Anomaly detection forms an essential component of real-time analytics, which help enterprises gain significant actionable insights across a wide variety of application domains. However, detecting anomalies accurately can be difficult. As systems evolve, behaviors change, and software gets updated, the system needs to be upgraded continuously to detect an anomaly effectively.
This white paper explores the know-hows of big data anomaly detection in real-time.
- The importance of big data anomaly detection
- How to build an anomaly detection model
- A view of the platform approach to real-time anomaly detection
- How Gathr can help in real-time anomaly detection
The only all-in-one data pipeline platform
- One platform to do it all - ETL, ELT, ingestion, CDC, ML
- Self Service, zero-code, drag and drop interface
- Built-in DataOps, MLOps, and DevOps tools
- Cloud-agnostic and interoperable