• Identify data anomalies

• Collect anomaly-related data

• Discover relationships and trends that explain anomalies.

• Identify data anomalies

• Predict when anomalies are likely to recur

• Use analytical tools such as decision trees and regression.

• Apply serf-learning loops to draw inferences from anomalies.

• Predict when anomalies are likely to recur

• Use analytical tools such as decision trees and regression.

• Identify data anomalies

• Use machine learning to find patterns in large datasets.

• Discover relationships and trends that explain anomalies.