Behind the Findings.

The business questions, the work behind the numbers, and what the evidence actually says.

/01 — Predictive analytics

Financial Operations Analytics

How can a SaaS business forecast revenue and identify valuable customers at risk of leaving?

PythonPower BIScikit-learnProphet

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/02 — Customer intelligence

Retail & Marketing Analytics

Which customers, categories, and regions should a retailer prioritize, and is discounting associated with stronger sales?

PythonPandasPower BIJupyter

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/03 — Data engineering & BI

E-Commerce Data Warehouse

How can raw e-commerce records become a reliable foundation for revenue, customer, and delivery reporting?

PostgreSQLSQLPythonPower BI

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/04 — Database reliability

ACID Transaction Ledger

How can a fund-transfer system protect balances when a transaction fails or multiple transfers happen at once?

PostgreSQLPythonSQLAlchemyPsycopg2

[ View case study ]