data-quality-validator

Post-load data quality validation inspects loaded Qlik datasets to identify null rates, referential integrity gaps, duplicates, and row count mismatches. It generates a standardized Data Quality Validation Report using reusable Qlik resident queries and MCP-SQL templates.

Referential integrity validation checks relationships between loaded Qlik datasets to identify orphaned records and key mismatches. The validator generates queries and includes findings in a standardized Data Quality Validation Report.

Yes, null rate and sparse field analysis can be performed using provided Qlik resident queries and MCP-SQL templates. These templates support embedding checks directly in load scripts to document field type consistency and value distribution.

Yes, the validator provides reusable MCP-SQL templates to validate data and document findings. These templates support post-load inspection across null rates, duplicates, row count validation, and field type consistency.

The best way to validate row counts and duplicates is running post-load inspection using standardized Qlik resident queries. This produces a Data Quality Validation Report surfacing row count mismatches and duplicate records.