In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Julia Diez, Localization Software Engineer at McAfee and the author behind one of the most quietly brilliant Substacks in tech today.

Trained as a linguist and now working at the intersection of metadata, multilingual ontologies, and LLMs, Julia brings a rare perspective to the world of data and AI—one shaped by bookstores, translation memories, and a deep appreciation for cultural nuance.

Together, they explore:

• Why translating “Welcome, User” might not be as simple as it sounds.

• The hidden complexity of plurals, pronouns, and color in globalized software.

• How language, etymology, and pragmatics shape our technologies (and sometimes break them).

• What it means to build a multilingual knowledge graph, and why it matters in the age of AI.

• Why localization isn’t just post-processing, but a design principle for global systems.

🎧 Tune in for a conversation that moves from Copenhagen to Cork, metadata to meaning—reminding us that culture, language, and context are just as foundational as code.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Lukas Plaehn, Head of Data Office at Bank of Valletta, to explore what makes data so hard to manage in financial institutions—and why that challenge goes deeper than technology.

From Malta’s sun-soaked shores to the global stage of regulatory compliance, Lukas brings a thoughtful voice to some of the industry's most complex issues.

Together, they explore:

• Why trust—not technology—is the core tension in financial data management.

• The layered legacy of banks, and how smart people can slow transformation.

• What systemic banks are, and why regulators are making data quality the law.

• How ontologies, data contracts, and shared models are reshaping the industry.

• Why BI is blurring with operational tech, and how this could finally close the loop from reporting to prediction.

🎧 Tune in for an insightful look into what it takes to modernize data in one of the world’s most risk-averse industries.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Jean-Georges Perrin—better known as JGP—to discuss the future of data products, the limitations of BI, and the importance of federated thinking in an era of real-time everything.

From his early days self-publishing a 300-page C++ guide with a classmate (armed with nothing but Word and a photocopier) to writing Implementing Data Mesh with O’Reilly, JGP reflects on why storytelling, open standards, and metadata will shape the next era of enterprise data.

Together, they explore:

• Why dashboards aren’t data products—and what that reveals about the lifecycle of data.

• The origin story of Bitol and its zero-code approach to defining open standards.

• What’s next for Data Mesh after the GenAI hype wave.

• Why BI might die (and why that’s not a bad thing).

• How federated governance beats both centralized and decentralized extremes.

🎧 Tune in for an honest, funny conversation about the future of data platforms—and why sometimes, it’s more helpful to say what something isn’t.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Rachael Greaves, CEO of Castlepoint Systems and pioneer of regulation-as-code AI, to unpack why records and information management are more relevant—and more technical—than ever.

Together, they explore:

• The sometimes overlooked discipline of records management and why it matters in the age of AI.

• Why data lifecycle decisions are so hard, and why deletion is sometimes the safest option.

• What ethical AI actually means and how to make it explainable and contestable by design.

• How Castlepoint uses rules-as-code to govern massive, messy, enterprise-scale datasets.

• Rachael’s advice to anyone (especially women) entering regtech, cyber, or data governance.

🎧 Tune in for a conversation that connects the dots between compliance, security, metadata, and meaning—and why AI won't fix your governance mess if your rules aren’t clear.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Thais Cooke, Senior Healthcare Data Analyst and LinkedIn Learning instructor, to discuss what happens when curiosity meets chaos—and how a career shift from frontline healthcare to data analytics has unlocked new ways of thinking about impact, problem-solving, and AI.

Together, they explore:

• Thais’ transition from burned-out dental professional to SQL-obsessed analyst.

• How learning to “follow the pain” helped her solve real-world problems with data.

• Her approach to using AI without outsourcing critical thinking.

• Why domain expertise is often the missing piece in data analysis and governance.

• How she created two LinkedIn Learning courses tailored to healthcare professionals.

🎧 Tune in for an inspiring take on learning, career change, and making AI part of your workflow, without losing your voice along the way.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Jérémy Ravenel, researcher, advisor, and founder of the open-source NaasAI platform. Known for bridging the gap between theory and execution, Jérémy shares his journey from Excel-heavy finance roles to leading cutting-edge research in AI interoperability and enterprise knowledge graphs.

Together, they explore:

• Why so many GenAI initiatives fail without semantic structure and context.

• What it means to “clean your room” before deploying AI agents.

• How ontologies can evolve from niche academic tools to practical building blocks of enterprise-scale AI.

• The tension between perfection and pragmatism in data work.

🎧 Tune in for a conversation on the hidden structures behind meaningful AI, and why the future might depend on how well we model what we already know.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Dr. Shweta Shah, a seasoned data and AI architect with a fresh perspective on how we think about quality in the age of unstructured data and GenAI. Shweta introduces “Content Quality Management” (CQM), a new framework designed to help organizations prepare unstructured content for trustworthy, auditable, AI-powered outcomes.

Together, they explore:

• Why traditional data quality frameworks fall short in GenAI systems.

• The seven dimensions of content quality.

• Why unstructured data needs more than structure to be AI-ready.

• The role of team diversity and ethical design in building AI that works for everyone.

• How CQM could evolve into a new standard—or even a product—for enterprise AI readiness.

🎧 Tune in for a timely conversation that reframes unstructured data not as a challenge, but as an opportunity to rethink what “quality” really means in modern data work.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Dylan Anderson, Head of Data Strategy at Profusion and author of The Data Ecosystem newsletter. Dylan brings a pragmatic, field-tested perspective on how to bridge the gap between strategy and implementation—and why many organizations still struggle to align data with business value.

Together, they explore:

• Dylan’s work helping companies turn vague goals into actionable data strategies.

• The real reasons enterprise-wide search still falls short, and how AI can help fix it.

• Why data catalogs disappointed, and what it takes to build real access and insight.

• The toughest part of connecting data and business strategy.

🎧 Tune in for a conversation about the messy reality of data transformation—and why the best strategies are the ones that actually get used.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux welcome Sofia Zapounidou, Team Lead at the Publications Office of the European Commission and a lifelong champion of metadata, identifiers, and meaning in a machine-readable world. Drawing on her background in library and information science, Sofia offers a unique perspective on the evolution of data work—from card catalogs to linked open data—and what today’s AI and data communities can learn from the past.

Together, they explore:

• Sofia’s work leading a linked data transformation at the European Commission.

• What librarians have always known—and technologists often forget—about user context and information architecture..

• Why data migration is an opportunity to improve data quality, not just preserve it.

• How FRBR (and now LRM) reshaped library metadata as a graph-based model.

• Why data needs continuous curation, and how to build a culture that supports it.

  
  

🎧 Tune in for a conversation that bridges the gap between tradition and innovation, reminding us that behind every intelligent machine is a century of human effort to describe the world clearly.

Hosted by Ausha. See ausha.co/privacy-policy for more information.

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Tim Wiegels, Executive Data Advisor and former VP of Data at FreeNow. Known for his brutally honest and refreshingly pragmatic take on building data teams, stacks, and cultures, Tim shares lessons from a career spanning gaming, mobility, and high-growth tech.

Together, they explore:

• Tim’s journey from bioinformatics PhD to startup veteran and strategic advisor.

• Why he believes your first hire shouldn’t be a data scientist—or even a data engineer.

• The rise of the analytics engineer and why Excel skills still matter more than most admit.

• The myth of the all-knowing centralized data team—and how to rethink service, ownership, and collaboration in real-world enterprises.

🎧 Tune in for an unfiltered, field-tested look at what it really takes to move organizations from spreadsheet chaos to data-driven confidence.

Hosted by Ausha. See ausha.co/privacy-policy for more information.