35 Leading Thought Leaders on Data Analytics Globally

Introduction

Every organisation on earth is sitting on a mountain of data and wondering why it is not telling them anything useful. The problem is almost never the data itself. It is the thinking, the frameworks, and the leadership culture around data that either unlocks value or buries it beneath dashboards nobody reads and reports nobody acts on. If you are searching for the people who are genuinely pushing that thinking forward, you are in the right place.

The global data analytics conversation has never been more active. According to research from McKinsey Global Institute, data-driven organisations are 23 times more likely to acquire customers, six times as likely to retain them, and 19 times as likely to turn a profit as their less analytically mature counterparts. Yet the same research finds that most organisations still struggle to translate analytical capability into business decisions. The gap between having data and using it well is not technological. It is human, cultural, and leadership-driven.

That is why the 35 voices in this guide matter. These are not the people selling software platforms or building dashboards for enterprise clients. These are the thinkers, researchers, educators, practitioners, and provocateurs who are reshaping how leaders, teams, and entire organisations think about data. They write books that change how CDOs approach governance. They build communities that bring rigour to data storytelling. They ask uncomfortable questions about whether the analytics revolution is actually serving the people it claims to serve.

This list was compiled with geographic and disciplinary diversity as explicit criteria. The field of data analytics has historically been dominated by a narrow slice of American male perspectives, and while some of those voices are on this list because they genuinely deserve to be, the list also includes practitioners from Brazil, India, the UK, the Netherlands, and voices from data journalism, algorithmic ethics, and data governance who rarely appear on these roundups. The result is a fuller picture of where the global conversation is actually happening.

Jonno White is a Brisbane-based leadership consultant, keynote speaker, and Certified Working Genius Facilitator. His work with leadership teams across schools, corporates, and nonprofits around the world is grounded in the same conviction that drives this list: the data exists, and the tools exist, and what is missing is the human conversation that turns insight into action. Jonno runs workshops and facilitates sessions that help leadership teams think more clearly and act more decisively.

To discuss how Jonno might support your team, email jonno@consultclarity.org.

Why Data Analytics Thought Leadership Matters

Most organisations are not short of data. They are short of the conceptual clarity to ask the right questions of it, the organisational courage to act on what it reveals, and the communication skills to translate findings into decisions. The thought leaders in this guide are the people who are addressing each of those gaps.

When a leadership team lacks data literacy, it makes decisions based on gut feel and disguises that process as strategy. When it lacks a data culture, it funds analytics teams and then ignores what those teams discover. When it lacks data ethics, it builds systems that optimise for efficiency while quietly causing harm to the people inside and outside the organisation. These are not technical problems. They are leadership problems, and the voices on this list are the ones who have spent years naming them clearly.

The cost of ignoring this conversation is not abstract. Gartner estimates that poor data quality costs organisations an average of USD 12.9 million per year. IBM's Institute for Business Value found that organisations with strong data cultures are 5.8 times more likely to retain customers and 4.6 times more likely to attract the right talent. These are not technology metrics. They are leadership outcomes.

Following the right voices in this space does not mean consuming every article they publish. It means building a mental model of how data-driven organisations actually work, absorbing frameworks that challenge how you currently think about decisions, and connecting with a global community of practitioners who are solving the same problems your organisation faces.

Organisations can bring Jonno White in to deliver keynotes and facilitated sessions that bridge the gap between data insight and leadership action. Email jonno@consultclarity.org.

How This List Was Compiled

Every person on this list was selected based on three criteria. First, genuine credentials: they have published original research, authored recognised books, built significant communities, founded influential organisations, or held senior roles that give their perspective real weight. Second, disciplinary diversity: the list deliberately spans data governance, data engineering, decision intelligence, data storytelling, algorithmic ethics, data journalism, data literacy, and data strategy, because these are the subfields that together make up the modern data analytics conversation. Third, geographic diversity: the list includes voices from the USA, UK, Brazil, India, the Netherlands, and the global public sector, with a deliberate effort to reduce the US-centric bias that plagues most lists of this kind.

This is not an exhaustive directory of every credentialled data professional. It is a curated starting point for any leader, team, or organisation that wants to understand where the best thinking in data analytics is currently coming from.

For more on building high-performing leadership teams that can act decisively on data insights, check out my blog post '50 Best Thought Leaders in Technology (2026)' at consultclarity.org/post/50-best-thought-leaders-in-technology-2026.

Category 1: The Data Strategy and Leadership Architects

These seven people are thinking at the highest level of what it means to build an organisation that actually runs on data. Their work spans data strategy, data culture, data monetisation, and the leadership behaviours that separate data-mature organisations from those still struggling to move from reporting to insight.

1. Tom Davenport

One of the original voices at the intersection of management thinking and data analytics, Tom Davenport has shaped how organisations conceptualise their relationship with data for more than three decades. As the President's Distinguished Professor of Information Technology and Management at Babson College, inaugural faculty director of the Metropoulos Institute for Technology and Entrepreneurship, and a Research Fellow at the MIT Initiative on the Digital Economy, his work bridges rigorous academic research and practical business application.

Davenport is the author of 'Competing on Analytics,' co-authored with Jeanne Harris, which became one of the most influential management books of the early data revolution. His frameworks for analytics maturity, the role of data scientists, and the governance of AI remain core references for any leader building an analytical capability from the ground up. His 2026 research with Randy Bean on executive attitudes toward AI investment continues to surface the gap between enthusiasm and rigour in data-driven leadership.

2. Doug Laney

Few people have done more to shift the way organisations think about data as a strategic asset than Doug Laney. As a Distinguished Research Advisor at West Monroe Partners and a former Gartner analyst, he has been championing the idea that data has economic value for decades, long before it became a mainstream conversation.

Laney's book 'Infonomics' introduced a rigorous framework for measuring, managing, and monetising information as a genuine enterprise asset. The frameworks he developed remain the most practical available for leaders who want to connect data investment to balance sheet value. His ongoing writing on data valuation, data market dynamics, and information strategy continues to challenge how CFOs and CDOs think about the numbers behind the numbers.

3. Randy Bean

Randy Bean has spent more than four decades as a practitioner, chronicler, and advisor at the intersection of data strategy and leadership. His annual surveys of senior executives on data and AI investment, published in Harvard Business Review and MIT Sloan Management Review with Tom Davenport, have become essential benchmarks for understanding how organisations actually approach data capability rather than how they say they do.

His book 'Fail Fast, Learn Faster,' co-authored with Tom Davenport, charts the history of data leadership in major organisations and draws lessons from both successes and failures that no case study can replicate. For any executive trying to understand why their data transformation is harder than the technology vendors suggested it would be, Bean's perspective is both sobering and actionable.

4. Caroline Carruthers

Caroline Carruthers is the co-founder of Carruthers and Jackson, a global data consultancy, and one of the most practically influential voices in data leadership in the UK. She was one of the first women to hold the title of Chief Data Officer in the UK public sector, having served in that role at Network Rail, which gives her writing and speaking a grounding in operational reality that purely academic voices often lack.

Her books, co-authored with Peter Jackson, including 'The Chief Data Officer's Playbook' and 'Data-Driven Business Transformation,' are field manuals for leaders trying to build data capability inside complex organisations. Her most recent book 'Halo Data,' also co-authored with Peter Jackson, introduces a new framework for understanding the full economic and social value of organisational data. She chairs the CDAO Summit and is one of the most active conveners of the senior data leadership community in Europe.

5. Bill Schmarzo

Known in the data community as the 'Dean of Big Data,' Bill Schmarzo has spent his career helping organisations understand what data is actually worth and how to extract that value systematically. His time at Dell EMC and in independent consulting has given him a perspective that is simultaneously strategic and deeply operational, rare in a field that often splits into ivory-tower theorists and pure technicians.

Schmarzo's book 'The Economics of Data, Analytics and Digital Transformation' and his Data Science Business Value Scorecard methodology are among the most used frameworks for connecting data investment to measurable business outcomes. His LinkedIn content regularly challenges leaders to move beyond data collection and toward genuine value creation, making him an essential voice for any organisation in the middle of a data transformation.

6. Jordan Morrow

Jordan Morrow is one of the most prominent global advocates for data literacy, having helped build and scale data literacy programmes at major organisations throughout his career. His book 'Be Data Literate' has become one of the standard references for leaders trying to build analytical capability across their organisations rather than just within a specialised analytics team.

His perspective that data literacy is a fundamental human skill for the 21st century, comparable to reading and writing, has shaped how organisations think about data education. His work as a former Global Head of Data Literacy at Qlik, and his ongoing advisory and speaking practice, have influenced the development of data literacy programmes across diverse industries. His advocacy for accessible, practical data education makes him a valuable voice for any leader trying to democratise analytical thinking beyond the data team.

7. Avinash Kaushik

Avinash Kaushik is one of the most influential independent voices in the intersection of data analytics and marketing, best known for his work as a digital marketing evangelist and author who spent years at Google helping organisations understand what their web and digital analytics data actually means for business performance.

His books 'Web Analytics: An Hour a Day' and 'Web Analytics 2.0' introduced rigorous analytical thinking to the marketing function at a time when most organisations were drowning in pageview data without understanding its implications. His framework for separating business objectives from KPIs and distinguishing between vanity metrics and actionable metrics has shaped how analysts across industries think about what to measure and why. His Occam's Razor blog remains one of the most cited resources in the field.

Category 2: The Data Engineers and Practitioners

These five people represent the technical and operational foundation of data analytics. They are shaping how data is collected, cleaned, engineered, and delivered to the people and systems that need it.

8. Zhamak Dehghani

Zhamak Dehghani introduced the concept of 'data mesh' to the world while at Thoughtworks, fundamentally changing how enterprises think about distributed data ownership. Her argument that centralised data platforms create the same bottlenecks as centralised software teams has sparked one of the most significant architectural debates in enterprise data in the last decade.

She is now the founder and CEO of Nextdata, where she is building the infrastructure to make data mesh a practical reality for organisations rather than a theoretical framework. Her book 'Data Mesh,' published by O'Reilly, is the defining text on the topic. The fact that she moved from writing about the idea to building a company around it makes her one of the most credible voices at the intersection of data architecture and organisational design.

9. Joe Reis

Joe Reis is the co-author of 'Fundamentals of Data Engineering,' co-authored with Matt Housley and published by O'Reilly, which has become the standard reference for the rapidly maturing discipline of data engineering. His ability to synthesise a complex and fast-moving technical field into clear, practitioner-friendly frameworks has made him one of the most trusted voices for data teams navigating the modern data stack.

Beyond the book, Reis is an active voice on LinkedIn and in the data community, consistently pushing back against hype and grounding conversations in what actually works in production environments. His commentary on the gap between what tool vendors promise and what data teams actually need is refreshingly honest and makes him essential reading for anyone building or managing a data team.

10. Barr Moses

Barr Moses is the co-founder and CEO of Monte Carlo, the company she built to address one of the most persistent and expensive problems in data analytics: data downtime, the periods when data is wrong, missing, or unreliable without anyone knowing. Her work has effectively created and then led the data observability category.

Her writing on data reliability, data quality at scale, and the future of data and AI infrastructure is grounded in what she has seen working with hundreds of enterprise data teams. Her 2026 predictions on AI investment and data quality demonstrate the breadth of her perspective beyond pure product marketing. For any leader concerned about whether their data can actually be trusted, her frameworks for data observability are the most practical available.

11. Zach Wilson

One of the most significant emerging voices in data engineering, Zach Wilson built a following of more than one million people across platforms by sharing deeply practical knowledge about data engineering at scale. His experience at Facebook, Netflix, and Airbnb gives his technical perspectives a production-grade credibility that distinguishes him from many analytics educators.

Wilson is the founder of DataExpert.io and creates content on data engineering fundamentals, career development in data, and the mental health challenges of working in high-pressure technical environments. His willingness to discuss the human side of technical work alongside the technical content itself makes him one of the most relatable and distinctive voices for data practitioners navigating the current landscape.

12. Kirk Borne

Kirk Borne is one of the most prolific and consistently active voices in the global data science and analytics community. His background as an astrophysicist who spent twenty years supporting NASA data systems, combined with his time as Principal Data Scientist at Booz Allen Hamilton, gives him a perspective that spans from fundamental scientific data methodology to applied enterprise analytics.

As founder of Data Leadership Group and Chief Science Officer at DataPrime, Borne has been continuously ranked as a top worldwide influencer in data science, big data, and AI since 2013. His forthcoming book 'AI Powered Digital Twins,' from Wiley in 2026, reflects his ongoing synthesis of data science with the next generation of analytical systems. For daily, substantive commentary on what is happening at the leading edge of data analytics, few voices are as consistent or as broadly engaged.

Category 3: The Data Storytelling and Communication Experts

These five voices have devoted their careers to closing the gap between insight and action through narrative, visualisation, and communication.

13. Brent Dykes

Brent Dykes is the author of 'Effective Data Storytelling,' published by Wiley in 2020, which has become the foundational text for anyone trying to turn data analysis into decisions and action. His framework for combining data, narrative, and visuals into coherent data stories is taught in organisations and universities around the world and has shaped how a generation of analysts communicates their findings.

As the founder of AnalyticsHero and a regular Forbes contributor, Dykes continues to develop the field of data storytelling with the rigour of someone who spent years at Omniture, Adobe, and Domo leading analytics teams before becoming an independent practitioner. His LinkedIn content in 2026 addresses the tension between AI-generated data communication and the human judgment required to make data stories genuinely persuasive. His webinars and workshops consistently fill because his material translates directly into improved analyst performance.

14. Mona Chalabi

Mona Chalabi is a data journalist, illustrator, and visualisation expert whose work challenges the assumption that data analytics is primarily a technical discipline. Through her work as a Guardian US data editor and her distinctive hand-drawn visualisations shared across social media, she has expanded who engages with data and why, reaching audiences who would never read a Gartner report.

Her ability to render complex statistical phenomena in forms that are both accessible and honest about uncertainty has earned her international recognition and has influenced how a new generation of data communicators think about their audience. Her TED talk on data literacy and statistical honesty has reached millions of viewers and remains one of the most compelling arguments for why data communication is a civic as much as a professional responsibility.

15. Kristen Sosulski

Kristen Sosulski is an Associate Professor at NYU Stern School of Business and a leading voice on data visualisation, data literacy, and the use of data in management decision-making. Her book 'Data Visualization Made Simple' provides a practical framework for business leaders and analysts who need to communicate data effectively without a background in graphic design or statistics.

Her research at the intersection of data communication and management education has shaped how business schools teach analytical thinking. Her perspective as an educator working with MBA students who will become the data-consuming leaders of major organisations gives her insights into the gaps between how data is produced by analysts and how it is received and interpreted by the people who need to act on it.

16. Kate Strachnyi

Kate Strachnyi is the founder of DATAcated, a data analytics community and education platform, and one of the most active connectors and conveners in the global data and analytics community. Her ability to identify emerging voices and create platforms for them to share their work has made her a significant force in shaping who gets heard in the data analytics conversation.

Her career history at Citigroup and Deloitte, combined with her work building the DATAcated community, gives her a perspective that bridges enterprise analytics practice and community-level data education. Her LinkedIn content consistently elevates voices and perspectives from underrepresented groups in the data community. Her work on data accessibility and data careers for non-traditional entrants is some of the most practically useful content in the space.

17. Bernard Marr

Bernard Marr is one of the most widely read voices on the business implications of data, AI, and emerging technology. His weekly Forbes column and regular data and AI briefings reach millions of readers globally. His ability to translate complex data science and AI concepts into clear, actionable insights for senior business leaders is unmatched in terms of reach and consistency.

Marr has authored more than 20 books including 'Data Strategy,' 'Big Data in Practice,' and 'Business Trends in Practice.' His particular contribution to the data analytics conversation is making data strategy accessible to the C-suite executives who fund data initiatives but lack the technical background to evaluate them. His 2025 analysis of the eight data trends defining 2026 and his ongoing commentary on AI and data at the executive level remain essential reading for non-technical business leaders.

Category 4: The Decision Scientists and Analysts

These five voices are focused on what data analytics actually exists to do: improve the quality of decisions. They examine the human, psychological, and methodological dimensions of turning data into better choices.

18. Cassie Kozyrkov

Cassie Kozyrkov founded the discipline of Decision Intelligence at Google, where she served as the company's first Chief Decision Scientist and personally trained more than 20,000 employees in data-driven decision-making. Her frameworks for separating good decision-making from good outcomes, and for understanding where human judgment must augment algorithmic outputs, are among the most practically useful in the analytics field.

Now CEO of Kozyr, her advisory firm, she works with senior leaders at organisations including NASA, Lenovo, and Gucci on building decision intelligence capabilities. She has been named a LinkedIn Top Voice in Technology for five consecutive years and her writing on Medium has reached millions of readers. Her distinctive ability to explain statistical and AI concepts with precision and wit makes her one of the most effective communicators in a field that often sacrifices one for the other.

19. Cindi Howson

Cindi Howson brings two decades of analytical rigour to the question of how organisations should select and deploy data and analytics tools. As a former VP of Research and Analyst at Gartner, where she authored the data and analytics maturity model and the Analytics and BI Magic Quadrant, she shaped how the global market thinks about analytics platforms. She is now Chief Data Strategy Officer at ThoughtSpot and host of The Data Chief podcast.

Her books 'Successful Business Intelligence: Unlock the Value of BI and Big Data' and 'SAP BusinessObjects BI 4.0: The Complete Reference' remain standard references in the field. Her perspective as someone who has assessed hundreds of analytics tools and implementations gives her an ability to cut through vendor claims and identify what actually drives analytical value in practice. Her podcast conversations consistently feature the most senior data executives in the world.

20. Seth Stephens-Davidowitz

Seth Stephens-Davidowitz occupies a unique position in the data analytics landscape: he uses data analysis to reveal the gap between what people say and what they actually do, think, and feel. His book 'Everybody Lies,' which analyses Google search data to surface hidden human behaviours, became a New York Times bestseller and introduced millions of general readers to the power and the limits of data analytics as a tool for understanding human behaviour.

His subsequent work and Substack newsletter continue to examine what data can and cannot tell us about the world, with a particular focus on the cognitive biases and social pressures that distort how people respond to surveys and self-report measures. For any analyst working with data that purports to measure human attitudes or behaviours, his work is both a methodological resource and a necessary challenge to overconfidence in data-driven conclusions.

21. Tricia Wang

Tricia Wang is a technology ethnographer and co-founder of Constellate Data, whose work challenges one of the most persistent myths in data analytics: that more data automatically means better decisions. Her research on 'thick data,' the qualitative, contextual, human stories that quantitative data cannot capture, has influenced how major corporations including Nokia and Nike think about the relationship between data and genuine insight.

Her TED talk on why big data needs thick data has reached millions of viewers and remains one of the most watched presentations on the limits of purely quantitative analysis. Wang's perspective is particularly valuable for leaders in industries where human behaviour is complex and contextual, including healthcare, education, and social services, where data analytics systems frequently produce technically correct but practically misleading results.

22. Daliana Liu

Daliana Liu is a data scientist and one of the most effective communicators about the realities of building a data career. Through her newsletter, social media presence, and The Data Scientist Show podcast, she has built a following of more than 100,000 people by sharing honest accounts of the challenges, successes, and learning experiences of working in data science at enterprise organisations.

Her content on career transitions into data analytics, the day-to-day realities of data science roles, and the skills that actually matter in practice fills a gap left by purely technical educators. For leaders building data teams, her perspective on what motivates and sustains data professionals is as valuable as any technical framework. For individuals entering the field, she is one of the most reliable guides to what the work actually looks like.

Category 5: The Data Ethics and Governance Voices

These five voices are calling out the risks of unexamined data analytics with intellectual rigour and practical urgency. Data analytics without ethics produces systems that optimise the wrong things. Without governance, it produces chaos.

23. Rumman Chowdhury

Rumman Chowdhury is one of the most credentialled and courageous voices at the intersection of data analytics, artificial intelligence, and accountability. Her work as a former Global Lead for Responsible AI at Accenture, as the founder of the Twitter AI META team, and now as co-founder and CEO of Humane Intelligence has made her a central figure in the global conversation about what it means to deploy data and AI systems responsibly.

Humane Intelligence is a non-profit organisation focused on AI auditing and evaluation, grounded in Chowdhury's conviction that the data analytics and AI community needs independent, technically rigorous auditing of the systems it builds. Her work on algorithmic audits, AI red-teaming, and the policy dimensions of responsible AI makes her essential reading for any leader who wants to understand the full risk profile of data-driven decision-making.

24. Sandra Wachter

Sandra Wachter is a Professor of Technology and Regulation at the Oxford Internet Institute and one of the world's foremost researchers on the legal, ethical, and societal implications of data analytics and algorithmic systems. Her research on counterfactual explanations, algorithmic transparency, and the right to explanation in automated decision-making has influenced both European regulation and corporate practice.

Her paper 'Counterfactual Explanations without Opening the Black Box,' co-authored with Brent Mittelstadt and Chris Russell, is one of the most cited works in the field of AI explainability. For legal teams, compliance officers, and senior leaders navigating the increasingly complex regulatory environment around data use, Wachter's work provides both the theoretical grounding and the practical implications that neither pure technologists nor pure lawyers can offer alone.

25. Brandeis Marshall

Brandeis Marshall is a Professor of Computer Science at Spelman College and the founder of DataedX, an organisation dedicated to making data science education more equitable and accessible. Her work sits at the intersection of data analytics practice and data justice advocacy, and her voice is one of the most important in the field for leaders who want to understand how data systems can amplify or mitigate structural inequality.

Her book 'DataKind' and her public commentary on social media consistently challenge the data community to examine whose interests its systems are actually serving. Her perspective is particularly important for leaders in public services, healthcare, and education, where algorithmic decision-making systems are increasingly being deployed in contexts that directly affect people's lives and opportunities.

26. Cathy O'Neil

Cathy O'Neil is the author of 'Weapons of Math Destruction,' which became one of the most important books in the data analytics field by documenting the ways in which algorithmic decision-making systems were causing real harm to real people, from credit scoring to criminal sentencing to teacher evaluation. Her background as a PhD mathematician and former Wall Street quantitative analyst gives her a technical credibility that pure social critics lack.

She is the founder of ORCAA, an algorithmic auditing consultancy. Her work demonstrates that the most important data analytics skills are not just technical but also ethical and critical, requiring practitioners to ask not only 'Does this model work?' but 'Should this model exist, and in whose interests is it operating?' Her voice is one of the most important in the field for any organisation deploying automated decision-making.

27. Lauren Maffeo

Lauren Maffeo is the author of 'Designing Data Governance from the Ground Up,' published by O'Reilly, and a practitioner-focused voice on how organisations build the structural foundations that allow data to be trusted, shared, and used effectively across teams and functions. Her work bridges the gap between data governance theory and the practical realities of organisations where data ownership is contested, data quality is inconsistent, and data cultures are still forming.

As a consultant with Upright Analytics, she works with organisations that are building data governance frameworks for the first time, bringing a practitioner's impatience with academic frameworks and a writer's ability to communicate complex governance concepts to non-technical audiences. Her LinkedIn content is consistently oriented toward the actual work of building data-ready organisations rather than the aspirational discourse of data transformation.

Category 6: The Data Quality and Infrastructure Specialists

These three voices address the foundational question of whether data can actually be trusted. Without reliable, well-structured data, all the strategy and storytelling in the world produces nothing.

28. Susan Walsh

Susan Walsh is founder of The Classification Guru and one of the most distinctive voices in the data quality and data cleansing space. Her work addresses one of the most persistent and least glamorous problems in data analytics: the fact that organisations cannot get meaningful insights from data that has not been consistently classified, cleaned, and structured.

Her book 'Between the Spreadsheets' introduced her 5D Methodology for data classification and cleaning, and her work has helped organisations from procurement to finance understand why data quality is a precondition for data value rather than a technical after-thought. Her candid and often humorous commentary on the realities of dirty data makes her one of the most approachable voices in a space that can feel impenetrably technical to non-specialists.

29. Scott Taylor

Scott Taylor, known as 'The Data Whisperer,' is the founder of MetaMeta Consulting and one of the most focused advocates for master data management as the foundation for any meaningful data analytics programme. His work has consistently made the case that without a shared understanding of core business entities such as customers, products, and locations, analytics investments are built on a fundamentally unstable foundation.

His book 'Telling Your Data Story' addresses the human and narrative dimensions of making the case for master data management inside organisations, recognising that the biggest obstacle to data quality investment is rarely technical. His perspective on the relationship between data governance, master data, and analytical value is essential for any organisation that wonders why its analytics outputs are inconsistent, unreliable, or contradicted by different teams' reports.

30. Vin Vashishta

Vin Vashishta is the founder of V-Analytics and one of the most direct and practice-focused voices on the business strategy dimensions of data analytics and AI. His work addresses the gap that many data analytics thought leaders avoid: the disconnect between the technical excellence of data teams and the strategic value that business leaders actually require from analytics investment.

His writing and consulting practice focus specifically on helping senior business leaders understand how to frame data and AI investments in terms of competitive strategy rather than technical capability. His perspective challenges both data professionals who think in terms of models and algorithms and business leaders who think in terms of transformation announcements, asking both groups to focus on the specific, measurable business outcomes that analytics investment is supposed to produce.

Category 7: The Global and Emerging Voices

These five voices represent disciplines, geographies, and perspectives that the mainstream data analytics conversation frequently overlooks. Their inclusion here is not tokenistic. It reflects the reality that some of the most important data analytics work is happening outside the US-centric mainstream.

31. Ronald van Loon

Ronald van Loon is one of the most recognised names in global data analytics education and advocacy. Based in the Netherlands, he brings a European and global perspective to a conversation that is often dominated by American voices. Consistently ranked among the top ten global influencers in big data, AI, and data science since 2013, his work as a speaker, advisor, and content creator reaches practitioners across industries and geographies.

Through his platform Intelligent World, van Loon advises data-driven businesses on strategy and helps organisations understand the practical implications of AI, machine learning, and advanced analytics. His LinkedIn content regularly synthesises global trends and translates them for business audiences, making him one of the most accessible entry points to the data analytics conversation for leaders without a technical background.

32. Marcus Borba

Marcus Borba is a data analytics consultant, speaker, and one of the most prominent data thought leaders in Latin America. His voice is a valuable counterpoint to the predominantly English-speaking analytics conversation, bringing perspectives on data analytics adoption, challenges, and opportunities in Brazil and across emerging markets that are rarely represented in mainstream global roundups.

He has been consistently named among the top global influencers in big data, data science, and AI, and his advisory work has helped organisations in Brazil and internationally build data strategies that reflect the specific organisational and cultural contexts of their markets. For leaders operating in or with Latin American markets, his perspective on data analytics in that context is both practically useful and simply underrepresented elsewhere.

33. Ganes Kesari

Ganes Kesari is the co-founder of Gramener, a data visualisation and analytics consultancy based in India, and one of the most prominent voices at the intersection of data analytics, data storytelling, and business strategy in Asia. His work with organisations across sectors has given him a perspective on how data insights are adopted and resisted inside real organisations that is grounded in hundreds of client engagements.

His writing on the leadership and cultural dimensions of becoming data-driven draws on case studies from Indian and global organisations that reflect a perspective underrepresented in the predominantly American data analytics literature. His LinkedIn content regularly addresses the gap between analytical capability and organisational decision-making, making him a valuable voice for leaders in any geography trying to understand why data insights fail to change behaviour.

34. Sundas Khalid

Sundas Khalid is a Senior Data Scientist at Google and one of the most effective mentors and educators in the data analytics community. Through her YouTube channel, LinkedIn content, and The Data Scientist Show, she shares practical knowledge about data science, career development, and the experience of building a data career as a woman of colour in a field that has historically lacked diversity.

Her ability to make complex data science concepts accessible to beginners while maintaining rigour for experienced practitioners makes her content unusually valuable. Her work on career transitions into data analytics has helped thousands of people enter the field from non-traditional backgrounds, and her focus on the human dimensions of data careers distinguishes her from the purely technical educators who dominate most data content.

35. Peter Jackson

Peter Jackson is the co-founder of Carruthers and Jackson and a serial Chief Data Officer who has led data transformations at organisations including Legal and General Investment Management and Southern Water. Alongside Caroline Carruthers, he has co-authored several books that have become standard references for senior data leaders, including 'The Chief Data Officer's Playbook' and 'Data-Driven Business Transformation.'

His perspective combines deep operational experience with strategic frameworks for data leadership that are grounded in real organisational complexity. As an active speaker and advisor on data governance, data strategy, and the leadership behaviours that separate data-mature organisations from those still struggling to move from data collection to data value, his voice is one of the most practically useful in the European data leadership community. His co-founding of the Chief Data Officers' Summer School, with an international alumni of 1,000 data leaders, reflects his commitment to building the next generation of data leadership capability.

Notable Voices We Almost Included

Several practitioners were seriously considered for this list and represent genuine thought leadership in the field. Anand S, co-founder of Gramener alongside Ganes Kesari, brings deep expertise in data visualisation and narrative analytics from an Indian perspective, and his work on data products and analytics for social impact is highly regarded. His recent focus has shifted toward broader data and AI strategy work, moving slightly away from the specific data analytics practitioner content that anchored his earlier reputation.

Hilary Mason, the former VP of Machine Learning at Cloudera and founder of Fast Forward Labs, is one of the most respected names in data science. Her current work at Hidden Door, a gaming company using AI narrative generation, reflects a genuine shift in focus away from analytics toward generative AI applications, which is why she was not included in a list focused on data analytics specifically. Gregory Piatetsky-Shapiro, founder of KDnuggets, which remains one of the most visited resources in the data science community, was a genuine pioneer of the field. His current focus at KDnuggets is primarily curatorial rather than original thought leadership, which distinguished him from the voices on this list.

Bill Franks, a long-time analytics leader and author of 'Taming the Big Data Tidal Wave' and 'The Analytics Revolution,' brings a practitioner's perspective from healthcare and financial services analytics. His content output has been less consistent in 2025 and 2026, which is why he was not included despite his strong foundational credentials. Thomas Redman, known as 'the Data Doc,' has spent decades advocating for data quality as a leadership priority, with books including 'Data Driven' and regular Harvard Business Review contributions. His focus has recently shifted heavily toward the intersection of AI and data quality, which is genuinely important but represents a narrower slice of the broader data analytics landscape this list addresses.

Common Mistakes to Avoid When Engaging With Data Analytics Thought Leadership

The biggest mistake most leaders make when engaging with the data analytics thought leadership landscape is treating thought leaders as technology advocates rather than conceptual challengers. Many of the most prominent voices in this space are associated with companies, platforms, or tools, and their content naturally reflects those associations. This does not invalidate their thinking, but it does mean that the reader must apply independent judgment about which parts of their perspective reflect genuine insight and which parts reflect commercial interest.

The second mistake is following only the voices that confirm what your organisation already believes. If your analytics team is primarily focused on dashboards, the natural instinct is to follow voices who write about dashboards. But the most valuable thought leadership is often the voice that challenges the entire frame: Cathy O'Neil asking whether the metric you are optimising for is actually the right one, or Tricia Wang asking whether your quantitative data is missing the qualitative context that would change your conclusion entirely.

The third mistake is following the biggest names without checking whether their perspective is still current. Data analytics is a fast-moving field, and a thought leader who was essential reading in 2020 may have shifted their focus or their voice may have been superseded by developments they did not anticipate. The list in this guide was explicitly assembled to include voices who are active and current in 2025 and 2026, not voices who were influential five years ago and have since moved on.

A fourth common mistake is treating data analytics thought leadership as a consumption activity rather than a conversation. The most effective way to engage with the voices on this list is not to passively absorb their content but to bring their frameworks into your organisational discussions, test their arguments against your specific context, and push back where your experience contradicts their conclusions. Thought leaders are not oracles. They are provocateurs, and the value they provide is most fully realised when their ideas are actively debated rather than reverently received.

Finally, many leaders make the mistake of treating data literacy as something only analysts and data teams need to develop. Several voices on this list, particularly Jordan Morrow, Kate Strachnyi, and Lauren Maffeo, are making the argument that data literacy is a leadership capability, not a technical one, and that organisations where senior leaders cannot engage critically with data will continue to make decisions that their data does not actually support.

Implementation Guide: Building Your Data Analytics Reading and Following Practice

The most valuable thing you can do immediately is select three voices from this list whose perspective most directly addresses your organisation's current challenge. If your challenge is data governance, start with Caroline Carruthers, Lauren Maffeo, and Peter Jackson. If your challenge is data storytelling and executive communication, start with Brent Dykes, Mona Chalabi, and Kristen Sosulski. If your challenge is data strategy and organisational maturity, start with Tom Davenport, Randy Bean, and Doug Laney. Do not try to follow all 35 simultaneously. Depth of engagement with a few voices is more valuable than shallow exposure to many.

The second step is to distinguish between the platforms on which each voice is most active and most valuable. Several voices on this list do their best work on LinkedIn, where they publish long-form analysis, respond to questions, and engage with other practitioners. Others are more valuable through their books, which provide frameworks that short-form social content cannot. Tom Davenport's books, Brent Dykes' 'Effective Data Storytelling,' Zhamak Dehghani's 'Data Mesh,' and Cathy O'Neil's 'Weapons of Math Destruction' are all works that reward slow, deliberate reading rather than quick consumption.

The third step is to create structured opportunities to bring analytical frameworks into your team's regular working conversations. A monthly discussion of one article, one framework, or one challenge from the voices on this list produces more change than hours of passive reading. Share a piece by Barr Moses on data quality with your leadership team and ask: where in our organisation does this describe us? Use Seth Stephens-Davidowitz's work on data and human behaviour to challenge how your team interprets customer satisfaction surveys. Use Rumman Chowdhury's questions about algorithmic accountability to pressure-test any automated decision-making system your organisation is considering.

The fourth step is to engage with the live communities these voices are building. Kate Strachnyi's DATAcated community, Caroline Carruthers' CDO Summer School, Zhamak Dehghani's events around data mesh and Data 3.0 concepts, and the growing Women in Analytics and Women in Data communities all offer opportunities to learn from practitioners who are at the same stage of their analytical journey as your organisation.

The fifth step is to translate what you learn into a specific, prioritised question about your organisation's data capability. The data analytics thought leadership landscape is vast and can easily produce overwhelm rather than clarity. The discipline that makes it valuable is the habit of asking: what is the one thing from what I have just read that my organisation should do differently, and who needs to hear it?

Organisations can bring Jonno White in to facilitate leadership conversations that bridge analytics insight and team action. As a keynote speaker and workshop facilitator who has worked with leadership teams across schools, corporates, and nonprofits around the world, Jonno helps teams move from insight to action.

Email jonno@consultclarity.org. International travel for facilitated sessions and workshops is often far more affordable than expected. Many organisations find that flying Jonno in to deliver a focused offsite or leadership session costs less than engaging a local provider for an equivalent outcome. Whether virtual or face to face, reach out today.

Frequently Asked Questions

What is data analytics and how is it different from data science?

Data analytics is the process of examining datasets to draw conclusions about the information they contain, typically to support specific business decisions. Data science is a broader discipline that encompasses data analytics but also includes predictive modelling, machine learning, and algorithm development. Most of the voices on this list work across both fields, but their common ground is the question of how data generates insight and how insight generates action.

Who are the most influential data analytics thought leaders globally in 2026?

The most widely recognised include Tom Davenport, who has been writing about data-driven decision-making since the early 1990s; Bernard Marr, whose synthesis of data trends reaches millions of executives globally; Cassie Kozyrkov, who founded the discipline of Decision Intelligence at Google; Zhamak Dehghani, who created the data mesh architecture concept; and Brent Dykes, whose data storytelling frameworks are among the most widely used in corporate analytics. However, the most influential voices for a specific organisation depend on which dimension of data analytics that organisation is trying to develop.

How was this list compiled?

The list prioritises three criteria: genuine credentials in the form of published research, recognised books, or significant leadership roles; disciplinary diversity spanning data engineering, data governance, data ethics, data storytelling, and data literacy; and geographic diversity to reduce the US-centric bias that characterises most data thought leader lists. The aim was to identify voices who are active, credible, and genuinely shaping how practitioners and leaders think about data analytics in 2025 and 2026.

How do I choose which voices to follow if I am new to data analytics thought leadership?

Start with three voices that match your organisation's current priority. For data strategy fundamentals, Tom Davenport and Randy Bean are the most foundational. For data communication and making analytics insights land with non-technical audiences, Brent Dykes and Mona Chalabi are the most accessible. For understanding the risks and ethics of data-driven systems, Cathy O'Neil and Sandra Wachter are the most rigorous. From these starting points, each voice will naturally lead you to others.

Can I hire someone to facilitate data analytics and data-driven leadership workshops for my team?

Yes. While the voices on this list are primarily researchers, educators, and practitioners focused on the analytics field itself, Jonno White is a Brisbane-based leadership consultant and keynote speaker who works with leadership teams to build the culture, communication habits, and decision-making frameworks that allow data insights to generate genuine change. Jonno runs workshops and facilitated sessions that help leadership teams think more clearly and act more decisively on the information their analytics teams produce.

Email jonno@consultclarity.org to discuss how Jonno might support your team. International travel is often far more affordable than expected.

Why do so many data analytics initiatives fail to produce business value?

The most consistent finding across the research of voices like Tom Davenport, Randy Bean, and Cindi Howson is that data analytics initiatives fail not because of technical problems but because of leadership and cultural ones. Organisations fund analytics teams but do not change their decision-making processes. They build dashboards that no one looks at. They hire data scientists but do not give them access to the decisions that matter. The thought leaders on this list are, in various ways, all trying to solve this problem from different angles.

What is the difference between a CDO and a Chief Analytics Officer?

A Chief Data Officer is primarily responsible for the strategy, governance, and management of an organisation's data assets. A Chief Analytics Officer is primarily responsible for the analytical programmes and capabilities that generate insight from that data. In some organisations the roles are combined. Caroline Carruthers, Tom Davenport, and Doug Laney all have extensive perspectives on how these roles should be structured and where they belong in the organisational hierarchy.

Final Thoughts

Data analytics is not a technology initiative. It is a leadership discipline. Every organisation that has successfully become data-driven has done so because its leaders developed new habits: the habit of asking what the data says before making a decision, the habit of questioning whether the data is measuring the right thing, the habit of investing in the cultural and governance foundations that make data trustworthy, and the habit of communicating insights in ways that generate action rather than filing in inboxes.

The 35 voices in this guide are not a comprehensive map of the field. They are a set of well-chosen entry points into a conversation that is richer, more global, and more practically urgent than most roundups acknowledge. Start with the voices that speak most directly to your organisation's current challenge. Engage seriously with their frameworks. Bring their questions into your leadership team's regular discussions.

The gap between data capability and data impact is not a technology problem. It is a leadership problem. And the good news is that the people working hardest on it are doing their work in public, in books, on LinkedIn, in podcasts, and at conferences, for anyone willing to pay attention.

Jonno White is a Certified Working Genius Facilitator and keynote speaker who works with leadership teams around the world to build the clarity and culture that allows good data to generate great decisions.

Email jonno@consultclarity.org.

His book Step Up or Step Out is available at amazon.com.au.

For more on staying current with the people shaping how the world thinks about data and technology, check out my blog post '50 Best Thought Leaders in Technology (2026)' at consultclarity.org/post/50-best-thought-leaders-in-technology-2026.

About the Author

Jonno White is a Certified Working Genius Facilitator, bestselling author, and leadership consultant who has worked with schools, corporates, and nonprofits across the UK, India, Australia, Canada, Mongolia, New Zealand, Romania, Singapore, South Africa, USA, Finland, Namibia, and more. His book Step Up or Step Out has sold over 10,000 copies globally, and his podcast The Leadership Conversations has featured 230+ episodes reaching listeners in 150+ countries. Jonno founded The 7 Questions Movement with 6,000+ participating leaders and achieved a 93.75% satisfaction rating for his Working Genius masterclass at the ASBA 2025 National Conference. Based in Brisbane, Australia, Jonno works globally and regularly travels for speaking and facilitation engagements. Organisations consistently find that international travel is far more affordable than expected.

To book Jonno for your next keynote, workshop, or facilitation session, email jonno@consultclarity.org.

Next Read: 50 Best Thought Leaders in Technology (2026)

Technology is transforming every industry, every organisation, and every leadership team on the planet. Whether it is artificial intelligence reshaping how we make decisions, cloud computing enabling remote teams to collaborate seamlessly, or data analytics uncovering insights that were invisible just a few years ago, the pace of change is relentless. Staying ahead requires more than reading the news. It requires learning from the people who are driving these shifts firsthand.

Keep reading: consultclarity.org/post/50-best-thought-leaders-in-technology-2026