Modelling
Beyond Market Intelligence keeps Modelling in one place: 3 stories so far. The section currently leads with “Track zeolite crystallization with a practical Python tutorial on spectral unmixing”, “Beyond Flat Tables A Practical Guide to Star Schema Dimensions”, and “Explore smarter retention strategies with pre-churn scoring and uplift modeling”. Zeolite crystallization is notoriously hard to track in real time. Dimensions often get treated as a single concept, but they come in distinct types, each serving a different analytical purpose. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every Modelling story on Beyond Market Intelligence, newest first.
Track zeolite crystallization with a practical Python tutorial on spectral unmixing
Zeolite crystallization is notoriously hard to track in real time. This tutorial shows you how to do it with spectral unmixing and real in situ data, using Python from start to finish. The approach is practical and reproducible, no black boxes, just non-negative least squares modelling applied to Raman spectra. If your spreadsheet memory keeps spiking on large data loads, you might also appreciate why streaming solves that problem.
Beyond Flat Tables A Practical Guide to Star Schema Dimensions
Dimensions often get treated as a single concept, but they come in distinct types, each serving a different analytical purpose. This guide breaks down those variations clearly, helping you choose the right structure for your data model. It's a practical read for anyone moving beyond basic spreadsheets and into more deliberate design. If you are curious about how structured thinking applies elsewhere, our piece on bridging retrieval and action offers a useful parallel.
Explore smarter retention strategies with pre-churn scoring and uplift modeling
Customer churn is a quiet leak in FinTech, one that erodes growth long before it hits a dashboard. This practical guide pairs pre-churn scoring with uplift modelling to show you not just who might leave, but which interventions actually change the outcome. It's a smarter, more human approach to retention. We appreciate the focus on actionable insight over theory. For those eager to expand their analytical toolkit, our guide to distributed training offers a complementary technical deep dive.