Thoughtworks

Global Service Portfolio Lead for Data & AI Strategy services, including strategic enablement for Data & AI Governance, Data Modernization, AI readiness and other related client objectives.

Director, Data & AI Strategy

Leading our data strategy and data governance services, shaping the offering and approaches to create value-driven solutions for our clients in Europe

Principal Data & AI Strategist

DataQG

DataQG is the leading Data Enablement and Community Platform designed to help organizations upskill their workforce in data literacy.

Education Advisory Board Member

DAMA Germany

Lead marketing planning, execution and monitoring to grow and engage the community and to establish thought leadership and knowledge exchange in all things Data Management & Data Governance in Germany

Head of Marketing

Technics Publications

Author - "Humanizing AI Strategy - Leading AI with Sense and Soul"

Author - "Humanizing Data Strategy - Leading Data with the Head and the Heart"

Ambassador

adidas

Ensuring product data is consistent, accurate and available and making sure it’s used in a secure and meaningful way. We govern product data end to end, from data creation through data processing all the way to data usage and enrichment.

Senior Director, Product Data Governance

Lead in Social, PR and Voice of Consumer Analytics to integrate Consumer Insights from Social Media, PR, Search Behavior, Product Reviews and Experience NPS feedback into any decision-making in brand strategy, campaign planning and in-activation optimization.

Director, Digital Analytics - Social, PR & Voice of the Consumer

Lead in Voice of the Consumer Analytics with focus on integrated insights based on consumer feedback across digital channels (e.g. Digital Brand Perception on Social Media, Product Ratings / Reviews on Website, Search Behaviour on Google)

Director, Digital Analytics - Voice of the Consumer

Creation of Digital Marketing Performance KPI Framework to measure success within branding activities and consumer perception on strategic and operational level

Lead standardisation and alignment of eCom KPI definitions and reporting methodology across Digital Analytics, BI/Finance, Markets and Business Units

Governance of holistic eCom business performance KPI framework across digital and financial teams

Senior Manager, Digital Analytics

TD Reply

Project Manager of projects in Digital Strategy & Performance Optimization

adidas: On-site Project Manager and Product Owner of KPI Frameworks and Dashboard Visualizations at Digital Brand Commerce

Miele: Account Management of International Brand Marketing and coordination with over 10 markets

Support in Digital Performance Management projects of Coca Cola, Volkswagen and Döhler

Knowledge Management & Advisory between German and Chinese Office

Senior Consultant

Lead of projects in Digital Strategy & Market Research

Key account manager of VW brand marketing

Development of Social Media strategies

Setting up processes and guidelines for crisis management

Consultant

Junior Consultant / Master Thesis

Student Worker

Berlin Institute of Technology (Technische Universität Berlin)

Analysis of business models and market analysis of various industries

Research Assistant - Chair of Strategic Leadership & Global Management

I’m a Data & AI leader by day, a musician at night, and an optimist at heart. 

After 12+ years in data analytics, data governance, consumer insights, digital transformation and AI innovation, I grew fond of the human aspect - how to communicate, collaborate and get creative around data and AI.

My passion lies in making data and AI more approachable and fun, and I often use unconventional methods to do so - with music, humor or other creative outlets. 

Nice to meet you! 
Let’s have a (virtual) coffee?

Tiankai Feng

Data quality has always been a little bit of a catch-all for all kinds of data complaints. Whenever data looks a little different than expected, it immediately must be a data quality problem. 

The rapid increase of AI-driven use cases for data now puts even more attention to the concept of data quality, because AI use cases often require expanded historical data, higher granularity, higher speed and a different focus - like unstructured data for context. 

One thing has not changed: the only way to manage data quality in the right way is to move away from generic complaints about it to detailed conversations about what "high quality" data actually means, and what currently is missing to get there - to then improve data quality together towards a defined state. 

When in doubt, dad jokes can also help - to not only break the ice, but to also exercise authority by positioning yourself as someone's dad. 😁 

Let me know if you need any help.

#dataquality #datagovernance #tiankaistuff

Data & AI Strategy Director @ Thoughtworks | Author of “Humanizing AI Strategy” | TEDx Speaker | Data Musician

This is an appreciation post for everyone working in data governance.

While most data governance people I talk to are really driven and passionate about making data better for their organization, they are also the most modest and self critical - believing they always can do more things better. 

Facing resistance and misunderstandings around what data governance even is trying to do, being a great empath and communicator became a necessity - making them great collaborators and people to hang out with (if you give them a chance).

Since data governance conferences very quickly turn into group therapy, I know we are not getting the attention and acknowledgement we deserve - and although the hype around AI has finally put us in the spotlight, we are now spending even more time and efforts clarifying requirements and objectives, and setting the right expectations.

So, to everyone working in data governance: you are doing your best and it’s awesome - just a little longer and you can recharge during the break. There’s a lot of exciting work to do in 2026.

Data governance rules. 

#datagovernance #appreciation #tiankaistuff

Fun with data literacy in Kindergarten?! 

Yesterday I was invited to read “The Data Detective at the carnival” to the kids at my son’s Kindergarten group - a book that I translated for the German community and donated to the Kindergarten before. 

I was first a little worried that talking to kids between 4 and 6 years old about qualitative and quantitative data would be too difficult - oh how wrong I was! 

We had the most fun letting the kids count and describe things not only in the book but also in the room and in their lives - and everyone was excited to get a “data detective certificate” afterwards! 

But the most rewarding thing of all is how proud my son was that his dad came to Kindergarten to read a book to everyone - showing up as his cool dad is probably my favorite speaking engagement ever. 

Thanks to Chandra Donelson and Jordan Morrow for writing such a wonderful book! 

#dataliteracy #education #tiankaistuff

No alternative text description for this image

In a desperate attempt to make data jobs cool for the next generation, Fortnite launches the new “data squad” skins! 

They even come with their own signature powers: 

👉 the data engineer can build pipelines to move faster but everytime a pipeline breaks the player is teleported next to the pipeline to fix it for an hour

👉 the data scientist can predict other players’ movements but needs to clean data in a spreadsheet for 30 minutes first 

👉 the data analyst puts random dashboards all across the map to confuse other players with KPIs and metrics 

👉 the data product owner can build powerful products but with every minute without a RoI the player loses power 

👉 the data governor can change the rules of the game entirely but other players only have to comply optionally 

Can’t wait for the AI roles skins to drop with equally as much realism! 

P.S. this is satire and not real. 

#data #humor #tiankaistuff

Receiving this kind of feedback after my talk and musical performance at the Forward Data Conference is truly so rewarding.

"People will forget what you said. People will forget what you did. But people will never forget how you made them feel”, the great Maya Angelou once said - that’s why sharing positivity and joy with others is for me equally as important as exchanging knowledge. 

After all, there are two things I love to spread: Happiness and germs. 

Just kidding, it’s Nutella. And germs. 😁

How we make people feel is our real legacy, y’all. Have a great weekend everyone!

#conference #mindset #tiankaistuff

Here are five reasons why you should buy my book "Humanizing Data Strategy":

👉 My mom calls it "better than expected"

👉 Critics call it "marxism for data" and "DEI Cr*p"

👉 It looks great on a book shelf

👉 That's why your kids will love to draw stuff onto the cover

👉 It's currently on Black Friday sales (but apparently only in Germany)

It's also about the human side of data and introduces the framework of the 5Cs (competence, collaboration, communication, creativity & conscience) to make data strategy truly human-centric, but those are just minor details. 😁 

Maybe those that read this book already can leave more reasons to buy it in the comments. Thanks in advance!

#datastrategy #author #tiankaistuff

“You’re too sensitive.” 

One of the worst things to say to someone who’s upset - and it never has made anyone less sensitive, ever. 

There’s always a reason why we are triggered by certain things based on our unique experiences, and this kind of statement shows ignorance to that. 

We can say many other things instead, like: 

“I’m sorry you’re upset - could you help me understand why this bothers you so much?”

“I think we can look at this from a different angle, what about…” 

“What can I do right now to make this situation better? I want to help make this right.”

It’s always easy to judge someone else, but trying to put yourself in someone else’s shoes is where real human connection starts. 

Be human, y’all! 

#empathy #collaboration #tiankaistuff

I’m really happy about anyone who voluntarily listens to my data music, but almost a thousand listeners from 51 countries is crazy! 

2025 was also very exciting because I’ve never performed music live so much as this year - I even got to play on a real concert piano thanks to the Inspari A/S data & AI day, and I got to write and perform a new original conference song for the Forward Data Conference! 

I know that making music about Data & AI is not everyone’s cup of tea - but as someone who’s passionate about the human side of data & AI, isn’t that subjectivity what truly shows our humanity? 

As long as my music brings a net positive to the data and AI community, I’ll keep on doing it - thank you all. 

P.S. I have some very cool new music coming before the year ends, stay tuned! 

#music #personalbranding #tiankaistuff

What do virtual meetings and Disney movies have in common? 

Not a lot, but I created this musical parody anyway. You’re welcome. 

And now everyone: 
🎶 can you see my screen right now? 🎶

YouTube link in comments. 

#meetings #humor #tiankaistuff

Forward Data Conference, here I come! 

This year’s final station of what for me felt like the “humanizing data & AI world tour” will be in Paris - and it will be a doozy! 

I’ll be giving a talk about the key success criteria of truly scaling AI, and I can’t wait to meet data friends like Joe Reis, Eevamaija Virtanen, Jessica Talisman, Andrea Gioia and Gaëlle SERET! 

The forward data conference was an excellent experience already last year, and from what I’ve seen so far Yoann Benoit, François Laurain and the team took it to really the next level this year.

Oh yeah, the scarf indoors is protecting my voice because there may or may not be some never before seen or heard music by yours truly tomorrow… 🎶

à demain!

#conference #data #tiankaistuff

Congratulations to Greg Freeman on publishing The Data & AI Literacy Bible - a book that’s timely, important and truly insightful! 

I had the honor to review and endorse this book, and what I really love about it is the focus on human confidence, growth and actions - aspects that are often forgotten in conceptual and abstract conversations around literacy. 

This having said, I’ve had the chance to meet various Data Literacy Academy folks and they’re all awesome - you can talk to them and find out yourself 🙂

The book is now out on amazon, link in the comments! 

#dataliteracy #book #tiankaistuff

There are many reasons why AI governance is important right now, but the biggest undeniable reason for me is that we need to admit that human-beings aren't perfect and make mistakes, and that we should do everything we can do prevent machines from making the same ones - faster and on bigger scale. 

I was asked to contribute to the "Document automation trends in 2026" report by Rossum and focused on the importance and challenges of AI governance, and there are many other interesting trends to read about that are not only specific to document automation but to AI use cases in general.

On a side note, I love how we are all trying our best to predict the next year, when AI specifically this year showed us that many things are truly unpredictable. I guess we all want some certainty for comfort, and I'm not blaming anyone.

Link to check out the full report in the comments!

Huge thanks to Julie BIASION ✨ for inviting me to contribute!  

#aigovernance #trends #tiankaistuff

🎶 EXCITING NEWS!🎶  

As a token of gratitude for all the opportunities and encouragement I got this year for my data & AI music, I want to give back with something very special: MY FIRST EVER (VIRTUAL) LIVE CONCERT!

Join me in an exclusive livestream where I'll perform my most iconic songs about, data & AI and so much more - and since it's live, of course I'll engage with all of your questions and comments. 

My only question for you is: Which of my songs do you want to see me perform live? The setlist is not completely done yet so I can still make changes 😎 

See you there!

#data #music #tiankaistuff Thoughtworks

TIANKAI LIVE IN CONCERT - a musical end of year celebration

How do I make my AI strategy human-centric, and why does it matter?! 

I’m so excited to return to DataQG to give a community webinar exactly on that topic tomorrow. 

Everyone can join, and there will be a live Q&A - so if you want to visit one of the best data governance communities and watch me improvise answers to your trick questions, join us! 

Thanks to my friend Philip Black for the invitation!

Link to sign up in the comments. 

#aistrategy #webinar #tiankaistuff

I often think about Formula 1 races as best practice environment where actual data-driven decisions are being made - a lot of them at an incredible speed! 

Being able to do that requires not only a well connected ecosystem of machines, tools, and systems - but also an incredibly well-oiled (get it?) team that understands how to work together in a high stakes environment. 

This is why I’m very excited about this upcoming Alteryx webinar with the Lisa Jarman, PhD from the McLaren Group Formula Team to exactly discuss how data-driven decisions are being made there, and I can’t wait to learn and get inspired!

See you at the webinar?

Link to register here: https://lnkd.in/dJi4dKKi

#webinar #dataanalytics #tiankaistuff

Actian

VP, Chief Evangelist

Searching for Data

Founder

GN Group

Architecture Governance

Zeenea

Chief Evangelist (Shareholder)

Enterprise Architect - Data

LEO Pharma

Lead Information Architect, PhD

Politi

Head of Division (Data Protection and Records Management) at Danish National Police

Slots- og Kulturstyrelsen

Specialkonsulent, Ph.d.

University of Copenhagen

External lecturer, PhD

PhD-student

I rethink data and tech by providing perspectives from Library and Information Science. 

In my new book Fundamentals of Metadata Management (O'Reilly, 2025) I out forward a completely new architecture for metadata that I call the Meta Grid.

I have previously published The Enterprise Data Catalog (O'Reilly, 2023), that established me as a globally recognized thought leader on data catalogs and enterprise data management. 

I consult for numerous companies, mostly large, European companies with significant technical complexity.

I have a BA, MA, and PhD from the University of Copenhagen, in Library- and Information Science.

Ole Olesen-Bagneux

How can we enable data intelligence? 

Two competing interpretations of data intelligence are emerging.

Recently, some technology vendors have begun promoting their data platforms as intelligence platforms. Needless to say, such platform have - at least have the intention - to be an ontology at the metadata layer. And as such this is further testimony of the ambition for technology companies to provide an intelligence layer above data.

A data platform, intended for data engineering, consists of all the functionality that data engineers perform, when storing, transforming, and transporting data. And it is a logical step, to want to provide a metadata layer on top. 

However. 

Is that data intelligence? 

Data Intelligence really means something else. Sure, you can depict your data platform at a metadata layer, but does that give you an overview of your data? No, not really. It gives you an overview of the data in your data platform. Does it give an ontology? Yes, if you build it correctly... But it will be a very siloed ontology - it will represent only one data platform.

Data intelligence is about making as much of your enterprise data discoverable, governable, usable. That takes looking further than _one_ platform. However well functioning that platform is.

This ambition is important in the present, and it is only getting more important in the future. Digital sovereignty is on the rise, and data intelligence has to be independent of any given data platform intended for engineering. Enterprises are moving towards technological, legal, and economic freedom from technology providers. And the should! 

There is no right or wrong in data architecture, only choices with consequences. But you have to ask yourself: 

What enables true data intelligence? 
What should your ontology represent? 
Where is the data you want to govern?
Should abstract metadata force you to use specific data technologies?

Winfried Adalbert Etzel, Cristina Caffarra, Kalyan Kumar (KK), Ask Hesby Holm, Mark Tritaris, Claudia Chamas, Aisha Memon, Peter Hanssens, Jérémy Ravenel, Tanya MacKinnon, Andrea Gioia, Peter Baumann, Ronald Baan 🕊️, Mario Meir-Huber, Eric Broda, Sandro Scordo 🇬🇧 🇮🇹 🇵🇹 🇪🇸 🇪🇺, 🌤️Charles CABOURET 📱⌚️💻 💡Emma McGrattan

#dataintelligence #data #dataplatform #metadata #datasovereignty #ontology

Chief Evangelist @ Actian | O’Reilly Author: Fundamentals of Metadata Management (2025), The Enterprise Data Catalog (2023)

data intelligence diagram, showing both options, data platform specific, data platform agnostic

What is knowledge engineering?

Ontologies are once again hot because they are key to succeed with AI - ontologies provide context for AI, so these perform better.

But:

In the current AI hype, some promote establishing a new type of engineer, a  “knowledge engineer” to help the construction of ontologies - and others have warned against introducing such an engineer. Both these positions are wrong.

Knowledge engineering is not something new. The term "knowledge engineer" appears in the scientific literature already 1977 as part of the Stanford Heuristic Programming Project: 

“The knowledge engineer practices the art of bringing the principles and tools of AI research to bear on difficult applications problems requiring experts’ knowledge for their solution. The technical issues of acquiring the knowledge, representing it, and using it appropriately to construct and explain lines-of-reasoning, are important problems in the design of knowledge-based systems“ (1)

and, just like today, the idea is that:

“The acquisition of expert knowledge is fundamental to the creation of expert systems.” (2)

Several experts are claiming knowledge engineering as a new concept, but it’s a false premise for a correct aspiration. We need knowledge engineers, but it’s not a new concept. The notion of Knowledge Engineering survived the AI winter and never stopped being actively discussed in Computer Science as well as Library- and Information Science. (3) And knowledge engineers are facing a great future.

An encouragement:

To push forward, faster, in experimenting with and refining AI for performing expert tasks in agentic architectures, we cannot ignore the fundamentals. We cannot lose time reinventing what already exists. True expertise requires that we build on established knowledge. Just like for AI itself.

Some questions:

How do delineate between knowledge engineers and ontologists? 
Where should the knowledge engineer sit, in the organization?
What is the future of knowledge engineering - To what extent is AI making the knowledge engineer redundant?

Ramona C. Truta, MSc Sabrina Schiele Pierre-Yves BONNEFOY Andrea Gioia  Gaëlle SERET Andrew Bolster Jamie Duff Jade Jones Peter Wilkerson Jessica Talisman Fabiola Aparecida Vizentim Gerke Geurts Christelle Maignan Martijn Muilwijk Heimo Hänninen Robert Dalgliesh MBA

#ontology #knowledgeengineering #ai #expert #agenticAI #data #meaning

(1) Feigenbaum, 1977, Stanford: The Art of Artificial Intelligence. Themes and case studies of knowledge engineering. ["knowledge engineering" as a modification of "epistemological engineering", introduced in 1968, see p. 4]

(2) Stefik, Conway, 1982, Xerox: Towards the Principled Engineering of Knowledge  

(3) ISKO Encyclopedia, 2021, ISKO: Ontologies (as knowledge organization systems)

expert knowledge transferred to expert systems through knowledge engineers

Just a friendly reminder that I believe in disagreeing peacefully. If you leave evil, toxic comments to my followers and friends you are blocked and reported. I dont care who you are or what you do - I treat everyone equally.

Thank you Christelle Maignan for reading Fundamentals of Metadata Management. I firmly believe understanding the reality in enterprises before setting a strategy for data, metadata and AI. That is often forgotten in the eagerness to implement even more technology.

I've had the pleasure of being the Lead Ontologist for the IKEA Knowledge Graph (IKG) for the past year and a half — first as a consultant, now as an employee. This role has pushed me to expand my horizons from customer-facing question-answering systems (like the Alexa knowledge graph I helped build at Amazon) to enterprise knowledge graphs and ontology-based data management.

The IKG is still in the early stages of its transition towards an enterprise knowledge graph, and I've been busy sharpening my skills through daily discussions and collaborations with subject matter experts, enterprise architects, and experts in governance, metadata, data catalogs, and business glossaries. Books are also proving invaluable in solidifying my learning.

Ole Olesen-Bagneux's Fundamentals of Metadata Management is well-structured and easy to read, providing clear definitions of concepts like the various metadata repositories in IT landscapes, data management vs. information management vs. knowledge management, data lakes and data warehouses, microservices, data mesh, and his solution to metadata management, the Meta Grid.

Next on my list is Data Management at Scale by Piethein Strengholt. I'm particularly interested in its chapters on data domains, data products, and master data management.

#knowledgegraphs #datamanagement #metadata

It's easy to get lost in the AI conversation. Especially on who is actually in control - humans or artificial intelligence? 

Join me for a conversation with data & AI visionary Tiankai Feng, when we talk about humans before AI. What do we, as humans, want to do with AI, and why? What are our strategic objectives for AI? How do we humanize our AI strategy? 

link in comment

#ai #aistrategy

I knew this post would explode

2026 is the year of the ontology

Ontology is having its moment. There was a time when we called it the "O word." Nothing killed a conversation with business - or IT - faster than mentioning ontology. The rule was simple: deliver value, keep the ontology part quiet.

But things have changed.

Ontology is shaping up to be the buzzword of 2026. A big part of that is Palantir's extraordinary rise - their entire Foundry platform is built on ontological modeling. Microsoft is now moving ontology into Fabric. The race is on.

Why now?

Because structured ontologies offer something generative AI desperately needs: grounding.

LLMs are creative but lack logical constraints. Ontologies provide the formal structure to anchor meaning and harmonize wildly different data sources into a coherent semantic layer. When you need precision over plausibility, ontologies are one of the most reliable ways to keep AI from hallucinating.

But what actually is an ontology?

The idea traces back 2,000 years to Aristotle, who tried to formalize how we perceive reality. Ontology today is that same craft: defining the concepts and relationships that shape our world in a logically rigorous way.

Fast forward to the early web. Tim Berners-Lee envisioned the Semantic Web - an internet where data, not just documents, was linked. Give every ontological concept a unique identity, he argued, and meaning becomes a first-class citizen of the web.

Google later operationalized part of this vision with Schema.org, creating a shared vocabulary to help search engines understand the public internet.

But the current frontier isn't the public web - it's the enterprise.

Companies want AI agents that can reason about their internal data - their customers, assets, processes. They need semantic clarity applied to their own messy, private reality. Disambiguating meaning isn't just useful anymore. It's essential.

Here's the problem: you can't outsource your ontology. Enterprises need their own internal version of schema.org - fully owned, built on open standards. Anything less means IP leakage and vendor lock-in. In the age of AI, your ontology is a key part of your competitive moat.

So, ontology is back. And this time it's not theory - it's critical infrastructure.

⭕ Your Schema.org: https://lnkd.in/eumPB3Hj

⭕ Your Ontology Your IP: https://lnkd.in/ersgR-Df

Gaëlle SERET joined us on Enterprise Wide Search

We are live with episode 22 with Gaelle Seret on domain architectures and technologies. Gaelle has a very detailed view on this, there is a lot to lea

Open article: Enterprise Wide Search 22: Domains First: Rethinking Data Through Business Boundaries by Ole Olesen-Bagneux • 1 min read

Enterprise Wide Search 22: Domains First: Rethinking Data Through Business Boundaries

I'm very proud to be part of Marc Potters team - under his leadership, we are making important progress with the Actian Data Intelligence Platform. And CIOReview has seen that. We are the Top Data Intelligence Platform of 2025!

Actian is named “Top Data Intelligence Platform of the Year” by CIOReview. 🎉

As highlighted in the latest issue, Actian is redefining what’s possible for enterprises in the AI era. The article notes that under the leadership of CEO Marc Potter, the Actian Data Intelligence Platform empowers organizations worldwide to discover, govern, and activate data with confidence.

The article captures Actian’s vision to bring together governance by design, a federated knowledge graph, and user-first design for trusted, easy-to-access data. Potter notes that if you don’t trust your data and you use AI, you risk undermining your entire initiative.

Read the full article to see how Actian is pioneering data intelligence. ➡️https://bit.ly/43GvLEZ

HCLSoftware, HCLTech, Kalyan Kumar (KK), Vijayakumar C
#DataIntelligence #AIReadyData #DataGovernance

Frédéric R. joined us for a conversation on MCP, and if MCP will kill the data marketplace. Link inside the newsletter 👀 
#mcp #ai #datamarketplace

We had Frederic Robert on Enterprise Wide Search, providing a technically succinct, precise answer to the question: Will MCP kill the data marketplace

Open article: Enterprise Wide Search 21: Will MCP kill the data marketplace? by Ole Olesen-Bagneux • 1 min read

Enterprise Wide Search 21: Will MCP kill the data marketplace?

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The Battle

Tiankai Feng

Ole Olesen-Bagneux

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taplio

The Battle

Tiankai Feng

Ole Olesen-Bagneux

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Tiankai Feng's LinkedIn Performance

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