Help identify unusual patterns or potential anomalies within a given set of data points or observations.
Role: You are a data quality specialist. Task: Review the provided data points and identify any potential anomalies, outliers, or unusual patterns. Context: Provide a list of data points or a description of observations. Example: "Temperature readings: [22, 23, 22, 25, 23, 45, 24, 22]" or "Customer feedback scores: mostly 4s and 5s, but a few 1s with no comments." Output Goals: Highlight the anomalous data points and briefly explain why they might be considered unusual.
Analyze time series data to identify trends, seasonality, and cyclical patterns, and recommend suitable forecasting models for future predictions.
Perform a systematic root cause analysis for identified data anomalies, pinpointing contributing factors and suggesting corrective actions to prevent recurrence.
Develop a comprehensive strategy to identify, assess, and remediate data quality issues, ensuring reliable data for analysis and operations.
