The most important part of AI is often the data pipeline. Data infrastructure quality is the strongest predictor of AI project success.
Feature Stores
Feature stores prevent training-serving skew, enable feature reuse, and provide lineage for governance.
Real-Time vs Batch
Choose architecture based on business latency requirements — fraud, personalization, and dynamic pricing often need real-time features.
Data Quality
Implement quality checks at every pipeline stage with alerting and circuit breakers that keep bad data out of production models.