PAN Number Validation using SQL

Analysis of a PAN dataset to surface common data quality issues and validate records against defined format rules. Covers null handling, duplicate detection, whitespace and casing inconsistencies, followed by rule-based classification and summary generation.

Files to Refer

• pan_validation.sql Main script covering:

  • data quality checks (nulls, duplicates, spacing, casing)
  • regex-based format validation
  • custom functions for sequence and repetition checks
  • classification into Valid / Invalid PAN
  • summary query (processed, valid, invalid, incomplete)

• PAN Validation Analysis.pdf Contains the full context of the Dataset, project motivation, and full set of validation rules.

• PAN Number Validation Dataset.xlsx Source dataset.

Running the Script

Environment: PostgreSQL

1. Create / connect to a database
2. Load data into pan_numbers_dataset
3. Run pan_validation.sql

Outputs:

• vw_valid_invalid_pan → PAN classification
• Final query → summary counts

Notes

• Validation rules are defined in PAN Validation Analysis.pdf
• Script is commented where required; follow it top-down
• Results are derived directly; no separate cleaned table maintained