This example demonstrates validation of classroom and student enrollment data across two independent systems with inconsistent schemas and naming conventions.
Scenario: Classroom data exists across two systems:
- System A reflects front-end classroom data
- System B stores enrollment and user data in a separate integration database
These systems cannot be directly joined and use inconsistent naming conventions.
Issue: Classrooms and schools are labeled differently across systems, requiring manual reconciliation to ensure correct student mappings.
Example mismatch:
- System A: "Community School" / "Social Studies"
- System B: "Central New Mexico Elementary" / "Class Resources"
Approach:
- Extract classroom integration IDs from System A
- Use those IDs to query System B
- Apply filters for active, non-deleted records
- Manually reconcile mismatched classroom and school names
Outcome:
- Validated student enrollment data across disconnected systems
- Identified inconsistencies in data mapping between systems
Key Concepts:
- Cross-system data validation
- Handling schema and naming inconsistencies
- Multi-step query workflows across separate databases
This example demonstrates validation of OCR-translated timesheet data in a SQL Server environment.
Scenario: Caregiver timesheets were scanned and processed using OCR, converting handwritten hours into structured database records.
Issue: OCR incorrectly classified worked hours as PTO, resulting in inaccurate PTO deductions.
Approach:
- Query timesheet and user data using T-SQL
- Compare OCR-extracted values against original scanned timesheets
- Identify discrepancies between worked hours and PTO fields
Outcome:
- Detected data integrity issue affecting caregiver PTO balances
- Supported defect identification in OCR processing logic
Key Concepts:
- Data validation against source documents
- Join operations across related tables
- Identifying business-impact defects in production data