How clarrent/customer-dqa-sq works
This repository documents a manual customer-data quality workflow: import the raw CSV into MySQL, profile and audit the table, apply verified fixes, and track issues in a spreadsheet. The README supports these relationships, but no source excerpts are available to establish finer-grained query execution or automated links between artifacts; the audit, fixes, and issue log should be treated as separate hand-operated steps.
Main entry points: 01_dqa_audit.sql Audit queries · 02_cleaning_fixes.sql Verified fixes · dirty_customers_fixes.xlsx Issue log · dirty_customers.csv Raw customer data
Components 9
Data input
- MySQL Workbench
- Raw customer data
dirty_customers.csv - dirty_customers table
Data assessment
- Audit queries
01_dqa_audit.sql - Audit findings
Fixes and handoff
- Verified fixes
02_cleaning_fixes.sql - Issue log
dirty_customers_fixes.xlsx - Microsoft Excel
Other components
- Analyst
Connections 10
- Analyst → MySQL Workbench: imports and runs
- Raw customer data → dirty_customers table: imported as
- MySQL Workbench → dirty_customers table: loads data
- Analyst → Audit queries: runs checks
- Audit queries → dirty_customers table: profiles and reads
- Audit queries → Audit findings: produces findings
- Analyst → Verified fixes: runs fixes
- Verified fixes → dirty_customers table: verifies and updates
- Analyst → Issue log: documents issues
- Microsoft Excel → Issue log: opens and tracks