
4 min read
Last week, I spent a few days in New Orleans for Confluent Current 2025, surrounded by the people who’ve helped build the real-time data movement from the ground up, including engineers, architects, platform leads, and product managers, there to compare notes on…

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Last month, I attended StreamNative’s 2025 Data Streaming Summit, where one trend became unmistakably clear: the center of gravity in AI is shifting from offline model training to agentic AI running directly on real-time streaming systems. Instead of treating AI as a…

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Recently, I read the McKinsey article “Breaking away: The secrets to scaling analytics.” The article discussed their findings on the importance of analytics to a company’s success. Unsurprisingly, they found that the most successful companies spend more money and effort on analytics,…

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There is a massive difference between generating the input data needed by a Machine Learning model once (to prove a concept), and doing it continuously, indefinitely, at scale, and within short time periods. Years of experience working with disparate and imperfect data…

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Not surprisingly, your business has collected a lot of data over the past few years, and you have used some analytical databases or data warehouses to organize and understand your insights. Congratulations, you have taken the 1st step with your data strategy,…