This project aims to detect anomalies in search query data, which can help identify unusual patterns that might indicate issues like click fraud, data errors, or unexpected user behavior. By analyzing various metrics, the project provides insights that can be used to improve search optimization strategies.
- Data Quality Checks: Performs initial data checks, including handling null values and converting key metrics, such as click-through rate (CTR), into appropriate formats for analysis.
- Query Analysis: Analyzes the common words in search queries and evaluates their performance metrics like clicks and impressions.
- Anomaly Detection: Identifies irregularities in search query data, focusing on metrics such as clicks, impressions, and CTR to spot anomalies.