Data Verification Tool

One data verification tool provides automated, rule-based validation to confirm data integrity across ingestion and analytics pipelines. It targets data engineers, analysts, and governance teams who need repeatable checks without bespoke scripting. The tool accepts multiple data sources (CSV, JSON, Parquet, databases) and applies a consistent set of validations to detect structural or content anomalies early in the workflow.
Core logic includes a rules engine that defines required checks (schema conformance, type and range validation, mandatory fields, referential integrity) and optional checks (duplicate detection, cross-field dependencies, checksum comparisons). Outputs include per-record status, summary metrics, and exportable reports. Optional advanced features support sampling, parallel processing, and incremental validation for large datasets.
Algorithms employ JSON Schema for structural validation, cryptographic hashes (MD5, SHA-256) for integrity, and deterministic deduplication by primary keys. It computes validation scores and flags failed records with remediation hints. Edge cases cover missing fields producing UNKNOWN status, invalid encodings triggering normalization attempts, and partial data handled via streaming or batched processing to maintain throughput.
Industry considerations include international formats, locale-aware parsing, and regulatory traceability needs. Assumptions: inputs declare correct schemas; external lookups may be cached. Exclusions: data cleaning or remediation actions beyond providing remediation hints, and UI layer responsibilities are out of scope.