It’s the title of a book. But is it also a deeper observation about what it takes to put good business intelligence in place? Behind this apparently innocuous catch-all pairing (if it isn’t art and it isn’t science, then… it must be religion), there’s a message for those who care to look. Business intelligence today is largely characterized by an analytic approach that involves capturing data, analyzing that data and arriving at a logical conclusion. It’s neat and ordered, and runs in software. Randomness sometimes only seems to come in when analysis runs out of steam or as a qualitative safety-barrier, in case the quantitative side is taking us over a cliff. Science first, art afterwards? Why not both art and science at the same time?
The art & science of business intelligence
Sean Salleh
Sean Salleh is a data scientist with experience in guiding marketing strategy from building marketing mix models, forecasting models, scenario planning models, and algorithms. He is passionate about consumer technologies and resource management. He has master's degrees in Operations Research from University of California Irvine and Mathematics from Northeastern University.
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