{"repo":"analyticsdurgesh/FraudStream-Lakehouse","free":true,"listed":false,"github":"https://github.com/analyticsdurgesh/FraudStream-Lakehouse","clone":"git clone https://github.com/analyticsdurgesh/FraudStream-Lakehouse.git","description":"Real-time fraud detection lakehouse with Kafka, medallion pipelines, data quality, explainable scoring, and dashboards.","language":"Python","stars":13,"topics":["airflow","data-engineering","data-quality","databricks","fraud-detection","kafka","lakehouse","medallion-architecture","plotly-dash","terraform"],"license":"MIT","category":"data-pipelines","readme_excerpt":"FraudStream Lakehouse Real-time fraud detection lakehouse built for data engineering portfolios, student labs, and production-style demos. --- FraudStream Lakehouse simulates fintech transactions, streams events through Kafka, lands raw data, applies Bronze/Silver/Gold lakehouse processing, scores transactions with explainable fraud rules, quarantines bad records, and serves analyst-ready dashboards. This repository is designed so students only fill environment variables when they move beyond local mode. The offline demo runs end to end without paid cloud services. Navigation Start Here Deep Dive Production Path --- --- --- Setup Guide Architecture Cloud Deployment Requirements Data Contracts Runbook Dashboard Guide Fraud Rules Interview Story Executive Snapshot Architecture Pipeline Movie What This Project Demonstrates - Real-time event generation for transactions, logins, devices, and chargebacks. - Kafka-based streaming ingestion with an offline JSONL mode for easy teaching. - Medallion architecture with Bronze, Silver, and Gold layers. - Data contracts for every event type. - Data quality checks with quarantine instead of silent drops. - Explainable fraud scoring with risk scores, bands, and reason codes. - Business-facing Gold tables for analysts and operations teams. - Dash dashboard for visual monitoring. - CI workflow, Terraform templates, Databricks notebooks, and Airflow DAG template. - Public-repo-safe secret handling using .env.example only. System Capabilities Ca","default_branch":null,"files":null,"tree":[],"storefront":"/r/analyticsdurgesh","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/analyticsdurgesh/FraudStream-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."}