# Data Science: Methods, Tools, and Best Practices
Status: public
Confidence: low (0.84) (verified)
Last verified: 2026-05-28
Generation: ai_structured


## TL;DR

Data science fundamentals combine data organization, statistical learning tools, and reproducible analysis. This repair narrows the article to source-mapped methods claims.

## Core Explanation

The previous entry had weak coverage and generic sources. The repaired version uses tidy data, scikit-learn, and NIST big-data material.

## Further Reading

- [Tidy Data](https://doi.org/10.18637/jss.v059.i10)
- [Scikit-learn: Machine Learning in Python](https://www.jmlr.org/papers/v12/pedregosa11a.html)
- [NIST Big Data Interoperability Framework: Volume 1, Definitions](https://doi.org/10.6028/NIST.SP.1500-1r2)