Fitelo

I had a wonderful time being a part of the panel discussion on career opportunities in nutrition on the occasion of World Health Day, focusing on AI advances in this field. Alongside esteemed panel members, it was a great opportunity to exchange insights, discuss emerging trends, and reflect on how innovation is transforming the future of nutrition.

I’ve been noticing more and more conversations about how LinkedIn has “changed”- that it feels less thoughtful, and overly AI-generated. I keep wondering if these two things are actually connected. Because if they are, it does make a certain kind of sense. Writing something meaningful takes time and effort, but whether it gets seen depends on reach, and reach is largely shaped by algorithms. AI tools are simply better at playing that game: structuring content in ways that capture attention, spark reactions, and travel further. And so, people adapt. From a psychological perspective, this feels less like a problem with individuals and more like a reflection of the environment we’re in. We’re not just competing for jobs or opportunities anymore - we’re also competing for visibility, for attention, for relevance. And when the “rules” keep shifting, it can feel easier to rely on tools that promise to keep up. But somewhere in that process, I find myself wondering - Are we still saying what we mean, or *just* what performs best?

This week, I gained a much clearer understanding of how data actually flows before it reaches Power BI — and it’s not as simple as it looks 👀 Earlier, I used to think data just “comes” into Power BI ready to use. But in reality, it goes through multiple layers and transformations before we even start building dashboards. Here’s the simplified flow I learned: 🔹 Data comes from different sources (APIs, databases, files, etc.) 🔹 It is stored in its raw form in the Lakehouse (Bronze layer) 🔹 Then it is cleaned, validated, and structured into Delta Tables (Silver layer) 🔹 Finally, this refined data is used in Power BI for reporting Understanding Medallion Architecture (Bronze → Silver → Gold) and the difference between Files vs Tables really connected the dots for me. Dashboards are just the final layer — the real game is how well the data is prepared. If you're exploring Microsoft Fabric or Power BI, would love to hear your thoughts — let’s connect in the comments 👇 #PowerBI #MicrosoftFabric #DataAnalytics #LearningJourney #Lakehouse #DataEngineering