Marriage Data Anomaly

Requirements Clarification & Assessment

1. Understanding the Dataset:

   • Identify the primary source of the dataset (e.g., backend database, external data source).
   • Determine the table structure and any relevant metadata, such as column descriptions and data types.
   • Clarify the intended use of the 'marriage' attribute and its expected values.

2. Data Collection Process:

   • Investigate how data is collected for the 'marriage' attribute. Is it user-reported, derived, or imported from another system?
   • Assess any data entry processes or ETL pipelines that might affect this attribute.

3. Historical Context:

   • Determine if the anomaly is recent or if it has persisted over time.
   • Identify any changes in data collection or processing methods that might have coincided with the onset of the anomaly.

4. Demographic and Contextual Factors:

   • Consider demographic factors such as age, location, and cultural norms that might influence marriage rates.
   • Assess if the dataset is a subset or filtered view that could explain the anomaly.