Our presentation focuses on the crisis simulation tool developed for Euroclear to evaluate institutional resilience under stress. Built on a smart combination of machine learning, deep analytics, and intuitive algorithms, the tool makes complex risk simulations both accessible and actionable. The presentation briefly explains the tool’s capabilities and elaborates on the technical implementation and strategic challenges during its development.

Hoe zorg je ervoor dat je data sneller, betrouwbaarder en met minder handmatige werkzaamheden beschikbaar is voor analyse? Anne Marthe den Hartog (Aviation & Business Intelligence specialist) en Wim Fieret (Data & Analytics specialist) van Rotterdam The Hague Airport vertellen hoe zij de overstap maakten van hun oude manier van datavoorbereiding naar een low-code datafundament met TimeXtender. Tijdens deze sessie delen ze hun ervaringen en praktische voordelen die deze nieuwe werkwijze oplevert.

AI is redefining the future. Technology is changing faster than ever; people have new ways of interacting with technology, and organizations are adapting and adopting this change. However, Trusted AI can only be built on trusted data. We will dive deep into how AWS is helping customers build a trusted data foundation as they embark on their AI journey to build outcomes that are tailored to their business needs. HEMA will present their journey towards a strong Data Platform and Data Governance strategy on AWS, and the business outcomes they achieved.

80% of analytics effort goes into preparing data due to poor goal setting, data complexity, and lack of best practices. This roundtable covers engaging business teams, aggregating disparate sources, moving to online collaboration, and empowering analysts to build transformations without programmers. Essential for anyone in operational analytics.

Everyone talks about data products, but what are they really? Join GoodData’s Ryan Dolley for an interactive talk on defining, building, and scaling data products for real business value. Learn key principles, common pitfalls, and share real-world wins. Whether you're in engineering, product, or analytics, you'll leave with a clear framework to succeed with data products.

Send us a text In this episode, we explore how public media can build scalable, transparent, and mission-driven data infrastructure - with Emilie Nenquin, Head of Data & Intelligence at VRT, and Stijn Dolphen, Team Lead & Analytics Engineer at Dataroots. Emilie shares how she architected VRT’s data transformation from the ground up: evolving from basic analytics to a full-stack data organization with 45+ specialists across engineering, analytics, AI, and user management. We dive into the strategic shift from Adobe Analytics to Snowplow, and what it means to own your data pipeline in a public service context. Stijn joins to unpack the technical decisions behind VRT’s current architecture, including real-time event tracking, metadata modeling, and integrating 70+ digital platforms into a unified ecosystem. 💡 Topics include: Designing data infrastructure for transparency and scaleBuilding a modular, privacy-conscious analytics stackMetadata governance across fragmented content systemsRecommendation systems for discovery, not just engagementThe circular relationship between data quality and AI performanceApplying machine learning in service of cultural and civic missionsWhether you're leading a data team, rethinking your stack, or exploring ethical AI in media, this episode offers practical insights into how data strategy can align with public value.

This session explores the building blocks of next-generation data platforms, with a focus on framing the right questions to unlock innovation. We’ll showcase how AWS Glue, ETL pipelines, crawlers, and data catalogs can transform raw data into analytics-ready insights. Drawing on hands-on experience, we’ll share forward-thinking strategies, lessons learned, and emerging best practices to help you architect a data foundation that is intelligent, adaptable, and future-proof.

Rabobank, a 120 year-old global cooperative bank, underwent a deep transformation in the way it garners and leverages digital analytics data to inform business units and boost operational effciency. In this fireside chat, Stefan Leever, Product Manager of Customer Engagement at Rabobank, will share why the change was necessary, how the team successfully deployed and onboarded a new digital analytics solution, and what tangible business benefits this has delivered.

Text-to-SQL promised self-serve analytics, but it failed to deliver trust. Accuracy plateaued, context was lost, and hallucinations eroded confidence. In this talk, we’ll explore what comes after: reliable, proactive AI analytics powered by semantic understanding and agentic systems.

Sligro Food Group, Dutch market leader in food service, needed to centralise data to improve retail decision-making and stay competitive. Moving away from on-premise databases, they simplified integration to GCP. Join this session to learn why centralised data is key for Sligro, why enterprises choose Fivetran over legacy tools, and how to integrate data into the cloud for real-time analytics.

Struggling with fragmented data and slow insights? Companies using warehouse-native analytics experience 30% faster time-to-insight. In this session, discover how to eliminate data silos, build real-time dashboards, and drive data-driven experimentation directly from your warehouse. Learn how to transform your analytics infrastructure and achieve faster, more impactful results.

Brought to You By: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. Statsig built a complete set of data tools that allow engineering teams to measure the impact of their work. This toolkit is SO valuable to so many teams, that OpenAI - who was a huge user of Statsig - decided to acquire the company, the news announced last week. Talk about validation! Check out Statsig. •⁠ Linear – The system for modern product development. Here’s an interesting story: OpenAI switched to Linear as a way to establish a shared vocabulary between teams. Every project now follows the same lifecycle, uses the same labels, and moves through the same states. Try Linear for yourself. — The Pragmatic Engineer Podcast is back with the Fall 2025 season. Expect new episodes to be published on most Wednesdays, looking ahead. Code Complete is one of the most enduring books on software engineering. Steve McConnell wrote the 900-page handbook just five years into his career, capturing what he wished he’d known when starting out. Decades later, the lessons remain relevant, and Code Complete remains a best-seller. In this episode, we talk about what has aged well, what needed updating in the second edition, and the broader career principles Steve has developed along the way. From his “career pyramid” model to his critique of “lily pad hopping,” and why periods of working in fast-paced, all-in environments can be so rewarding, the emphasis throughout is on taking ownership of your career and making deliberate choices. We also discuss: • Top-down vs. bottom-up design and why most engineers default to one approach • Why rewriting code multiple times makes it better • How taking a year off to write Code Complete crystallized key lessons • The 3 areas software designers need to understand, and why focusing only on technology may be the most limiting  • And much more! Steve rarely gives interviews, so I hope you enjoy this conversation, which we recorded in Seattle. — Timestamps (00:00) Intro (01:31) How and why Steve wrote Code Complete (08:08) What code construction is and how it differs from software development (11:12) Top-down vs. bottom-up design approach (14:46) Why design documents frustrate some engineers (16:50) The case for rewriting everything three times (20:15) Steve’s career before and after Code Complete (27:47) Steve’s career advice (44:38) Three areas software designers need to understand (48:07) Advice when becoming a manager, as a developer (53:02) The importance of managing your energy (57:07) Early Microsoft and why startups are a culture of intense focus (1:04:14) What changed in the second edition of Code Complete  (1:10:50) AI’s impact on software development: Steve’s take (1:17:45) Code reviews and GenAI (1:19:58) Why engineers are becoming more full-stack  (1:21:40) Could AI be the exception to “no silver bullets?” (1:26:31) Steve’s advice for engineers on building a meaningful career — The Pragmatic Engineer deepdives relevant for this episode: • What changed in 50 years of computing • The past and future of modern backend practices • The Philosophy of Software Design – with John Ousterhout • AI tools for software engineers, but without the hype – with Simon Willison (co-creator of Django)  • TDD, AI agents and coding – with Kent Beck — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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Rabobank scales GenAI through complementary approaches. First, with an analytics platform strategy: a lab platform for low-friction experimentation on non-sensitive data, and a lab platform for secure development and a governed promotion path to production. Second, the availability of re-usable GenAI building blocks that enable secure, responsible, standardized, and scalable development of GenAI solutions.

Hoe maak je 100 miljoen sensormetingen per dag bruikbaar voor engineers en analisten? In deze sessie laten we zien hoe Heerema met een klein datateam een schaalbaar self-service data platform bouwde met Databricks en dbt, waarmee ruwe metingen worden omgezet in betrouwbare datamodellen voor verschillende analyses en teams.

We tell about our journey of going from a fragmented analytics landscape towards a platform with curated datasets and consolidated metrics for analytics within Rituals using the concepts of data domains, data contracts and defining everything-as-code.

Session en ligne présentant les différences entre Data Analytics et Data Science & AI, afin d’aider à choisir la formation adaptée. Le rôle clé de l’IA dans les formations et comment elle est intégrée, ainsi que des informations pratiques sur le programme, les formats, le financement et les admissions.

Before you start cramming tools to land a data job, ask yourself this: What tools are data analysts actually using every day? In this episode, I went straight to the pros—analysts at Google, Amazon, Apple, Tesla, Humana, Veterans United, 7-Eleven, and more—to hear which tools truly power their work. ✨ Try Julius today at https://landadatajob.com/Julius-YT 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩‍💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 00:00 - Introduction 00:22 - Sundas Khalid (Google and Amazon) 03:10 - Jen Hawkins (Apple) 06:17 - Ryan Ponder (Veterans United) 07:32 - Alex Sanchez (7-Eleven) 09:37 - Jason Bryll (Healthcare Analytics Expert) 12:47 - Erin Shina (Humana) 14:54 - Lily BL (Tesla) 🔗 Watch my interviews and connect with our data experts! Sundas 🤝 LinkedIn: https://www.linkedin.com/in/sundaskhalid/ 🎥 YouTube: https://youtu.be/e53U55HbBog?si=_hQkB2EuuD1pFsg7 Jen 🤝 LinkedIn: https://www.linkedin.com/in/jeandriska/ 🎥 YouTube: https://youtu.be/f-BWp_IJZ-I?si=llWBc5hIW80SmeEd

Ryan 🤝 LinkedIn: https://www.linkedin.com/in/rtponder/ 🎥 YouTube: https://youtu.be/bH0wfE342R0?si=iN1ftUN31LbstdRw

Alex 🤝 LinkedIn: https://www.linkedin.com/in/ale-san/ 🎥 YouTube: https://youtu.be/VfrTaw27rDc?si=IlwL7FJLdUvlbbms

Jason 🤝 LinkedIn: https://www.linkedin.com/in/jason-bryll/ 🎥 YouTube: https://youtu.be/Qh4RBY5GwUY?si=HCvF80qw7gVbL0dc

Erin 🤝 LinkedIn: https://www.linkedin.com/in/erinshina/ 🎥 YouTube: https://youtu.be/5gSUqk1AiWM?si=MPF3oRY45B2DTQ2P

Lily 🤝 LinkedIn: https://www.linkedin.com/in/lilybl/ 🎥 YouTube: https://youtu.be/AB2McisjPTM?si=yw_2gCWtBcQDFGWf

🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

The manufacturing floor is undergoing a technological revolution with industrial AI at its center. From predictive maintenance to quality control, AI is transforming how products are designed, produced, and maintained. But implementing these technologies isn't just about installing sensors and software—it's about empowering your workforce to embrace new tools and processes. How do you overcome AI hesitancy among experienced workers? What skills should your team develop to make the most of these new capabilities? And with limited resources, how do you prioritize which AI applications will deliver the greatest impact for your specific manufacturing challenges? The answers might be simpler than you think. Barbara Humpton is President and CEO of Siemens Corporation, responsible for strategy and engagement in Siemens’ largest market. Under her leadership, Siemens USA operates across all 50 states and Puerto Rico with 45,000 employees and generated $21.1 billion in revenue in fiscal year 2024. She champions the role of technology in expanding what’s humanly possible and is a strong advocate for workforce development, mentorship, and building sustainable work-life integration. Previously, she was President and CEO of Siemens Government Technologies, leading delivery of Siemens’ products and services to U.S. federal agencies. Before joining Siemens in 2011, she held senior roles at Booz Allen Hamilton and Lockheed Martin, where she oversaw programs in national security, biometrics, border protection, and critical infrastructure, including the FBI’s Next Generation Identification and TSA’s Transportation Workers’ Identification Credential. Olympia Brikis is a seasoned technology and business leader with over a decade of experience in AI research. As the Technology and Engineering Director for Siemens' Industrial AI Research in the U.S., she leads AI strategy, technology roadmapping, and R&D for next-gen AI products. Olympia has a strong track record in developing Generative AI products that integrate industrial and digital ecosystems, driving real-world business impact. She is a recognized thought leader with numerous patents and peer-reviewed publications in AI for manufacturing, predictive analytics, and digital twins. Olympia actively engages with executives, policymakers, and AI practitioners on AI's role in enterprise strategy and workforce transformation. With a background in Computer Science from LMU Munich and an MBA from Wharton, she bridges AI research, product strategy, and enterprise adoption, mentoring the next generation of AI leaders. In the episode, Richie, Barbara, and Olympia explore the transformative power of AI in manufacturing, from predictive maintenance to digital twins, the role of industrial AI in enhancing productivity, the importance of empowering workers with new technology, real-world applications, overcoming AI hesitancy, and much more. Links Mentioned in the Show: Siemens Industrial AI SuiteConnect with Barbara and OlympiaCourse: Implementing AI Solutions in BusinessRelated Episode: Master Your Inner Game to Avoid Burnout with Klaus Kleinfeld, Former CEO at Alcoa and SiemensRewatch RADAR AI where...

Tristan talks with Mikkel Dengsøe, co-founder at SYNQ, to break down what agentic coding looks like in analytics engineering. Mikkel walks through a hands-on project using Cursor, the dbt MCP server, Omni's AI assistant, and Snowflake. They cover where agents shine (staging, unit tests, lineage-aware checks), where they're risky (BI chat for non-experts), and how observability is shifting from dashboards to root-cause explanations. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.

Dante joins the Inside Economics team to talk about the August employment report. After another set of weak numbers, Mark declares that the economy has entered a jobs recession. Cris and Marisa agree, but Dante would like to see more evidence. They also discuss how the lack of hiring is disproportionately impacting young workers. They wrap up by considering what it all means for the Fed, in light of a big jump in market expectations for more drastic rate cuts by the end of the year.   Guest: Dante DeAntonio, Senior Director of Economic Research, Moody's Analytics Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

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