Medipalm - QR App

Project Context

A financial services company needed:

• Real-time transaction monitoring
• Anomaly and fraud detection
• Updated performance metrics
• Automatic reports for stakeholders

Implemented Solution

Real-Time Data Pipeline

• Data ingestion from multiple sources
• Stream processing with Apache Kafka
• Optimized storage in ClickHouse
• REST and GraphQL APIs for queries

Interactive Dashboard

• Dynamic visualizations with D3.js
• Advanced filters and drill-down
• Configurable automatic alerts
• Report export in multiple formats

Integrated Machine Learning

• Automatic detection of anomalous patterns
• Trend prediction
• Automatic transaction classification
• Personalized recommendations

Measurable Impact

📊 99.9% system uptime ⚡ Data latency < 100ms 🎯 98% fraud detection 📈 70% reduction in analysis time

Key Technologies

• Streaming: Apache Kafka, Apache Flink
• Database: ClickHouse, Redis
• Frontend: React, TypeScript, D3.js
• ML: Python, scikit-learn, TensorFlow
• Infrastructure: Kubernetes, Prometheus, Grafana

Client Testimonial

“The analytics dashboard has revolutionized our decision-making capacity. Now we have complete visibility of our operations in real time.” - Ana Martínez, CTO of FinTech Solutions

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*This project demonstrates our ability to handle large volumes of data and create solutions that generate actionable insights.