Challenge: Real-time Anomaly Detection

Justification

Real-time anomaly detection is essential for identifying unexpected patterns and critical events in streaming data. This has applications across diverse fields, including cybersecurity, finance, manufacturing, and healthcare. It helps detect threats, equipment malfunctions, fraudulent activities, and medical conditions, enabling timely responses and mitigating potential damage.

Objective

Using Apache Beam’s capabilities, build a data pipeline that enables real-time anomaly detection.

Things to consider

• Process streaming data
• Integrate anomaly detection models into Beam pipelines

Expected result

In the simplest scenario, a data pipeline implemented in Google Colab that analyzes a data stream and detects anomalies.