the evolving landscape of AI in software development, discussing the opportunities and challenges presented by new tools and methodologies. They explore the importance of collaboration, the need for continuous learning, and the role of AI in enhancing productivity while addressing its limitations. The discussion also touches on the future of engineering skills, the rise of AI agents, and the significance of knowledge management in navigating organizational changes and improving incident response. Chapters 00:00 Welcome to the Praxi Pod 10:04 Generative AI: Hype vs. Reality 22:06 The Intersection of AI and Software Engineering 27:59 Shifting Paradigms in AI Deployment 34:07 Organizational Structures for AI Teams 42:07 Exploring Opportunities in AI and Requirements Gathering 47:52 AI's Role in Continuous Learning and Governance 55:07 The Future of Engineering Skills and Organizational Change 01:01:45 The Rise of AI Agents and Knowledge Management Patrick Debois, often hailed as “the Father of DevOps,” is a Belgian Tech professional and thought leader renowned for pioneering the cultural and technical paradigm that unites software development and IT operations. Born and raised in Belgium, Debois initially trained in computer science and spent the early part of his career working in both development and system administration roles, giving him firsthand experience with the friction and communication gaps that often hindered effective software delivery. In the late 2000s, Debois became increasingly focused on streamlining the collaboration between development teams and operations teams—two traditionally siloed groups within IT organizations. He was inspired by the principles of Agile, continuous integration, and continuous delivery, as well as ideas presented by John Allspaw and Paul Hammond about bridging Dev and Ops at the Velocity Conference in 2009. Recognizing the need for a dedicated forum to explore and refine these concepts, Debois co-organized the first DevOpsDays conference in Ghent, Belgium, in 2009. This intimate gathering of practitioners and thinkers is widely regarded as the birthplace of the DevOps movement. From that seminal event, DevOps spread rapidly throughout the global IT community, with Debois serving as a key advocate, educator, and facilitator. He helped define the ethos of DevOps, emphasizing culture, collaboration, automation, measurement, and sharing—often summarized as the “CAMS” principles. Debois’s approach highlighted the importance of breaking down silos, enhancing empathy, and encouraging continuous learning to improve software quality, delivery speed, and organizational resilience. Over the years, Debois has held various consulting and leadership roles at different technology companies, advising organizations on their DevOps transformations. He has spoken at numerous international conferences, written extensively on the topic, and maintained a strong presence in the DevOps and Agile communities. His influence extends beyond tooling and methodologies into the broader cultural changes that help organizations evolve and thrive in a fast-paced, technology-driven world. Today, Patrick Debois continues to shape the DevOps conversation through advocacy, research, and mentoring. His legacy endures in the global network of DevOpsDays events, the widespread adoption of DevOps practices, and the ongoing conversation around how best to integrate people, processes, and technology. Through his vision and community-building efforts, Debois remains a seminal figure in how modern IT organizations conceive, build, and deliver software. Renowned for his groundbreaking contributions to DevOps and DevSecOps, Patrick is once again at the forefront, navigating the evolving intersection of human intelligence, automation, and AI Native Development Patrick is currently the Principal Product engineer AI at Humans and code and can be found on Linkedin here https://www.linkedin.com/in/patrickdebois/ But also has a great Youtube channel with great content https://www.youtube.com/@jedi4ever Enjoy and if you listen to the FULL episode you will get Patrick's insight on his 2025 predictions…

The Praxi Pod

1
Stephen Harris : What's our readiness for AI, and how do we get there? 57:04

41 weeks ago57:04

57:04

In this episode of the Praxi Pod, host Andrew Turner speaks with Stephen Harris, a seasoned expert in data management and AI. They discuss Stephen's extensive background in the data space, the importance of data management for AI readiness, and the impact of regulatory compliance on data practices. Stephen emphasizes the need for organizations to validate their AI outputs, understand data ownership, and the evolving role of Chief Data Officers. The conversation also touches on the significance of data curation, classification, and the future of AI in organizations. Takeaways Organizations must test AI internally before external deployment. Data management is crucial for AI readiness. Regulatory compliance drives better data practices in industries. AI should be used to validate and improve data quality. Education on AI and data management is still lacking. Data ownership issues can create internal conflicts. The role of Chief Data Officers is evolving and critical. Data curation and classification are foundational responsibilities. Metadata management is essential for data confidence. The future of AI will see a shakeout based on data quality. Chapters 00:00 Introduction to Stephen Harris and His Journey 02:47 The Importance of Data Management and AI Readiness 05:54 Regulatory Compliance and Its Impact on Data Management 09:04 The Role of AI in Data Validation and Customer Experience 12:10 Understanding AI and Machine Learning in Business 14:54 The Need for Education in AI and Data Management 18:00 Validating AI Outputs and Managing Edge Cases 20:47 The Challenges of Data Ownership and Governance 24:05 The Role of Chief Data Officers in Organizations 27:08 The Future of AI and Data Management Roles 29:52 Data Curation and Classification in the AI Era 32:49 The Importance of Metadata and Data Quality 35:55 The Future of AI and Its Impact on Organizations…

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Tiankai Feng, The Impact of AI on Creativity and the Challenges of Ownership 41:08

46 weeks ago41:08

41:08

In this new episode of The Praxi Pod, Andrew Turner spends a very enjoyable time with Tiankai Feng talking about data governance and AI governance. Tiankai shares his approach to making data more approachable and fun, using his musical talents to create songs and parodies about data. They discuss the resurgence of data governance, driven by innovation and regulations. They also explore the challenges of governing AI and machine learning models, including data quality, bias, and ethical considerations. Tiankai emphasizes the importance of human oversight in AI governance. They touch on the adoption of AI in different industries and the role of small innovation hubs in driving progress. Tiankai also explains the concept of data mesh and its principles. Finally, Tiankai shares his role at ThoughtWorks in helping clients with data strategy and governance, including implementing data mesh projects. In this conversation, Andrew and Tiankai discuss the concept of data mesh and its relevance in today's data landscape. They explore the role of data governance and metadata management in ensuring data quality and usability. They also touch on the impact of AI on creativity and the challenges of ownership and responsibility in the AI era. The conversation concludes with a discussion on the future of AI and the need for organizations to embrace new technologies while considering legal and ethical implications. Chapters 00:00 Introduction and Background 02:15 The Resurgence of Data Governance 06:04 Challenges in Governing AI and Machine Learning Models 09:31 Adoption of AI Across Industries 13:29 Driving Progress in AI through Small Innovation Hubs 19:45 Understanding Data Mesh and its Principles 20:55 The Role of Human Oversight in AI Governance 21:10 The Concept of Data Mesh 23:24 The Evolution of Data Management 25:43 The Importance of Data Classification and Curation 28:36 The Role of Data Quality in Outcomes 29:26 The Challenges of Unstructured Data 30:30 The Impact of AI on Tedious Tasks 32:56 Motivating Data Owners and Providing Tools 36:57 The Boundaries of Human Creativity and AI 39:38 The Future of AI and Ethical Considerations Our guest Tiankai Feng, is a Data & Analytics leader and author of "Humanizing Data Strategy". He is currently the Data Strategy & Governance Lead in Thoughtworks Europe and the Head of Marketing of DAMA Germany. With 11+ years experiences in Data Analytics, Data Governance and Data Strategy, he found a passion for the human aspect of data: how to collaborate, communicate and be creative around data. He is passionate about making data more understood, approachable and fun through unconventional methods like music and memes. Links: Book: https://technicspub.com/humanizing-data-strategy/ LinkedIn: https://www.linkedin.com/in/tiankaifeng/ Youtube: https://www.youtube.com/kaifeng…

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Dan Sodergren, Embracing AI in the Future of Work 52:33

49 weeks ago52:33

52:33

In this episode of The Praxi Pod, Andrew and Dan discuss the future of work and the impact of AI and technology. They explore the gap in understanding about what jobs will look like in the future and the role of humans versus non-humans. They also discuss the resistance to change and the fear of losing control in organizations. Dan emphasizes the importance of embracing hybrid work and creating a more flexible and inclusive work environment. He also highlights the need for organizations to have an AI policy and train employees on how to use AI effectively. The conversation explores the role of AI in the future of work and the responsibilities of leaders and individuals in embracing and managing this technology. It emphasizes the need for learning and development, understanding the tasks to be done, and upskilling employees to drive innovation and change. The conversation also highlights the importance of leadership in driving digital transformation and the need for incentives to motivate individuals to embrace AI. It discusses the potential impact of AI on work-life balance, the importance of purpose and passion in work, and the potential for AI to create a more equitable society. Takeaways The future of work is being shaped by AI and technology, and organizations need to adapt to stay competitive. Hybrid work is here to stay, and organizations should embrace flexibility and create a more inclusive work environment. Leadership plays a crucial role in driving the adoption of AI and technology in organizations. Diversity and inclusion are not just moral imperatives, but also lead to better business outcomes. Having an AI policy and training employees on how to use AI effectively is essential for organizations. AI is revolutionizing the future of work, and individuals and organizations need to embrace and manage this technology. Learning and development, upskilling, and understanding the tasks to be done are crucial for driving innovation and change. Leadership plays a key role in driving digital transformation and creating a culture that embraces AI. Incentives are important to motivate individuals to embrace AI and become more productive. AI has the potential to create a more equitable society and allow individuals to focus on meaningful work. Chapters 00:00 Introduction and Busy Schedule 02:03 The Impact of AI and Technology on the Future of Work 08:56 Embracing Hybrid Work and Flexibility 13:29 The Role of Leadership in Driving Change 19:14 The Business Benefits of Diversity and Inclusion 21:37 The Importance of an AI Policy and Training 29:08 The Role of Learning and Development in the Future of Work 31:13 The Responsibilities of Leaders in Digital Transformation 32:47 Motivating Individuals to Embrace AI 33:45 AI's Impact on Work-Life Balance 39:01 The Power of Purpose and Passion in Work 43:12 AI's Potential to Create an Equitable Society…

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Alasdair Anderson, Data Access, Quality and Sovereignty still major hurdles for true AI adoption 32:57

1 year ago32:57

32:57

In this episode, Andrew Turner interviews Alasdair Anderson about the current state of the data space and the challenges and opportunities it presents. They discuss the explosive growth of data, the importance of data integrity and foundation, and the impact of data on different industries. They also delve into the challenges of access and quality in data, the role of artificial intelligence, and the need for real-time and high-quality information. They explore organizational changes and the skills gap, as well as the future of data workers and the challenges of data sovereignty. The episode concludes with a discussion on balancing innovation and practicality in AI adoption. Takeaways The data space has experienced explosive growth in recent years, with advancements in technologies like artificial intelligence revolutionizing industries and society. Access and quality of data are major challenges in the data space, with issues of data sovereignty and legal ramifications adding complexity to the adoption of AI. Organizations need to embed data workers with hybrid skills into their teams and focus on the practicality and purpose of AI adoption, considering cost and bottom-line impact. The future of data workers lies in conversational data, where AI technologies enable more productive and efficient interactions with data. Chapters 00:00 Introduction and Setting the Stage 01:00 The Explosive Growth of the Data Space 03:10 Challenges and Opportunities in the Data Space 05:02 The Importance of Data Integrity and Foundation 06:20 The Impact of Data on Different Industries 08:16 The Challenges of Access and Quality in Data 10:09 The Role of Artificial Intelligence in Data 11:35 The Importance of Real-Time and High-Quality Information 12:20 Organisational Changes and Skills Gap 17:34 Embedding Data Workers and Hybrid Skills 21:23 The Future of Data Workers and Conversational Data 22:01 The Challenges of Data Sovereignty and Legal Ramifications 29:43 Balancing Innovation and Practicality in AI Adoption 31:16 Considerations for AI Adoption: Cost and Purpose 32:17 Closing Remarks and Future Possibilities Alasdair Anderson, with over 20 years in data technology, has worked in major financial firms and now leads the EMEA region for Protegrity. A recognised expert in data management and anti-financial crime, he's won multiple industry awards and is part of the Global Scot Network, mentoring organisations expanding globally.…

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Edosa Odaro, Human impact, Value equations, Data stories, AI and insights from the Middle East 42:18

1 year ago42:18

42:18

Summary In this conversation, Andrew and Edosa discuss the challenges and opportunities in the data world. They emphasize the importance of aligning data strategies with organizational goals and asking the right questions to ensure value creation. They also highlight the need to consider the human dimension and the impact on the workforce. The conversation explores the rapid pace of change and the need for organizations to adapt and navigate the complexities of data and AI. Edosa provides insights into the Middle East market and the unique constraints and opportunities in the region. The conversation concludes with key takeaways, including the importance of not reinventing the wheel, involving the right people, and focusing on return on investment. Takeaways Align data strategies with organizational goals and ask the right questions to ensure value creation. Consider the human dimension and the impact on the workforce when implementing data and AI solutions. Adapt and navigate the rapid pace of change in the data world, considering the constraints and opportunities in different markets. Focus on not reinventing the wheel, involve the right people, and prioritize return on investment. Chapters 00:00 Introduction and Setting 00:46 Purpose of the Conversation 03:07 The Data World and Challenges 08:01 The Value Equation 09:18 Defining Value in Different Perspectives 11:40 Importance of Alignment and Asking the Right Questions 16:15 The Pace of Change and the Future Workforce 20:10 Navigating the Buzz and Constraints 24:49 Challenges and Opportunities in the Middle East 29:08 Top Priorities for Data Leaders 36:04 Summary and Takeaways Edosa is a highly accomplished data and AI leader, strategist, and investor, with extensive global experience. He's a Chief Data Analytics & Privacy Officer and serves on boards. With a strong academic background and a focus on people and culture, he's a published author, coach, and renowned global speaker, recognised with numerous prestigious awards.…

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Roberto Maranca, The Path to Chief Decision Officer 35:18

1 year ago35:18

35:18

In this conversation, Roberto Maranca discusses the role of data in business and the challenges of implementing data initiatives. He emphasises the importance of agile data modelling and the need for a digital twin and enterprise intelligence. Roberto also highlights the challenges of sustainability and data centres. He explores the hype cycles surrounding AI and GenAI and the role of a Chief Data Officer. Finally, he emphasises the importance of people and business outcomes and provides key takeaways for listeners. In this episode, Andrew speaks with Roberto Maranca, Data Officer at an energy business, about the challenges and considerations of implementing new technology and data-driven processes. They discuss the limitations of viewing new technology as a panacea and emphasize the importance of having a well-designed architecture. They also explore the resistance to change and the difficulty of switching off old systems. Additionally, they highlight the value of lean thinking and streamlining processes to create more customer value. Finally, they stress the significance of effective communication and understanding in data initiatives. Takeaways Data plays a crucial role in business and should be treated as a product that requires continuous improvement. Agile data modeling is essential for adapting to the complexity and changing demands of the business environment. Sustainability and the impact of data centers on CO2 emissions are important considerations for data leaders. The concept of a digital twin and enterprise intelligence can provide valuable insights and support decision-making. The hype surrounding AI and GenAI should be approached with caution, and the focus should be on translating these technologies into tangible business outcomes. The role of a Chief Data Officer evolves from focusing on dashboards to data to decision-making, with a strong emphasis on understanding the business and translating data initiatives into business value. Viewing new technology as a panacea is a mistake; it is important to have a well-designed architecture and consider the limitations of any new tool. Resistance to change is common, and organizations often struggle with switching off old systems. Applying lean thinking and streamlining processes can help create more customer value and improve efficiency. Effective communication and understanding are crucial in data initiatives to avoid miscommunication and alignment issues. Chapters 00:00 Introduction and Background 02:10 The Role of Data in Business 06:24 The Importance of Agile Data Modeling 09:12 The Challenges of Sustainability and Data Centers 11:19 The Need for a Digital Twin and Enterprise Intelligence 15:22 The Hype Cycles and the Role of AI and GenV 20:47 The Journey of a Chief Data Officer 25:49 The Importance of People and Business Outcomes 28:57 Key Takeaways 31:47 The Limitations of New Technology 32:33 Resistance to Change 33:18 Lean Thinking and Streamlining Processes 33:47 The Importance of Communication and Understanding With almost 30 years of IT and data experience, Roberto worked at Nissan, Ford, General Electric Capital, Lloyds Banking Group, and Schneider Electric. In 2023, he became Schneider Electric Energy Management BU's Data Officer, focusing on sustainability. He holds a master's degree in Aeronautical Engineering from "Federico II" Naples University and enjoys sailing, gardening, and cooking.…

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Andrew Ahn, Founder & CEO of Praxi Data, Solving business problems with Data and GenAI 23:32

1 year ago23:32

23:32

In this episode, our Host Andrew Turner interviews Andrew Ahn, founder and CEO of Praxi Data, about the importance of data and the challenges in the data industry. They discuss the hype cycle of data technologies and the need for good quality data. Andrew Ahn introduces the concept of generative AI and its role in solving data problems. He also provides practical advice for businesses in 2024. The episode concludes with a teaser for future episodes of the Praxi Pod. Chapters 00:00 Introduction and Background 03:01 The Importance of Data 04:05 The Hype Cycle of Data Industry 07:06 Challenges in Data Work Productivity 09:44 The Quantum Shift in Technology 11:49 The Need for Good Quality Data 13:34 The Role of Generative AI 19:27 Practical Advice for 2024 23:07 Conclusion Specialised in Big Data and governance, with roles at Waterline Data, Hortonworks, and NYSE Euronext. Founded Praxi, developed three Data Catalogs, and achieved over $60M in sales.…

The Praxi Pod

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The Praxi Pod Introduction with Host, Andrew Turner 2:06

1 year ago2:06