How to Work with Data and AI to Improve Doing Business

Most companies talk about becoming data-driven or adopting AI, and few actually improve the business as a result.Maren Vos joins our Coffee Pod to talk about the practical side of working with data and AI.how to set up platforms that support the business,why organizational design (including approaches like Data Mesh) mattershow to avoid the classic dashboard trap, and what it takes to make data truly useful for decision-making and processes.We also cover the jump from academia to industry, leadership skills, and advice for early-career data professionals.0:00 Teaser: The Legend of 'Tom'0:40 Welcome to Coffee & Bites1:45 From Academia to Industry Data Science4:47 Early Career Realities: APIs and Programming Stacks9:53 Demystifying Data Mesh and Data Products16:50 Hurdles in Decentralization and Shadow IT24:45 Bronze, Silver, and Gold Data Layers Explained29:46 Balancing Technical and Leadership Skills38:04 Common Pitfalls in Building a Data-Driven Culture47:15 Career Advice for Young Data Professionals54:01 Final Takeaways and Outro====================================📝 Show Notes====================================https://www.linkedin.com/in/marenvos/Tom meme: https://www.linkedin.com/feed/update/urn:li:share:7402599186782638080/====================================☕️ Join our Discord Community====================================We post our content also in discord, never miss an episode. We also sometimes go live there. Join us there: https://coffeenbytes.com/discord====================================🎙️ Want to be a guest ?====================================👉 We do all our recording online. Apply here: https://coffeenbytes.com/guest====================================🎙️ All our Podcast Links:====================================https://coffeenbytes.com/https://x.com/coffee_n_byteshttps://www.linkedin.com/company/coffeenbyteshttps://creators.spotify.com/pod/profile/coffeenbytes/====================================Host: https://www.linkedin.com/in/costaruitiago/====================================