Project Context
A consulting company needed a solution for predictive analysis of client data, but faced challenges with existing tools that were slow and inaccurate.
Results Achieved
Metrics that demonstrate the project's impact
Development Process
Methodology applied to ensure project success
Requirements Research & Analysis
Identification of predictive analysis needs and definition of main KPIs for the business.
- Stakeholder interviews
- Historical data analysis
- Success metrics definition
ML Model Development
Creation and training of machine learning models with TensorFlow for predictive analysis.
- Advanced algorithm selection
- Historical data training
- Validation and optimization
REST API Creation
Development of robust APIs with Node.js for data processing and delivery.
- Scalable RESTful APIs
- PostgreSQL integration
- Intelligent caching system
React Interface Development
Creation of intuitive dashboard with real-time visualizations and optimized experience.
- Interactive dashboard
- Reusable components
- Full responsiveness
Testing & Performance Optimization
Implementation of automated tests and optimization to ensure maximum performance.
- Automated testing
- Query optimization
- Continuous monitoring
Deploy & Monitoring
Production implementation with CI/CD and advanced 24/7 monitoring.
- Automated deployment
- Real-time monitoring
- Alert system
Challenges & Solutions
Main challenges faced and how they were overcome
Large Volume Processing
Implementation of optimized algorithms to process millions of records in real-time.
Solution: Use of parallelization techniques and intelligent caching
Legacy System Integration
Connecting with old systems without interrupting existing operations.
Solution: Development of adapters and compatibility APIs
ML Model Optimization
Ensuring maximum accuracy while maintaining adequate performance.
Solution: Feature engineering techniques and ensemble methods
Accuracy Guarantee
Maintaining high prediction accuracy even with constantly changing data.
Solution: Automatic retraining system and continuous validation
Technologies Used
Technology stack that enabled project success
Project Impact
40% reduction in data analysis time and 25% increase in prediction accuracy
Main Metrics
- 40% redução no tempo de análise
- 25% aumento na precisão das previsões
- 99.9% uptime em produção
- 500+ usuários ativos mensais
Main Achievements
- Implementação de algoritmos de ML avançados
- Interface intuitiva com dashboard em tempo real
- Integração com múltiplas fontes de dados
- Sistema de alertas inteligentes