In this session, we will explore the powerful combination of Apache Flink, Apache NiFi, and Apache Kafka for building real-time data processing pipelines. We will present a case study using the FLaNK-MTA project, which leverages these technologies to process and analyze real-time data from the New York City Metropolitan Transportation Authority (MTA). By integrating Flink, NiFi, and Kafka, FLaNK-MTA demonstrates how to efficiently collect, transform, and analyze high-volume data streams, enabling timely insights and decision-making.

Takeaways:

Understanding the integration of Apache Flink, Apache NiFi, and Apache Kafka for real-time data processing
Insights into building scalable and fault-tolerant data processing pipelines
Best practices for data collection, transformation, and analytics with FLaNK-MTA as a reference
Knowledge of use cases and potential business impact of real-time data processing pipelines