{"repo":"MPGranji/retail-banking-customer360-lakehouse","free":true,"listed":false,"github":"https://github.com/MPGranji/retail-banking-customer360-lakehouse","clone":"git clone https://github.com/MPGranji/retail-banking-customer360-lakehouse.git","description":"End-to-end retail banking Lakehouse for Customer 360, segmentation, churn analytics, and cross-sell campaigns using Spark, Iceberg, MinIO, Trino, Airflow, and Docker Compose.","language":"Python","stars":25,"topics":["airflow","iceberg","postgresql","spark","superset","trino","banking","dataengineering","oracle","docker"],"license":null,"category":"deployment-docker-iac","readme_excerpt":"Customer 360 Lakehouse for Retail Banking Customer 360 Lakehouse is a Docker-based retail banking data platform for Customer 360 analytics. It integrates customer, account, card, CRM, transaction, branch, and product data into curated Lakehouse layers for segmentation, campaign targeting, and customer follow-up. Main use case: Marketing/CRM can find customers for credit cards, deposits, personal loans, or wealth management without waiting for manual extraction across separate systems. The serving layer exposes governed SQL tables and Superset dashboard views. 1. Business Context In many retail banks, customer data lives across several operational systems: - Core Banking holds customers, accounts, deposits, loans, products, branches, and account transactions. - Card and CRM systems hold card transactions, campaign history, customer interactions, and consent signals. - Business teams need a unified view, but raw data often contains sensitive fields such as names, phone numbers, national IDs, and email addresses. The workflow lands source data into Bronze, standardizes it through Silver, builds Gold marts with historical changes, and publishes masked tables to Sandbox. Marketing access goes through Trino/Superset on sandbox tables only; raw PII stays outside the business-facing layer. 2. Project Structure 3. Data Set The demo data is synthetic and deterministic. The generator uses seed: 42 , a baseline cob dt of 2025-12-31 , and 12 months of transaction history. The day-2 flow u","default_branch":null,"files":null,"tree":[],"storefront":"/r/MPGranji","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/MPGranji/retail-banking-customer360-lakehouse/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}