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# The Data-Driven Decision Making Blog

Copyright © 2026 Elizabeth Press

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## Beiträge

- [European DeepTech in a Frenemy Economy](https://d3mlabs.de/?p=1685) - The era of safe dependencies is over. What does that mean for investors, companies, and the startups in DeepTech and beyond? Here are my insights from the Aspen Institute Germany German American Trade and Tech Conference 2026. I was a guest on the panel Strategic Autonomy or Alliance Integration? Transatlantic Defense Cooperation at a Cross Roads. My question concerned the European conundrum of seeking to retain and commercialise IP while lacking sufficiently deep private capital markets and risk appetite to fund DeepTech.
- [Europa rüstet auf — Innovatrice schließt die Lücke zwischen Deep-Tech und Kapital](https://d3mlabs.de/?p=1665) - Die europäische Verteidigungs- und Dual-Use-Technologie hat den Übergang von einer politischen Ambition hin zu messbaren Kapitalallokationen vollzogen – und das Zeitfenster für Gründer, Investoren und Partner, sich strategisch zu positionieren, ist genau jetzt offen. Das Bild würde mit ChatGPT generiert.
- [Europe is rearming — Innovatrice closes the gap between deep tech and capital](https://d3mlabs.de/?p=1668) - European defense and dual-use technology has crossed from policy ambition into measurable capital deployment — and the window for founders, investors and partners to stake a position is open right now. This picture was generated with ChatGPT.
- [Why Operational Resilience Is Now a Strategic Imperative](https://d3mlabs.de/?p=1655) - Elizabeth Press talked with Sina Yazdanmehr, IT Security Consultant and BSides Berlin Co-Organizer about the strategic imperative of operational resilience. In today’s digital-first world, companies have become heavily dependent on vendors—especially cloud providers—often without fully considering the risks of lock-in. Operational resilience is now critical, how vendor dependency can threaten mission-critical systems, and what organizations can do to stay in control. The image was generated by ChatGPT.
- [Data Leadership in Transition: Navigating Generative AI and Business Value](https://d3mlabs.de/?p=1649) - This year is a time of transition for many data leaders—at the intersection of Generative AI, economic shifts, and political change. Data Leader Divya Bokaria and Elizabeth Press (D3M Labs) explore how the world is evolving, while emphasizing that data leaders remain stewards of business value.🧩 Data leaders navigate complex, evolving value chains and translate insights into strategies, objectives, and processes. Technologies and workflows may change, but the core mission remains: turning data and complex technologies into measurable business outcomes, whether in formal leadership roles or beyond. The image was generated by ChatGPT
- [From European Integration to Digital Innovation: A Franco-German Tech Story](https://d3mlabs.de/?p=1637) - What will define Europe’s digital future in 2026? From Franco-German cooperation to the ubiquity of Silicon Valley, Data Leader Nicolas Michaud and Elizabeth Press (D3M Labs) reflect on the evolution of digital leadership in Europe.
- [Gen X: How Surviving Economic Collapses Built the Ultimate Bounce-Back Generation](https://d3mlabs.de/?p=1625) - Resilience, grit, and reinvention forged through repeated crisis have given Gen X the unique skills to lead through today’s challenges—why a generation raised on uncertainty learned to adapt and lead. The picture was generated by ChatGPT.
- [From Hype to Hard Truth: Lessons in Data-Driven Innovation](https://d3mlabs.de/?p=1612) - In our latest video, Elizabeth Press speaks with Pier Martin, data leaders who’ve weathered Berlin’s decade of hype, hope, and hard lessons, about how organizations can turn data into real business value. Here’s what they shared.
- [The AI Inflection Point: Generative AI and the New Era of Regulation and Resilience](https://d3mlabs.de/?p=1616) - We are standing at an inflection point in the evolution of AI. The field is moving from hype to maturity. After a decade in which cheap capital and boundless optimism fueled sky-high expectations—when data was hailed as “the new oil”—the post-COVID era has brought a dose of sobriety. The age of “move fast and break things” is being replaces by a new mantra: move thoughtfully, build sustainably, and govern wisely. This picture was generated with ChatGPT.
- [My First October 3rd as a German Citizen: Reflections about Unity, Resilience, and Sovereignty](https://d3mlabs.de/?p=1605) - Today marks my first October 3rd — the Day of German Unity — as a German citizen. This day commemorates the reunification of East and West Germany in 1990, a moment of profound historical significance. For me, becoming a German citizen is not just a legal milestone; it is a moment to reflect on the
- [Mein erster 3. Oktober als deutscher Staatsbürger: Reflexionen über Einheit, Resilienz und Souveränität](https://d3mlabs.de/?p=1608) - Heute markiert meinen ersten 3. Oktober — den Tag der Deutschen Einheit — als deutscher Staatsbürger. Dieser Tag erinnert an die Wiedervereinigung von Ost- und Westdeutschland im Jahr 1990, ein historisches Ereignis von großer Tragweite. Für mich ist die deutsche Staatsbürgerschaft nicht nur ein rechtlicher Meilenstein, sondern auch ein Moment, um über die Werte, Verantwortlichkeiten
- [ How LLMs Are Changing Software Engineering](https://d3mlabs.de/?p=1587) - This article is based on my talk with Varshith Anilkumar, engineering leader and AI researcher. The release of GPT-5, now integrated into tools like GitHub Copilot, marks a significant turning point for software development. LLMs such as Claude Code and GPT-5 can generate complex code. "Agentic" tasks are pushing the industry toward a new paradigm where developers orchestrate multiple AI agents to build entire systems. This shift is changing the game from focus on writing code to designing and managing sophisticated, automated workflows. The image was generated by GPT-5.
- [The Resiliency Imperative: Redefining Digitalization in a Post-Velocity World](https://d3mlabs.de/?p=1565) - 24-25 June 2025 I had the opportunity to attend the German-American Trade and Tech Conference, organized by the Aspen Institute Germany. A new digital imperative crystallized through the conference discussions—the need to fundamentally rethink how we build and secure our digital future. In this blog, I outline the key forces at play and the strategic imperatives they demand.
- [Elevate Your Data Team: How an ITIL Service Model Drives Performance & Value](https://d3mlabs.de/?p=1532) - After more than a decade of leading data teams at various organizations, including startups and enterprises, I’ve seen centralized functional organizations, centers of excellence, start-up one woman shows and agile, zombie agile, pods, squads, the federated, the „data as a product“ model. But after all the pivots, restructures, and retrospectives, I’ve landed on a conclusion that might raise eyebrows: most data teams should function as service teams—with the critical caveat that they adopt ITIL principles. Image was generated by ChatGPT.
- [Toxic Leadership in Data: The Hidden Costs of Hype-Based-Growth](https://d3mlabs.de/?p=1545) - In 2023, Kasia Musur CEO and Founder of Vent, conducted a study about Toxic Leadership in Data based on experiences of members in the D3M Labs community. Vent is THE platform addressing experiences of toxic leadership through storytelling and research. VENT brings together multidisciplinary collaborators, survivors, and technology to reduce the impact of toxic leadership on individuals, communities, businesses, and the environment. Through educational campaigns, research, and powerful storytelling, VENT sheds light on real experiences, offering insights to inspire change! Image was generated by ChatGPT
- [Avoiding Data Strategy Spaghetti: Be more like Hummus. Be Simple.](https://d3mlabs.de/?p=1478) - Analytics Fear of Missing Out (AFOMO) might be the reason your data strategy resembles a chaotic spaghetti-filled pasta bar, with many options and free-form combinations. This pervasive apprehension compels individuals and businesses alike to scramble in fear of being left behind, driving them to relentlessly try new KPIs and keep options open with any data set they could recall being in their organization. This blog is inspired by my interview "Data should be like a plate of hummus," a conversation with Lior Barak and Elizabeth Press (myself) from D3M Labs.
- [What is the Future of AI Development & Deployment?](https://d3mlabs.de/?p=1474) - 🔮 Generative AI is going to change the world….🔮until you take some practicalities into account. We had a great time talking about the "Future of the Development and Deployment of AI," organized by D3M Labs and hosted by SPICED Academy with Elizabeth Press, M. Murat Ardag, Ph.D. and Samantha Edds. M. Murat Ardag, Ph.D, a Data Scientist and Political Psychologist, presented his study utilizing the Stack Overflow 2023 Annual Developer Survey.
- [Is the love of artisinal SQL the downfall of data teams?](https://d3mlabs.de/?p=1484) - The artisanal approach to SQL and the masterpiece culture in querying are not-so silent killer of many data teams. The self-view of many analysts and even data leaders is that writing long queries is an intellectual and technical pure form of analysis. However, if crafting a 200-something line SQL query takes hours or even days (a scenario all too familiar), it's a sign that your data team is operating like artistic masters. Let’s face it, data teams don’t have royal sponsors to create masterpieces. Thinking Bauhaus is more fitting for cash-burn budgets that most data teams run on.
- [Brave Questions About AI & Information and Cyber Security Round Table # 1](https://d3mlabs.de/?p=1461) - In today's dynamic environment, both individuals and organizations are embarking on innovative experiments with AI applications. However, amidst this exploration, concerns about security linger. In the first Brave Questions about AI & Information and Cyber Security Round Table # 1, we delved into the burgeoning AI landscape, where one participant likened the journey to the unpredictable nature of the "Wild West."
- [Mutige Fragen zu KI & Information und Cybersicherheit Round Table # 1](https://d3mlabs.de/?p=1466) - In der heutigen dynamischen Umgebung beginnen sowohl Einzelpersonen als auch Unternehmen mit innovativen Experimenten mit KI-Anwendungen. Inmitten dieser Erkundung gibt es jedoch immer wieder Bedenken hinsichtlich der Sicherheit. Beim ersten "Brave Questions about AI & Information and Cyber Security Round Table # 1" (Mutige Fragen zu KI & Informations- und Cybersicherheit) haben wir uns mit der aufkeimenden KI-Landschaft befasst, wobei ein Teilnehmer die Reise mit den Unwägbarkeiten des "Wilden Westens" verglich.
- [Brücken schlagen: KI und Informationssicherheit & Cybersicherheit](https://d3mlabs.de/?p=1458) - 🔒 Cybersicherheit ist ein Wettbewerbsvorteil. 🚀 In einer sich rasch entwickelnden KI-Landschaft drängen Unternehmen auf den Einsatz von KI als Mittel, um relevant zu bleiben. In diesem Blog wird das komplexe Terrain der Gewährleistung von Cyber- und Informationssicherheit bei KI-Einsätzen untersucht. Es gibt auch einen Link zu einem Video mit einem Gespräch zwischen Elizabeth Press und Hannah Suarez, zwei Branchenexperten für gewinnbringende KI und Cybersicherheit, über "Unlocking Business Value Through Cyber and Information Security" auf dem D3M Labs YouTube Channel.
- [Bridging the Gap: AI and Information & Cybersecurity](https://d3mlabs.de/?p=1449) - 🔒 Cybersecurity is a competitive advantage. 🚀 In a rapidly evolving AI landscape, companies are rushing to deploy AI as a means to stay relevant. This blog explores the complex terrain of ensuring Cyber & Information Security in AI deployments. There is also a link video to a conversation between Elizabeth Press and Hannah Suarez, two industry experts in Profitable AI & Cybersecurity, about "Unlocking Business Value Through Cyber and Information Security" on the D3M Labs YouTube Channel.
- [Die Schaffung einer sicherheitsbewussten Kultur zum nachhaltigen Erfolg](https://d3mlabs.de/?p=1413) - Sicherheit ist ein fortlaufender Prozess, kein einmaliges Ereignis. Wir müssen unsere Sicherheitspraktiken ständig anpassen und verbessern, um neuen Bedrohungen zu begegnen. In der Eile, etwas zu liefern und Geld zu verdienen, wird die Sicherheit oft vernachlässigt. Aleksandra Kornecka sprach mit Elizabeth Press (mir) darüber, wie man eine sicherheitsbewusste Kultur schafft.
- [Fostering a Security-Aware Culture for Sustainable Success](https://d3mlabs.de/?p=1407) - Security is an ongoing process, not a one-time event. We must continuously adapt and improve our security practices to address emerging threats. Often, in the rush to deliver and monetize, security is an after thought and threats remain exposed. Aleksandra Kornecka talked with Elizabeth Press (myself) about how to create a security aware culture.
- [Why the Digital World Needs Operations](https://d3mlabs.de/?p=1396) - Operations is the often-overlooked hero of profitable growth. Antonia Landi and Elizabeth Press (myself) connected over the insight that operational excellence is the key to business success, be it in product, data, on the factory floor or the newsroom. Even creative agencies have processes. Ops and processes will become a passport to play, as legislators catch up with technology (NIS2, DORA as examples) and ISO 27001 becomes a standard business hygiene in many industries.
- [Die Sicht eines Data Leaders auf Cybersicherheit](https://d3mlabs.de/?p=1391) - Dieser Blog enthält einige meiner wichtigsten Eindrücke von der kürzlich stattgefundenen niederländisch-bayerischen Konferenz ‚Zusammenarbeit in der Cybersicherheit: Die wichtigsten Aufgaben für die Unternehmensführung‘ in München, organisiert von InnovationQuarter. Ich hatte das Privileg, von der Recruiting-Firma GCS zu der Veranstaltung eingeladen zu werden. Die Welt wird immer digitaler und gefährlicher, was den Gedankenaustausch über Cybersicherheit zwischen Freunden und Geschäftspartnern unerlässlich macht. Ich verbrachte einen Tag damit, brillanten Köpfen aus den Niederlanden, Bayern und darüber hinaus zuzuhören, die darüber sprachen, wie man Cybersicherheit zu einem C-Suite-Thema machen kann.
- [A Data Leader's Perspective on Cybersecurity](https://d3mlabs.de/?p=1384) - This blog entails a few of my high-level takeaways from the recent Dutch-Bavarian "Collaboration in Cybersecurity: The most important tasks for business leaders" conference in Munich, Organized by InnovationQuarter. I was privileged to get invited by the recruiting firm GCS to the event. The world gets increasingly digital and dangerous, making the exchange of ideas about cybersecurity between friends and trading partners essential. I spent a day listening to brilliant minds from the Netherlands, Bavaria and beyond talk about what how to make Cybersecurity a C-Suite issue.
- [Operational Analytics, a New Paradigm for Delivering Data-Driven Impact](https://d3mlabs.de/?p=1372) - From higher ROI to easier use, operational analytics answers many contemporary challenges facing data teams. I (Elizabeth Press), spoke with Dani Solà Senior Vice President of Data and Analytics at Clark about Operational Analytics. Success, however, necessitates a well-governed data platform and solid security concepts. When your stakeholders come back with questions, it's a sign of engagement and thus relevance of the system you built.
- [How Large Language Models are Transforming Data Operations](https://d3mlabs.de/?p=1355) - Large language models and generative AI are disrupting how data is done. I (Elizabeth Press from D3M Labs) spoke with Leonid Nekhymchuk (Leo), CEO and Co-Founder of Datuum.ai, about how large language models will transform data operations. Datuum uses AI to connect data sources with target models, automate mapping, making data integration less time-consuming and less expensive.
- [Experiences of Toxic Leadership in Data](https://d3mlabs.de/?p=1321) - Kasia Musur from VENT conducted research about experiences of toxic leadership amongst data professionals in cooperation with Elizabeth Press from D3M Labs. The blog is a high level summary of a couple of insights with a link to the full interview on the D3M Labs YouTube channel.
- [Ensuring the Data Team's Financial Viability, Beyond Cash Burn - An Interview with Timur Bokari](https://d3mlabs.de/?p=1305) - In his current role, Timur Bokari supports the growth of a FinTech in the Recurring Revenue Financing space by developing new customer segments and evolving strategy based on existing data. Timur talks to D3M Labs about the financial viability of data teams. He explains the financial and accounting mechanisms that are relevant to Data Leaders. Data team viability lies in the link between data availability and decision-making capability. Financial sustainability and job stability in data requires clearer correlations between data and revenue growth and cost reduction.
- [Die finanzielle Überlebensfähigkeit des Data Teams gewährleisten, über den Cash-Burn hinaus - Ein Interview mit Timur Bokari](https://d3mlabs.de/?p=1291) - In seiner aktuellen Position unterstützt Timur Bokari das Wachstum eines FinTechs im Bereich Recurring Revenue Financing durch die Erschließung neuer Kundensegmente und die Weiterentwicklung der Strategie auf Basis vorhandener Daten. Timur spricht mit D3M Labs über die finanzielle Nachhaltigkeit von Datenteams. Er erklärt die Finanz- und Buchhaltungsmechanismen, die für Data Leaders relevant sind. Die Überlebensfähigkeit von Datenteams liegt in der Verbindung zwischen Datenverfügbarkeit und Entscheidungsfähigkeit. Die finanzielle Nachhaltigkeit und Arbeitsplatzstabilität im Datenbereich erfordert klarere Korrelationen zwischen Daten und Umsatzwachstum und Kostensenkung.
- [Sustainable data tool purchasing, Part 2: How to prevent haphazard cool tool purchasing from de-railing your engineering team](https://d3mlabs.de/?p=1251) - Engineers and customer success teams are unsung heroes of IT Operations. Have you wondered what your they think of your purchasing habits? Especially in virtual organizations, engineers and customer success counterparts at vendors can live in their coding-cave, working hard, invisible to others. Impulsive cool tool purchasing without including engineers might not only be driving those difficult to recruit professionals crazy and burn vendor relationships, it could derail your platform development and important projects such as data migration. It might frustrate your engineers enough to quit.
- [Die nachhaltige Beschaffung von Datentools ist dringend erforderlich,Teil 2: Wie verhindert man, dass der planlose Kauf von coolen Tools das Engineering-Team aus der Bahn wirft?](https://d3mlabs.de/?p=1267) - Ingenieure und Customer Success Teams sind die unbesungenen Helden des IT-Betriebs. Hast du dich schon einmal gefragt, was sie über deine Kaufgewohnheiten denken? Vor allem in virtuellen Organisationen können Ingenieure und Kundenerfolgsteams bei Anbietern in ihrer Programmierhöhle leben, hart arbeiten und für andere unsichtbar sein. Wenn man impulsive coole Tools kauft, ohne die Ingenieure mit einzubeziehen, kann das nicht nur diese schwer zu rekrutierenden Fachleute in den Wahnsinn treiben und die Beziehungen zu den Anbietern belasten, sondern auch die Entwicklung Ihrer Plattform und wichtige Projekte wie die Datenmigration zum Scheitern bringen. Das könnte Ihre Ingenieure so frustrieren, dass sie kündigen.
- [Product lifecycle management in the era of smart devices - an Interview with Eric JoAchim Liese](https://d3mlabs.de/?p=999) - How to Manage the Data Science Product, Part 2: As devices get smart, product lifecycle management for hardware needs to evolve to encompass the view of data as a long-term asset and as an active, even pro-active part of the customer relationship. Eric JoAchim Liese talks about edge computing and device autonomy as being requisite to providing a good customer experience. He also explains how traditional hardware manufacturers can evolve their operations and hire in expertise to successfully navigate the journey.
- [Sustainable data tool purchasing, Part 1: Cool tools on the Boulevard of Broken Dreams](https://d3mlabs.de/?p=1209) - Cool tools are often the Data Leader's (or stakeholder's) hot tech hookup, ending up in a cold alley with yesterday's clothes the morning after. Cool tools get purchased, installed, tried out and abandoned for the next promising vendor. And it’s seriously threatening data teams' financial and operational viability. Why are data tools so seductive? How can we prevent procurement from ending up in a boulevard of broken dreams and unrealized projects?
- [Die nachhaltige Beschaffung von Datentools ist dringend erforderlich,Teil 1: Coole Tools und Data Teams auf dem Boulevard der zerbrochenen Träume](https://d3mlabs.de/?p=1220) - Coole Tools sind oft die heiße Hookup des Data Leaders (oder Stakeholders), um am nächsten Morgen mit den Klamotten von gestern in einer kalten Gasse zu landen. Coole Tools werden gekauft, installiert, ausprobiert und für den nächsten vielversprechenden Anbieter aufgegeben. Und das bedroht ernsthaft die finanzielle und operative Überlebensfähigkeit des Data Teams. Warum sind Data Tools so verführerisch? Wie können wir verhindern, dass die Beschaffung zu einem Boulevard der geplatzten Träume und nicht realisierten Projekte wird?
- [My top takeaways from the Berlin AI Summit: Understand the problem and don't neglect operations.](https://d3mlabs.de/?p=302) - The major challenges to AI implementation are often mind-set based rather than technical. Problems in production and implementation of AI often stem from organizations' and practitioners' lack of ability and/or desire to thoroughly scope out and define the problem they are trying to solve. Consequently, they often don't select the right tools, capabilities and processes to implement successfully. Organizations can also negelct operations (such as MLOps), which are important for work efficacy and scale.
- [What is the Future of AI Adoption?](https://d3mlabs.de/?p=465) - This article summarizes the main takeaways as discussed in the panel "What is the future of AI adoption?" at Rework's Enterprise AI Summit in Berlin.
- [Why the public needs to know more about AI - An interview with Varsh Anilkumar](https://d3mlabs.de/?p=503) - AI is still magical to many people. Is that a major obstacle to AI adoption? Varshith H Anilkumar talked to myself and the D3M Labs community about what can be done to create a more AI-aware public and how that will help decrease bias and improve innovation.
- [Beyond the algorithm, the realities of operationalizing AI - A podcast interview with Elizabeth Press](https://d3mlabs.de/?p=541) - The AI mystique might be the biggest obstacle to AI adoption. The artisanal data scientist who works on an alchemy of code output the magical algorithm impedes discussion on what is needed to commercialize and scale AI solutions. AI needs to be treated like a product and an item to be manufactured and scaled on an industrial level.
- [Das Produktlebenszyklusmanagement im Zeitalter der intelligenten Geräte - ein Interview mit Eric JoAchim Liese](https://d3mlabs.de/?p=1024) - Wie managt man ein Data Science Produkt, Teil 2: Da die Geräte immer intelligenter werden, muss sich das Produktlebenszyklusmanagement weiterentwickeln, um die Daten als langfristigen Wert und Teil der Kundenbeziehung zu betrachten. Eric Joachim Liese spricht über Edge Computing und Geräteautonomie als Voraussetzung für ein gutes Kundenerlebnis. Er erklärt auch, wie traditionelle Hardware-Hersteller ihre Betriebsabläufe weiterentwickeln und Fachkräfte einstellen können, um diesen Weg erfolgreich zu beschreiten
- [Das Management des Data Science Produktes - ein Interview mit Anna Hannemann, PhD](https://d3mlabs.de/?p=972) - Wie managt man ein Data Science Produkt, Teil 1: Algorithmen sind Produkte, die gemanagt werden müssen, um geschäftliche Ergebnisse zu erzielen. Anna Hannemann, PhD von Metro.digital erzählt, was sie als Pionierin im Produktmanagement für Datenwissenschaft gelernt hat. Sie spricht auch über den organisatorischen Aufbau, die Kompetenzen, die vorhanden sein müssen, und darüber, wie neue Tools das Management von Data-Science-Produkten beeinflussen.
- [Managing the data science product - an interview with Anna Hannemann, PhD](https://d3mlabs.de/?p=963) - How to manage the data science product, Part 1: Algorithms are now products that need to be managed for business impact. Anna Hannemann, PhD of Metro.digital shares what she has learned as a pioneer in data science product management. She shares some key success factors for data science product development to drive monetization and growth .She also talks about organizational design, competencies that need to be in place and how new tools are impacting how data science products are managed.
- [Wie managt man ein Data Science Produkt?  - Eine Serie von D3M Labs](https://d3mlabs.de/?p=955) - Die Datenwissenschaft entwickelt sich von der Forschung und Entwicklung zu Produkten - sowohl online als auch offline. Die Verwaltung von Datenprodukten erfordert eine Weiterentwicklung sowohl der traditionellen Software- als auch der Hardware-Entwicklung. Einführung in die zweiteilige Serie: Teil 1: Das Management des Data Science Products - ein Interview mit Anna Hannemann, PhD. Dr. Anna Hannemann
- [The prevalence of AI and importance of engaging in dialogue](https://d3mlabs.de/?p=708) - AI is becoming omnipresent in our lives and is shaping our world. Thus wider public involvement in determining how AI is designed and used is important for society. Understanding AI and getting involved in how it is applied and governed might seem daunting, but Varsh Anilkumar offers some ways to get involved and learn about AI.
- [Why creatives in advertising should embrace data science and data mining - an interview with Les Guessing](https://d3mlabs.de/?p=1074) - Contextualizing our world with data, part 1: Advertising. Les Guessing has a high school degree (barely) but has managed to find great success as an Emmy Winning Copywriter / Creative Director in Los Angeles (and beyond) in advertising – the marketing arm of Capitalism. Over the last 10 years, he has become hellbent on using data/Data Science/Machine Learning and aspects of Artificial Intelligence (especially NLP, Natural Language Processing) to make advertising creative more insightful, more efficient, more impactful, and funnier. He explains why creatives should work with data because. Among other reasons, the creative mindset enables them to look at data and see something from an entirely different perspective than data people.
- [Exploring BERT: Feature extraction & Fine-tuning](https://d3mlabs.de/?p=1169) - Natural language processing (NLP) is a set of techniques that aim to interpret and analyze human languages. By using it in more complex pipelines, we can solve predictive analytics tasks and extract valuable insights from unstructured text data. A major breakthrough was made in the field of NLP by the introduction of transformers, which paved the way for large language models (LLMs) and generative AI research (e.g. BERT, BART, GPT). In this article, we walk through different concepts of NLP. In the first section, we summarize the architecture of transformers and highlight its core concepts, such as the attention mechanism. Then, in the second section, we focus on BERT, one of the most popular Transformer-based LLMs, and we present examples of how it is used in data science applications.
- [How can analytics become a revenue generating function?](https://d3mlabs.de/?p=1194) - The first Decision Lab Round Table covered the topic of how to make Analytics a revenue-generating function. We had a cross functional discussion involving data professionals, as well as adjacent professions who are working in Europe and the USA. This blog covers the discussion points, as well as D3M Labs commentary about how analytics should be a business function.
- [Wie kann Analytik zu einer Umsatz generierenden Abteilung werden?](https://d3mlabs.de/?p=1190) - Der erste Decision Lab Round Table befasste sich mit dem Thema, wie man die Analytik zu einer Umsatz generierenden Abteilung machen kann. Wir hatten eine funktionsübergreifende Diskussion unter Beteiligung von Datenexperten und benachbarten Berufsgruppen, die in Europa und den USA arbeiten. Dieser Blog enthält die Diskussionspunkte sowie einen Kommentar von D3M Labs dazu, wie Analytik eine Geschäftsfunktion sein sollte.
- [Lehren aus New York: Es gibt nie "nur Business"](https://d3mlabs.de/?p=85) - In Berlin habe ich mehr als ein paar Mal den Kommentar "das ist nur Business" gehört. In New York habe ich niemals einen solchen Kommentar vernommen. Ganz im Gegensatz zu Berlin wird es in New York über Unternehmensstrategie, Marktentwicklung und Marketingstrategie eifrig diskutiert.
- [The monetisation of customer relevancy](https://d3mlabs.de/?p=88) - The monetisation of customer relevancy through data-driven insights is essential for any successful marketing campaign in the digital economy. With the advent of social media, cloud computing, IoT and mobile applications, data sources and use cases for marketing and communications professionals are proliferating. Companies can collect data on customer preferences, attributes, actions and more to, for example, anticipate demand, increase customer satisfaction and loyalty, as well as proactively capitalize on acquisition, upsell and cross sell opportunities.
- [Turning customer relevancy into revenue](https://d3mlabs.de/?p=79) - Monetizing customer relevancy through data-driven insights is key for any successful modern marketing campaign. Modern marketers work in a hypotheses-driven manner, using data to gain customer insight. Consumers and B2B customers have grown used to marketers understanding who they are, their behaviors, as well as when and how they want to communicate with you.
- [Consumer Insights and Data Analytics: The ying and yang of how and what](https://d3mlabs.de/?p=353) - Consumer Insights is a natural partner of Data Analytics. While data analysts can show you in-depth what is happening, consumer insights can illuminate the how. The partnership between Consumer Insights, Data Analytics and other Insights functions can be powerful. This article will explain the benefits and how organizations can make it work,
- [Data strategy is a part of corporate strategy](https://d3mlabs.de/?p=376) - Matt Brady, Founder of Zuma Recruiting and I talked about Data Strategy. We will start by covering data strategy and roadmaps before discussing how to treat data, data roles and where data should sit in an organization. Data teams add the best value to their organization when they are part of a holistic company strategy discussion and work as strategic partners with the stakeholders.
- [Data only has financial value if it can be monetized - An interview with Michael Guthammar](https://d3mlabs.de/?p=662) - Having no physical form, data is an intangible asset. Data is often a contributory asset as well, its value being realized via the ability to generate profit through, for example, insight used in decision making or algorithmic-product such as a recommendation engine. Certain methods and considerations are required when valuing data.
- [Bridging the gap between data and money](https://d3mlabs.de/?p=677) - This article was co-authored by Elizabeth Press and Peter Schroeter Data is a top priority on almost every C-suite agenda, and for good reason. When data is properly sourced, compiled, and understood, it has the potential to add tremendous value to a company’s profitability and competitive positioning. However, without proper business acumen, data organizations often
- [Building defensibility with Data Moats  - an interview with Raúl Berganza Gómez](https://d3mlabs.de/?p=777) - Competitive advantages enable your business to be successful. Defensibility is what you need to keep that competitive advantage. Data Moats leverage data to create parts of your business that are hard for competitors to replicate. In an open source, fast-moving digital world, building a deep moat gives your business the margin and time to maintain competitiveness. Elizabeth Press #
- [Tackling machine learning enemy #1, poor data quality -  an interview with Sahar Changuel, PhD](https://d3mlabs.de/?p=790) - Data quality is a business problem, as well as a tech problem. It is the biggest enemy of data-driven business and machine learning. Bad quality data can block or render a data project or machine learning use case unusable and thus a waste of money, human resources and time. Tackling data quality needs to be a targeted, systemic and ongoing, rather than a huge, one time cathartic event.
- [Fall in love with the problem, not the data - an interview with Mor Eini](https://d3mlabs.de/?p=810) - Mor Eini’s career started in the Israeli Defense Force in the Office of the Prime Minister and took her to the VC ecosystem in Berlin. Mor Eini from APX, which is an early stage investor, explains how she evaluates a startup’s use of data. Mor also talks about the Israeli and Berlin ecosystems. She also shares her insights as a B2B investor on how data is a tool to create, foster, accelerate innovation, but data is not the innovation.
- [Elevating the analyst - an interview with João Sousa](https://d3mlabs.de/?p=831) - The Future of the Analyst, Part 1: The gap between analytics and impact can be filled with business acumen and empowerment. João Sousa talks about his journey as an analytics practitioner to McKinsey and into diagnostic analytics at a vendor. Knowing the why, understanding the root cause, is the key to driving more business value with data. The root cause and how to change something is the real way to create business impact.
- [Data is about business- an interview with Tristan J Burns](https://d3mlabs.de/?p=911) - The Future of the Analyst, Part 3: Data is about business, strategy and revenue generation. Tristan J Burns shares his transition from banking to being a data leader. Tristan details how he sees the role of a data leader encompassing EQ (emotional intelligence) and enabling the data team to drive strategy and data-driven decision making. The interview also includes how data leaders should be measured and which C-Suite roles they should fill.
- [Can we align on the Definition of SELF-SERVICE ANALYTICS?](https://d3mlabs.de/?p=1157) - Ashish Kalra is an experienced data leader who has been reading about self-service analytics over LinkedIn from different Data Leaders for some time. He has observed that everyone has their own definition of "Self-Service Analytics." In this article, Ashish publishes his own view on the topic and is open to peer and stakeholder feedback.
- [Solving the speed vs. quality experimentation dilemma and growing the New York Times- an interview with Shane Murray](https://d3mlabs.de/?p=1129) - Contextualizing our world with data, part 4: Journalism. Solving the speed vs. quality dilemma and growing the New York Times, also during the Trump years. Shane Murray, Field Chief Technology Officer at Monte Carlo and former Senior Vice President of data & insights at The New York Times, talks with about experimentation and growing a digital subscriber business, the New York Times. Shane talks about how to solve the experimentation speed vs. quality dilemma – and often outright conflict – between business stakeholders and data teams. Shane also talks about how the New York Times transformed itself into a digital subscription product and tech company.
- [Nurturing the customer relationship with data - an interview with Sarah Carr](https://d3mlabs.de/?p=1088) - Contextualizing our world with data, part 2: Customer Relationship Management (CRM). Sarah Carr is a recovering Marketer who has gone on to become a CRM systems nerd. Aside from core CRM, Sarah also works on data governance, data quality, and privacy. Looking back at her journey, Sarah talks about how CRM went from email marketing to automated omni-channel orchestration of the customer experience. Sarah also gives her insight on how data teams and stakeholders can utilize self-service and data education to drive business forward together. Moreover, she discusses how Arts degrees can be good breeding grounds for analytical minds.
- [On the communication front with the Ukrainian PR Army – an interview with Liuka Lobarieva](https://d3mlabs.de/?p=1115) - Contextualizing our world with data, part 3: Public Relations. Liuka Lobarieva, co-founder and coordinator at the Ukrainian PR Army, has been volunteering as a coordinator for Food Safety and Nuclear Safety since Russia invaded Ukraine. She is driven by her conviction that it is important to tell the truth about the war caused by Russia in the very center of Europe today. She does this while she is working as Public Relations and Communications Manager at Datuum.ai, a startup using AI to automate data pipelines. Liuka gives a unique glimpse into the virtual world of PR professionals telling Ukraine’s story and narrates her own experiences before and since the Russian invasion of Ukraine. The Ukrainian PR Army is data-driven. Liuka tells us how.
- [Contextualizing our world with data, a D3M Labs Series](https://d3mlabs.de/?p=1062) - Contextualizing our world with data. A four part D3M Labs series about how communications professionals use data. Writing and other forms of communications might be art, however, technology is the means by which thoughts, news, images, etc. are conveyed, stored, measured and iterated. The impact can range from branding and connecting with customers and prospects, to reporting about world events.
- [<strong>Why is it important to talk about toxic leadership?</strong>](https://d3mlabs.de/?p=1101) - Kasia Musur is a Berlin-based founder of an early-stage startup dealing with toxic leadership through preventive, protective and accountability measures. „A job is a job. A boss is a boss “. For centuries people complain about their work-lives and yet the world goes round. Why is it suddenly such a big deal how we feel about our jobs, colleagues, and bosses?
- [Why managers should drink coffee: A Military Veteran's take on change management](https://d3mlabs.de/?p=694) - Neil Herzog-Gilroy is a former British Army Military Intelligence Operator. He draws on 20 plus years of experience of working with various Intelligence and Law Enforcement Agencies around the world to bring us some food for thought on how to manage change in fast paced environments where people are the most important resource.
- [How to manage the data science product, a D3M Labs Series.](https://d3mlabs.de/?p=942) - Data science is moving from R&D into products - both online and off. Managing data products requires evolution from both traditional software and hardware development. Introducing the two-part series: Part 1: Managing the data science product - an interview with Anna Hannemann, PhD. Anna Hannemann, PhD of Metro.digital shares what she has learned, building on
- [Launching a human understandable data pipeline in times of war - and interview with Dmytro Zhuk](https://d3mlabs.de/?p=1054) - Automating the ETL process using deep learning and semantic data type detection is never easy, especially in the midst of war. One year after Russia’s invasion of Ukraine, Dmytro Zhuk, founder and CTO of Datuum.ai talked to Elizabeth Press from D3M Labs about his experiences as a family man and an entrepreneur in Kharkiv. He also shares his vision and hopes for the future.
- [Is scary data pipeline technical debt haunting your business?](https://d3mlabs.de/?p=443) - Technical debt in your data pipeline will impact your organization in ways that will annoy stakeholders, make the working lives of analysts tedious and frustrate data engineers. This debt can cause embarrassment in front of boards and investors, as numbers can be mismatching and unexplainable. And worse.
- [From analyst to CEO - an interview with Alfredo Carreras](https://d3mlabs.de/?p=896) - Future of the Analyst, Part 2: Despite their geeky reputation, analysts often enjoy working cross-functionally, guiding data-driven decision making. According to a recent D3M Labs Poll, many of them have C-Suite ambitions. Alfredo talks about his journey from analytics to the C-Suite. He explains how a background in analytics is good training ground for data-driven CEOs. He also talks about what analysts need to learn to get the top job and excel.
- [Data Mesh - Wie man verhindert, dass es sich in ein geldverschlingendes Chaos verwandelt - ein Podcast](https://d3mlabs.de/?p=987) - Data Mesh ist eine analytische Datenarchitektur und ein Betriebsmodell, bei dem Daten wie ein Produkt behandelt werden und den Teams gehören, die sie produzieren, d. h. den Geschäftsbereichen. Wie können sich Unternehmen auf den Weg zu Data Mesh machen, ohne ihre Budgets zu sprengen und letztlich einen großen, unübersichtlichen und teuren Datensumpf zu schaffen? Höre dir den Podcast an. Lese den Blog.
- [Data Mesh - How to prevent it from turning into a money draining mess - A podcast](https://d3mlabs.de/?p=977) - Data Mesh is an analytical data architecture and operating model where data is treated like a product and owned by teams who produce it, i.e the busness domains. How can organizations embark on their data mesh journeys without exploding their budgets and ultimately creating a big, mess, expensive data swamp? Listen to the podcast. Read the blog.
- [The future of the analyst](https://d3mlabs.de/?p=820) - This week D3M Labs releases the 3 part series: "The Future of the Analyst." Is the role of the analyst endangered? What is the future of the most visible role in analytics, and the one responsible for delivering the insight? What is the future of the analyst?
- [Why should you adopt data-driven decision making?](https://d3mlabs.de/?p=185) - Data-driven management improves your "soft skills": A data-driven approach to solving problems and leading discourse enhances the tenor of your communication and teamwork, in addition to improving hard performance metrics such as revenue and margin. Data and evidence-based brainstorming can also help turn creative ideas into business transformation. Using specified metrics and analytical methods at key points in your decision processes will improve your accountability. Even if your decision turns out to be sub-optimal, you will be able to explain your actions in a logical and concise manner and understand where you need to improve. Setting goals and measuring how your performance benefits your organization's strategy and tactical goals will allow you to communicate your successes and your prioritized areas of improvement through evidence-based reasoning.
- [Creativity and intuition in a data-driven world](https://d3mlabs.de/?p=75) - A creative mind can discover the insight lurking behind data. When found, it is absolutely necessary in bringing your business forward. In my experience, too many people cut corners here and just use the data or information at hand and/or that which is familiar to them. Approaching it with the right question frames your entire analysis both in terms of strategic and tactical impact, as well as project budget. The right question will also create a clear scope for the data needed, requisite analytical processes and tools, as well as human capital.
- [Turning Big Data Disillusionment into Opportunity with Data-as-a-Service Products](https://d3mlabs.de/?p=158) - Big Data's descent from the peak of inflated expectations into the trough of disillusionment made a splash when Gartner came out with its 2016 Hype Cycle for Business Intelligence and Analytics. This stage is decisive: Big Data either delivers, and so rises a bit further up the slope of enlightenment
- [Elizabeth & Mike talk about Social Media and Data with local entrepreneurs in Soho & New Haven](https://d3mlabs.de/?p=176) - Mike and Elizabeth had a lively discussion about how local entrepreneurs can map the customer journey, as well as use a mix of social media and in person interactions for cost effective solutions to targeting micro customer segments.
- [European Venture Market](https://d3mlabs.de/?p=77) - Confidence in the European venture market seems to be growing, although many participants still cite best practices from the US. Corporate-Startup partnerships with the goal to "learn" "innovation" is in fever pitch in Berlin at the moment. A more diverse investor ecosystem - from very well known investors, to niche investors and corporate investors. Although more diverse does not extend to those who control the capital - the Berlin circle that controls the capital is still tight knit. The German government seems to slowly be realizing the urgent need for early stage financing. BAFA announced their grant for angel investors - Zuschuss für Wägniskapital.
- [Topography of a social media listening project](https://d3mlabs.de/?p=81) - Social media monitoring has received a huge amount of attention in the past year following the explosive popularity of social media platforms coupled with the high-profile predictions in the US presidential elections. I have worked with numerous clients who wanted to build social media listening capabilities. This is an overview of what a social media listening project entails.
- [What is Data-as-a-Service?](https://d3mlabs.de/?p=140) - Data-as-a-Service (DaaS) can be described as productized data-driven insight on demand. DaaS allows business users to access the data and insights they need at the timing they desire. The data and insights can be consumed by multiple individuals simultaneously, location-independent of where the data has been sourced and managed.
- [Data-as-a-Service lessons from the company that was right about Trump](https://d3mlabs.de/?p=142) - One South African company correctly predicted both the outcome of the Brexit vote and Trump's victory. BrandsEye delivered a Data-as-a-Service (DaaS) product, amalgamating social media analysis, geolocation data and other inputs to create impactful insight that most pollsters missed.
- [Are you a shallow innovator? That's ok as long as you can execute.](https://d3mlabs.de/?p=93) - Successful shallow innovation creates and executes a use case for proven technology in a way that is sustainably profitable and/or beneficial to society. I created this term to help clients conceptualize the difference between value created by deep innovation, i.e. disruptive technological or scientific innovation, and those created by shallow innovation coupled with wonderful execution.
- [Julian and the robot- Next-gen user experience (UX) gets social](https://d3mlabs.de/?p=124) - What can we learn about robotics, artificial intelligence and how UX will evolve into the architecture of social-emotional experiences?
- [The D3M Labs Manifesto (English)](https://d3mlabs.de/?p=167) - The world needs more visionaries with big ideas. D3M Labs wants to avail these visionaries the tools they need to successfully go beyond the bounds of the present-day normal. Imagination coupled with brave decisions powered by analytics, executed on scale can and does transform industries, economies and the world. Social networks, the sharing economy, machine learning and more have all fundamentally changed our everyday lives. All of these innovations were brought to us by vision, insight, strategy and excellent execution.
- [Das D3M Labs Manifesto (auf Deutsch)](https://d3mlabs.de/?p=164) - Die Welt braucht mehr Visionäre mit gößen Ideen. D3M Labs möchte diesen Visionären die Werkzeuge zur Verfügung stellen, die sie benötigen, um erfolgreich über die Grenzen des heutigen Normalbetriebs hinauszugehen. Fantasie gepaart mit mutigen Entscheidungen auf der Grundlage von Daten, die in großem Maßtab umgesetzt werden, können und werden Industrien, Wirtschaft und die Welt verändern. Soziale Netzwerke, die gemeinsame Wirtschaft, maschinelles Lernen und mehr haben unseren Alltag grundlegend verändert. Alle diese Innovationen wurden uns durch Vision, Einsicht, Strategie und exzellente Umsetzung nahergebracht.
- [Data meets Communications - takeaways from the Digital Communication Awards](https://d3mlabs.de/?p=95) - At the after party some people asked me for feedback and what they could do better next time. Here is a list of tips that are useful when pitching the impact of your project, as well as to anybody using key performance indicators (KPIs) to communicate the value of your work.
- [Digitale Kommunikation trifft Analytics- Erkenntisse aus den Digital Communication Awards](https://d3mlabs.de/?p=121) - Ich hatte die Ehre, Jurymitglied bei den Quadriga Digital Communication Awards zu sein.Auf der After-Party baten mich einige Leute um Feedback und was sie beim nächsten Mal besser machen könnten. Hier ist eine Liste von Tipps, die nützlich sind, wenn es darum geht, die Wirkung Ihres Projekts zu vermitteln - und an jeden, der Key Performance Indicators (KPIs) verwendet, um den Wert Ihrer Arbeit zu kommunizieren.
- [Customer Segmentation: Rules-based vs. K-Means Clustering](https://d3mlabs.de/?p=1) - Customer segmentation is a means by which you group customers into an identifiable category that you can use as a basis for analysis of a specific group of customers. Customer segmentation is useful for activities such as strategic planning, campaign planning & customer targeting, product analytics, planning customer communications, customer experience management, churn prediction, upselling, cross-selling, acquisition, sales operations and more.
- [Operational KPIs that will let you know your Data Team is creating impact (rather fixing & firefighting)](https://d3mlabs.de/?p=202) - Data teams are usually busy, but are they impactful? Just because your data team is burning through tickets does not mean that they are creating impact, especially if they are stuck fixing and firefighting. Impact can be broken down into prioritization, coverage and quality. KPIs such as the statistical re-do rate, analytical throughput rate and effective analytical throughput rate that will help you quantify the impact of your data organization. This framework, along with external validation from stakeholders, is helpful to root cause and make business cases to invest in improvements.
- [Take aways from Big Data World, May 2022](https://d3mlabs.de/?p=223) - The right mix of governance and freedom in architecture is still up for debate, end-to-end solutions are often-heard recommendations, low and no-code is expanding access to data and the customer journey could be seen as a source of revenue are some insights I gleaned from this spring’s Big Data World.
- [Building your company's first data competency](https://d3mlabs.de/?p=262) - Is business intelligence a luxury? Data - done right - is neither cheap nor easy. Most businesses wait until they are a certain size before investing in an in-house data competency. A greenfield assignment, the initial build-up of an inhouse data function, is an important early step in a company’s journey towards data maturity. Before the inception of an inhouse function dedicated to data, a company can be considered data immature, regardless of who uses the data or how long the company has been around.
- [What I look for when I hire a data professional](https://d3mlabs.de/?p=235) - At the AI Guld Dinner, I was asked by a couple of people about what I look for when I hire data scientists. This advice can be scaled to all data professionals - and beyond.
- [Data Festival 2022: Democracy, Mesh, Fabric](https://d3mlabs.de/?p=244) - The industry seems to be disillusioned by centralized data assets, data warehouse and data lake alike and looking for the next big thing.
- [AI can help defend European freedom](https://d3mlabs.de/?p=254) - A child of the Cold War, I grew up hearing stories and learning deeply about World War 2. Much of my youth was spent pondering the new and old-world order. For that reason, I found the panel at the Data Festival in Munich inspiring. I hope it inspired others in the tech scene to support the use of data in defending European freedom.
- [Babbel Live’s data-informed success: How early stage digital products can be hypothesis driven despite little data](https://d3mlabs.de/?p=390) - Babbel Live is a success story that product managers who are launching new digital products can learn from. Massive amounts of data are not necessary in order to use data to make good decisions. Starting simple and working in a data-informed way to prove or disprove hypotheses can yield positive results quickly.
- [What can stop the cycle of chaos, under investment, attrition and over hiring in data teams? - An interview with Stevan Lazic](https://d3mlabs.de/?p=412) - Data teams are often chaotic places to work, which leads to attrition, over hiring, burn-out and other bad side effects. Stevan Lazic, an experienced product engineering leader who has worked at numerous startups and scaleups, talks with Elizabeth Press about what he thinks is driving the unhealthy dynamic in many data teams and what measures can be taken so that data teams are properly resourced.
- [Aufbau des ersten Data Teams in ihrem Unternehmen](https://d3mlabs.de/?p=555) - Ist Business Intelligence ein Luxus? Daten - richtig gemacht - sind weder billig noch einfach. Die meisten Unternehmen warten, bis sie eine gewisse Größe erreicht haben, bevor sie in eine interne Datenkompetenz investieren. Ein Greenfield-Projekt, der erste Aufbau einer internen Datenfunktion, ist ein wichtiger erster Schritt auf dem Weg eines Unternehmens zur Datenreife. Vor der Einrichtung einer internen Datenfunktion kann ein Unternehmen als Daten unreif gelten, unabhängig davon, wer die Daten nutzt oder wie lange das Unternehmen bereits besteht.
- [Data analysts are often aspiring leaders - Results from a D3M Labs poll](https://d3mlabs.de/?p=514) - According to a D3M Labs poll, many data analysts who answered wanted to move into management, be it product management or people management. Behind the desired career move, was the interest to step back from the keyboard and focus on the communication and greater involvement in business and strategy.
- [The co-dependence between data governance and growth - An interview with Irina Nikiforova](https://d3mlabs.de/?p=550) - Irinia Nikiforova explains what data governance is and why it is essential for any business that not only wants to survive, but use insights from data or data-driven products to drive growth.
- [Data governance starts at both the C-Suite and metadata level of your organization- An interview with Laurent Dresse](https://d3mlabs.de/?p=592) - Facilitating the interface between IT and business is data governance, which is filled with opportunity. There is no specific career path into data governance, but the ability to understand metadata and contextualize organizational insights to executives holds much opportunity.
- [Tech debt sloth breeds a culture of sloppy operations - An interview with Daniele Marmiroli, PhD](https://d3mlabs.de/?p=610) - Tech debt is often unavoidable in most early stage startups. Not fixing the tech debt as a company gets traction and scales is more of a problem than the original creation of the tech debt. Turning a blind eye to tech debt has implications beyond the stack and creates an unstructured and sloppy culture.
- [Data interoperability is a precondition for healthcare innovation - An interview with Jörg (Jack) Godau](https://d3mlabs.de/?p=638) - Healthtech startups such as doctorly and others see the opportunity to reinvent the wheel with SaaS platforms based on open standards in healthcare. The incumbent healthcare system is based on a fragmented landscape of software providers and data solutions. Data interoperability presents an opportunity to unblock innovation in healthcare in Germany and beyond.
- [Die Interoperabilität von Daten als Voraussetzung für Innovation im Gesundheitswesen - Ein Gespräch mit Jörg Godau](https://d3mlabs.de/?p=656) - Startups im Gesundheitswesen wie doctorly sehen die Chance, mit SaaS-Plattformen, die auf offenen Standards im Gesundheitswesen basieren, das Rad neu zu erfinden. Das etablierte Gesundheitssystem basiert auf einer fragmentierten Landschaft von Softwareanbietern und Datenlösungen. Dateninteroperabilität bietet die Chance, Innovationen im Gesundheitswesen in Deutschland und darüber hinaus zu ermöglichen.
- [Growing the AI Guild  - An interview with Dânia Meira, Co-Founder and Director of the AI Guild](https://d3mlabs.de/?p=734) - The AI Guild has become a brand synonymous with AI thought leadership and expertise in the Berlin Tech Scene and beyond. Immigration, integration, sharing personal challenges and working together towards professional growth are all elements of the human story behind the technology that are talked about in this interview and retrospective.
- [Die Zukunft des Analysten](https://d3mlabs.de/?p=826) - In der dreiteiligen Serie, “Die Zukunft des Analysten” wird untersucht, wie sich diese wichtige Rolle weiterentwickeln wird. Wie sieht die Zukunft der sichtbarsten Rolle in der Analytik aus, die für die Bereitstellung von Erkenntnissen verantwortlich ist? Was ist die Zukunft des Analysten?

## Seiten

- [Publications, Events & Partners](https://d3mlabs.de/?page_id=47) - Chairing the CDAO Munich 2026 Conference Chairing Day 1 of the #CDAOGermany 2026 conference in Munich was a privilege. Presentation: Operationalizing AI in a regulated German Industry, where I shared the work I have been doing at Chesco, creating a secure and compliant environment to scale AI in an industrial setting. Host an Ask-Me-Anything on
- [Elizabeth Press, ROI on Digital Business Advisory & Journalism](https://d3mlabs.de/?page_id=45) - Profitable growth Leader and expert in strategy, finance, and data, specializing in data-driven ROI, compliance, and cybersecurity. Proven track record in economic cluster development, venture financing, and driving profitable growth. Cases of Profitable Growth 7-digit soft savings for a Berlin-based scale up due to optimized data processes & governance, successful data tiering & life cycle
- [Subscribe to our YouTube Channel](https://d3mlabs.de/?page_id=1335) - https://www.youtube.com/@d3mlabs Subscribte to the D3M Labs YouTube Channel: https://www.youtube.com/@d3mlabs
- [Contact / Kontakt / Impressum](https://d3mlabs.de/?page_id=46) - Elizabeth Press (D3M Labs) Burgemeisterstr. 1 12099 BerlinTelefon: 0162/2148316 E-Mail: elizabeth.press@d3mlabs.deUmsatzsteuer-Identifikationsnummer gem. § 27a UStG: in der GründungInhaltlich Verantwortlicher gem. § 55 II RStV: Elizabeth Press (Anschrift s.o.)
- [Sample Page](https://d3mlabs.de/?page_id=2) - This is an example page. It's different from a blog post because it will stay in one place and will show up in your site navigation (in most themes). Most people start with an About page that introduces them to potential site visitors. It might say something like this: Hi there! I'm a bike messenger
- [Gestalte deine Website mit Blöcken](https://d3mlabs.de/?page_id=44) - Gestalte deine Website mit Blöcken Füge Block-Vorlagen ein Block-Vorlagen sind vorgefertigte Gruppen von Blöcken. Um eine solche Vorlage hinzuzufügen, wähle die Schaltfläche Block hinzufügen [+] in der Symbolleiste oben im Editor. Wechsle zur Registerkarte „Vorlagen“ unter der Suchleiste, und wähle eine Mustervorlage aus. Rahme deine Bilder Twenty Twenty-One enthält stilvolle Umrandungen für Ihren Inhalt. Wenn

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