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Someone asked me if AI is killing data science. The answer depends on where you sit. Senior data scientists are still in high demand. It’s junior hiring where things get tricky. A lot of the work junior data scientists used to cut their teeth on, like dashboards, SQL queries, and simple ML models, is exactly what AI handles well. Give it clear instructions and it rarely makes syntax mistakes. Where AI still falls short is the open ended, vague business questions. It doesn’t understand the busine
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Cloudflare's Monetization Gateway went live July 1, 2026. Snowflake, Datamatics, and Monte Carlo are all calling 2026 the year clean data becomes the actual bottleneck for AI agents, not the models themselves. Poor data quality is already costing companies 15 to 25% of annual revenue. That part isn't one guy's theory. That's the consensus. The
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Part 1/2 Recursion & Call Stack - Data structures and algorithms explained This function is the simplest example of recursion we can have… BUT, the placement of the print statements really tests your understanding of how recursive code evaluates. 🧠 ANSWER: foo 3 foo 2 foo 1 bar 1 bar 2 bar 3 👀 Did you get it right? In this deceptively simple code snippet, most software engineers know that the foo’s will count down 3..2..1 but far less know that the bar’s will count up 1..2..3. This behavior st
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Data is the new oil, but you need a solid foundation before you can extract it. In 2013, I asked companies if they had small data, because big data alone was useless without clean, centralized info. Fast forward 15 years—AI is everywhere, but it still fails if the data base is shaky. The key lesson? Build a rock‑solid data foundation first, then let AI shine. Ready to audit your data base? #DataFoundation #AI #MachineLearning #BigData #DataStrategy #TechTrends #DigitalTransformation
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