Skip to main content

Anomaly Detection

Steps

  1. Overview
  2. Pre-requisites
  3. Key Choices and Guidelines
  4. Implementation

1 Overview​

Description​

Anomaly detection is the process of identifying data points, events, or patterns that deviate significantly from the expected or normal behavior within a dataset. In the SAP ecosystem, this involves leveraging tools within SAP HANA ML (PAL, hana-ml) to find data points that "do not follow the collective common pattern of the majority of data points". This practice covers implementing these techniques effectively.

Expected Outcome​

To successfully identify and flag unusual behavior or outliers in various types of data (e.g., transactional data, sensor readings, time series, API traffic) residing within or connected to the SAP landscape. This enables proactive responses to potential risks or opportunities.