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DataScience Show Podcast

Podcast af Mirko Peters

engelsk

Videnskab & teknologi

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Læs mere DataScience Show Podcast

Welcome to The DataScience Show, hosted by Mirko Peters — your daily source for everything data! Every weekday, Mirko delivers fresh insights into the exciting world of data science, artificial intelligence (AI), machine learning (ML), big data, and advanced analytics. Whether you’re new to the field or an experienced data professional, you’ll get expert interviews, real-world case studies, AI breakthroughs, tech trends, and practical career tips to keep you ahead of the curve. Mirko explores how data is reshaping industries like finance, healthcare, marketing, and technology, providing actionable knowledge you can use right away. Stay updated on the latest tools, methods, and career opportunities in the rapidly growing world of data science. If you’re passionate about data-driven innovation, AI-powered solutions, and unlocking the future of technology, The DataScience Show is your essential daily listen. Subscribe now and join Mirko Peters every weekday as he navigates the data revolution! Keywords: Daily Data Science Podcast, Machine Learning, Artificial Intelligence, Big Data, AI Trends, Data Analytics, Data Careers, Business Intelligence, Tech Podcast, Data Insights. datascience.showBecome a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

Alle episoder

73 episoder

episode Data Contracts as Organizational Glue: Building Trust Between Data Producers and Consumers cover

Data Contracts as Organizational Glue: Building Trust Between Data Producers and Consumers

Enterprises routinely stall when the handoff between data producers and consumers is informal, slow, or mistrusted. This episode reframes data contracts as a strategic operating lever—an organizational capability that formalizes expectations, encodes SLAs, and makes data a reliable, auditable input for decisioning and models. Mirko walks through the executive view: what a pragmatic data contract program looks like, how to link contracts to incentives and budgets, trade-offs between rigor and speed, and the technical patterns that make contracts enforceable in production. Listeners will get a realistic playbook for starting small, measuring impact, and avoiding common pitfalls—how to pilot contracts for high-value pipelines, negotiate producer/consumer responsibilities, and align legal, compliance, and engineering. The episode ends with concrete success metrics executives can use to track adoption, ROI, and risk reduction. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support [https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support?utm_source=rss&utm_medium=rss&utm_campaign=rss]. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn [https://www.linkedin.com/in/m365showpodcast/] if you want decision-ready frameworks, not hype.

24. maj 2026 - 10 min
episode Model Observability for Execs: Turning Observability into Business Controls cover

Model Observability for Execs: Turning Observability into Business Controls

Most enterprises can build models, but few have turned model observability into a strategic control plane. This episode gives C-level leaders a practical blueprint for treating model observability as a business capability that enforces reliability, cost controls, regulatory readiness, and measurable ROI. Mirko narrates a monologue-style deep dive into what meaningful observability metrics look like across data, models, and outcomes; how to define model SLOs tied to business KPIs; designing executive-friendly alerts and dashboards; organizational ownership and escalation paths; trade-offs between fidelity, volume, and cost; and pragmatic rollout steps for integrating observability into procurement, contracts, and governance. Concrete use cases—credit scoring, pricing engines, and churn prediction—illustrate how observability prevented revenue loss and compliance incidents. Listeners will leave with an actionable framework to align engineering, risk, and the business so observability stops being a technical afterthought and becomes an executive control. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support [https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support?utm_source=rss&utm_medium=rss&utm_campaign=rss]. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn [https://www.linkedin.com/in/m365showpodcast/] if you want decision-ready frameworks, not hype.

I går - 10 min
episode Insuring AI: Enterprise Strategies for Liability, Risk Transfer, and Governance cover

Insuring AI: Enterprise Strategies for Liability, Risk Transfer, and Governance

Many organizations treat insurance and legal frameworks as afterthoughts while deploying AI systems; that gap creates real financial and operational exposure. This episode presents a practical playbook for C-level leaders to treat AI liability as a measurable enterprise risk: how to translate model failure modes into insurable exposures, design contractual risk allocation with vendors and partners, price retention vs. transfer, and align governance, audit trails, and observability to meet underwriter needs. Mirko walks through real-world examples across fintech, healthcare, and commerce showing how insurers underwrite technology risk, what controls materially reduce premiums, and how to build cross-functional processes (legal, risk, data science, procurement) that make risk transfer feasible and defensible. Listeners will get concrete steps to quantify risk, negotiate policies, design clause templates, and instrument systems so insurance becomes a strategic tool rather than a false safety net. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support [https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support?utm_source=rss&utm_medium=rss&utm_campaign=rss]. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn [https://www.linkedin.com/in/m365showpodcast/] if you want decision-ready frameworks, not hype.

22. maj 2026 - 10 min
episode AI Investment Portfolio: A C-Level Playbook to Prioritize and Fund AI Initiatives cover

AI Investment Portfolio: A C-Level Playbook to Prioritize and Fund AI Initiatives

Executives face a steady stream of AI proposals but rarely a disciplined method to prioritize, fund, and scale the ones that produce measurable business value. This episode introduces a pragmatic AI investment portfolio framework for C-level leaders: define expected value and risk profiles, adopt stage-gated funding, balance short-term operational wins with strategic bets, and align capacity across data, engineering, and governance. I unpack concrete metrics—expected value, time-to-impact, cost-to-production—and a simple scoring model plus an executive review cadence that converts pilots into a diversified portfolio. Through concise, real-world examples I show common trade-offs (double down, pivot, or sunset), resource reallocation strategies, and how to avoid “pilot trap” churn. The monologue closes with governance templates, scoring pitfalls to avoid, and a repeatable 90-day playbook for prioritization and funding decisions that help leaders maximize ROI and institutionalize sustained AI value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support [https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support?utm_source=rss&utm_medium=rss&utm_campaign=rss]. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn [https://www.linkedin.com/in/m365showpodcast/] if you want decision-ready frameworks, not hype.

4. maj 2026 - 9 min
episode Building the AI Runway: Executive Capacity Planning to Sustain AI at Scale cover

Building the AI Runway: Executive Capacity Planning to Sustain AI at Scale

Many AI initiatives stall not because the models are weak but because organizations run out of runway: data availability, compute, talent, or governance capacity. This episode gives C-level leaders a concise, operational framework to build a multi-year AI runway that aligns strategy, budget, and operational reality. Mirko walks through how to quantify dataset velocity, forecast feature engineering throughput, size compute and storage for production workloads, plan hiring and skill shifts, and bake governance and compliance into capacity decisions. The approach focuses on decision-driven metrics, cross-functional slos, and sanity checks that separate optimistic experiments from fundable, repeatable programs. Listeners will get an executive checklist, three realistic forecasting templates, and example trade-offs—so you can present a defensible three-year AI capacity plan to your board or executive committee. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support [https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support?utm_source=rss&utm_medium=rss&utm_campaign=rss]. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn [https://www.linkedin.com/in/m365showpodcast/] if you want decision-ready frameworks, not hype.

3. maj 2026 - 10 min
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En fantastisk app med et enormt stort udvalg af spændende podcasts. Podimo formår virkelig at lave godt indhold, der takler de lidt mere svære emner. At der så også er lydbøger oveni til en billig pris, gør at det er blevet min favorit app.
Rigtig god tjeneste med gode eksklusive podcasts og derudover et kæmpe udvalg af podcasts og lydbøger. Kan varmt anbefales, om ikke andet så udelukkende pga Dårligdommerne, Klovn podcast, Hakkedrengene og Han duo 😁 👍
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