# Dataops

DataOps and DS/MLOps testing reference for data tiering, Bronze-to-Silver validation...

- Repository: https://github.com/microsoft/hve-core (1591 stars)
- Category: Design
- License: CC-BY-4.0
- Last updated: 2026-11-01
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add microsoft/hve-core --skill dataops -g -a claude-code -y`
Codex: `npx skills add microsoft/hve-core --skill dataops -g -a codex -y`
Cursor: `npx skills add microsoft/hve-core --skill dataops -g -a cursor -y`
Gemini CLI: `npx skills add microsoft/hve-core --skill dataops -g -a gemini-cli -y`

## Description

DataOps and DS/MLOps testing reference for data tiering, Bronze-to-Silver validation placement, pipeline invariants, pytest categories, and validation-versus-drift. Use when designing, reviewing, or generating data pipelines, transformation code, data validation, or data-science test suites.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# DataOps Reference Pack

## Goal

Ground pipeline and test generation in the Microsoft CSE engineering playbook so that data tier semantics, validation placement, recovery invariants, and DS/MLOps test technique are applied consistently and attributed accurately.

## Inputs

* The pipeline, transformation, validation, or test work under discussion
* The tier of each dataset involved, when the consuming workflow records one
* Existing test layout, package structure, and data-access boundaries
* A data classification produced elsewhere, when sensitivity matters

## Reference index

Read only the reference that matches the active concern.

The rest: https://github.com/microsoft/hve-core/blob/HEAD/.github/skills/data-science-engineering/dataops/SKILL.md