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Capivon Data

Veri Platformları & ML Altyapısı — Veriden Değer Üretmenin Yolu

Verilerinizi Stratejik Varlığa Dönüştürün

Capivon Data, modern veri mimarileri, ML altyapısı ve analitik çözümlerle verilerinizden maksimum değer çıkarmanızı sağlar. Data lake'lerden feature store'lara, ETL pipeline'larından MLOps'a kadar end-to-end veri platformu.

Production-ready ML sistemleri ve ölçeklenebilir veri mimarileri ile veriye dayalı karar alma süreçlerinizi güçlendiriyoruz.

Veri & ML Platform Çözümleri

Modern Veri Mimarisi

Data lake, data warehouse ve lakehouse mimarileri. Data mesh implementation, medallion architecture (bronze/silver/gold layers). Real-time ve batch processing altyapısı.

Data Pipeline & ETL

Otomatik veri toplama ve dönüştürme pipeline'ları. Stream processing, data quality validation, schema evolution. Orchestration ve scheduling.

ML Platform & MLOps

Feature store, model registry, experiment tracking. Model training infrastructure, automated retraining pipelines. Model serving, A/B testing ve monitoring.

Analytics & BI Platform

Self-service analytics altyapısı, metrics layer oluşturma. Dashboard ve reporting sistemleri. Data catalog ve documentation.

Data Governance & Quality

Data lineage tracking, data quality framework, automated testing. Privacy compliance (GDPR, KVKK), data access controls ve audit logging.

Real-Time Data & Streaming

Event streaming platforms, real-time processing, CDC (Change Data Capture). Stream-batch unification, low-latency analytics.

Kullanım Senaryoları

Recommendation Systems

Real-time feature engineering, model serving infrastructure, A/B testing framework ile personalized recommendations.

Predictive Analytics

Churn prediction, demand forecasting, anomaly detection için automated ML pipelines ve production deployment.

Customer 360

Çoklu veri kaynaklarından unified customer view, behavioral analytics ve segmentation.

Business Intelligence

Self-service analytics, automated reporting, real-time dashboards ile data-driven decision making.

Fraud Detection

Real-time transaction analysis, ML-based anomaly detection, automated alert systems.

Search & Discovery

Semantic search, vector databases, ranking models ile advanced search capabilities.

End-to-End ML Lifecycle

1

Data Collection & Preparation

Veri kaynaklarından toplama, cleaning, validation ve feature engineering. Data versioning ve reproducibility.

2

Model Development & Training

Experiment tracking, hyperparameter tuning, distributed training. Model evaluation ve comparison.

3

Model Deployment & Serving

Production deployment, auto-scaling, low-latency serving. Canary releases ve shadow deployments.

4

Monitoring & Retraining

Model performance monitoring, data drift detection, automated retraining. Feature store updates ve model versioning.

Kimler İçin?

🎯 E-commerce & Retail

Recommendation engines, inventory optimization, customer analytics

🏦 Fintech & Banking

Fraud detection, risk modeling, customer lifetime value prediction

📱 SaaS & Tech

Product analytics, user behavior modeling, churn prediction

🏢 Enterprise

Data warehouse modernization, BI platform upgrade, data governance

Veri Stratejinizi Birlikte Belirleyelim

Data maturity assessment ve roadmap oluşturma için görüşelim

Ücretsiz Assessment