Analyze and remediate data quality issues in tabular datasets.
npx skills add https://github.com/dathere/qsv --skill data-quality-dathere
Please help me install this Agent Skill. Skill: data-quality Source: https://github.com/dathere/qsv/tree/main/.claude/skills/skills/data-quality Command: npx skills add https://github.com/dathere/qsv --skill data-quality-dathere
Quality teams need a compact, actionable reference to quickly gauge tabular data quality and guide remediation decisions.
To start, review the quality dimensions and use the remediation tree to identify the first corrective action.
High-intent search queries and answers about installing and using this skill.
Data quality assessment evaluates tabular datasets against six dimensions: completeness, uniqueness, validity, consistency, accuracy, and conformity. It applies a statistics-based framework to profile data and identify specific quality issues in analytics pipelines and warehouses.
Data quality remediation uses a structured decision tree to determine appropriate fixes for identified issues. This guides corrective actions across datasets and pipelines, moving directly from profiling discovery to a recommended remediation step.
Yes, CSV and Parquet datasets can be validated directly within analytics pipelines and data governance workflows. The process requires no external dependencies, applying a statistics-based evaluation framework to check conformity and validity.
A remediation decision tree maps identified quality failures to specific corrective actions for data warehouse governance. It evaluates the statistics-based profile of the dataset to recommend whether to fix, flag, or drop non-conforming records.
A statistics-based data quality framework should be used when profiling large tabular datasets for analytics pipelines where manual checks fail. It efficiently scales completeness, uniqueness, and consistency evaluations across entire data warehouses.
kevinlinProfile tabular or file-based datasets with per-column metrics and quality signals.
timequityOptimize data warehouse queries and storage across Snowflake, BigQuery, and Redshift.
vignesh2027Design enterprise data governance frameworks with cataloging, lineage, and PII policies.
lucas-flatwhiteMonitor URLs for console errors, performance regressions, and page failures after deploy.
