What are 2 reasons why data may be anomalous?

Data may be anomalous due to errors in data collection, such as incorrect measurements or data entry mistakes, which can lead to outliers that do not reflect the true underlying patterns. Additionally, genuine changes in the environment or underlying processes, such as sudden shifts in consumer behavior or system failures, can result in data points that diverge significantly from established trends.