01
AI vs traditional analysis: the engine-and-driver model
You no longer need SQL to ask the question. You still need to know which question to ask.
Traditional pipeline: collect from teams, store, join tables, analyse, present with recommendations. AI changes three things: it automates cleaning (missing values), outliers and pattern spotting; it handles massive datasets; and natural language replaces SQL and Python ('I just express what I want'). It also adds predictive power (Netflix recommendations, sensor-based failure prediction). The analyst remains the driver - deciding which relationships and questions to pursue - and AI needs quality data and skilled people.
Why it matters
Sets up why the next six lessons teach vocabulary before tools.
This idea elsewhereparallelKairos analytics on actionability