Data IQ Tool

Data IQ Tool ingests CSV or JSON datasets and computes a composite quality score across completeness, validity, uniqueness, consistency, and range compliance. It reports per-field metrics to pinpoint where data quality issues originate and to guide remediation.

Conceptually the tool treats data quality as a multidimensional attribute. It enforces schema conformance, detects missing values and type mismatches, identifies duplicates, checks value ranges, and flags anomalous patterns. Profiling and optional rule libraries support customization for industry-specific datasets.

Beneficiaries include data engineers preparing pipelines, analysts validating incoming data, and governance teams auditing data health. Unique value lies in transparent scoring rules, chunked processing for large datasets, and exportable reports suitable for data audits and cross-team communication.

Core features include dataset input handling, per-field statistics, a configurable validation rule set, remediation recommendations, and export options for JSON and CSV. Use cases span pre-ETL validation, data quality monitoring, and root-cause analysis of data quality incidents.