# Data and engineering quality — Learning path | Yishto

Canonical page: https://yishto.com/en/learn/data-practice/

Author: [Yishto](https://yishto.com/en/about/)

Use metrics, experiments, tests, and documented decisions as evidence.

Support engineering decisions with checkable evidence.

## Data and engineering quality

- [Connect metrics, charts, and experiments to a question](https://yishto.com/en/learn/data-practice/metrics-analysis-and-experiments/index.md): Use synthetic directory data to examine denominators, missing values, latency distributions, and experiment assignment, separating descriptive differences from evidence for a product decision.
- [Define the purpose and boundaries of event data](https://yishto.com/en/learn/data-practice/data-events-and-governance/index.md): Define purposes, minimal fields, versions, and lateness rules for course-completion events, then trace how duplicates, missing records, and deletion affect derived metrics.
- [Support code evolution with tests and decision records](https://yishto.com/en/learn/data-practice/testing-refactoring-and-decisions/index.md): Use an integer discount rule to define behavior, rounding boundaries, and test layers, then preserve the rationale for small refactors through decision records.