Can it process different file formats?

Yes, the skill is designed to handle common data formats including CSV, Excel, JSON, Parquet, and results from database queries through automated Python-based profiling.

Is the final report ready for professional use?

Absolutely. The skill generates a structured Markdown report that can be used as a standalone document or populated into formal quality declaration templates.

What if I don't have full context for the dataset?

If context is missing, the skill will perform a technical profile of the data itself and clearly mark dimensions requiring external context as 'Unable to assess' with specific information requests.

What metrics are included in the column-level scorecard?

The scorecard quantifies Completeness, Validity, Consistency, Uniqueness, Timeliness, and Accuracy for every column, providing a color-coded quality assessment.

What framework does this skill use for analysis?

It utilizes the Australian Bureau of Statistics (ABS) Data Quality Framework, which evaluates data across seven dimensions: Institutional Environment, Relevance, Timeliness, Accuracy, Coherence, Interpretability, and Accessibility.

Data Quality Analysis

Name: Data Quality Analysis
Author: SAS-Asset-Management

bySAS-Asset-Management

0•

데이터 과학 및 ML

Evaluates datasets using the ABS Data Quality Framework to produce comprehensive quality reports and automated column-level scorecards.

This skill provides a rigorous, standardized approach to data auditing by applying the Australian Bureau of Statistics (ABS) Data Quality Framework across seven key dimensions. It automates technical profiling—including completeness, validity, consistency, and accuracy checks—while guiding users through a contextual discovery process to ensure data is fit for its intended purpose. Whether you are preparing data for machine learning or generating formal reports, this skill ensures your datasets are reliable and well-documented.

주요 기능

01Automated column-level quality scorecard with weighted metric scoring

02Standalone Markdown report generation for formal quality declarations

03Interactive discovery interview to capture critical institutional context

040 GitHub stars

05Seven-dimension analysis based on the professional ABS Data Quality Framework

06Technical data profiling including schema inspection and outlier detection

사용 사례

01Reviewing third-party data sources for accuracy and timeliness before high-stakes modeling

02Generating automated data documentation and quality audits for organizational compliance

03Evaluating raw datasets for fitness-for-purpose before ingestion into production pipelines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sas-asset-management/sasamclaudecodeskills data-quality-analysis

For use in Claude.ai and ChatGPT

주요 기능

01Automated column-level quality scorecard with weighted metric scoring

02Standalone Markdown report generation for formal quality declarations

03Interactive discovery interview to capture critical institutional context

040 GitHub stars

05Seven-dimension analysis based on the professional ABS Data Quality Framework

06Technical data profiling including schema inspection and outlier detection

사용 사례

01Reviewing third-party data sources for accuracy and timeliness before high-stakes modeling

02Generating automated data documentation and quality audits for organizational compliance

03Evaluating raw datasets for fitness-for-purpose before ingestion into production pipelines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sas-asset-management/sasamclaudecodeskills data-quality-analysis

For use in Claude.ai and ChatGPT