> For the complete documentation index, see [llms.txt](https://www.mlcompendium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.mlcompendium.com/data/engineering-intro/data-kpis.md).

# Data KPIs

Data spend needs a return measure, not only pipeline uptime. The page is about that one question, measuring the return on data and analytics.

The KPI for data sits inside the wider OKR and KPI practice of the organization. The same notes are in [Data Science OKR KPI](/ai-product/management.md#data-science-okr-kpi) and [OKRs & KPIs](/ai-product/management.md#okrs--kpis).

[How to measure ROI of data analytics](https://medium.com/be-data-driven/how-to-measure-the-roi-of-data-analytics-2d2ac172754a) is Bruno Aziza's piece on measuring the ROI of data analytics, in an issue that also asks whether thinking is the enemy of innovation and what to do when scaling a data team. A second source on measuring the ROI of data and analytics used to sit here; its address no longer opens and it is kept at the end of the page.

## Deprecated links

{% hint style="warning" %}
These links and images no longer work. The original wording is kept here. A same-resource copy, when one was checked, is used above.
{% endhint %}

* Measuring ROI of data and analytics. This address no longer opens: <https://santiagotacoronte.com/5-ways-to-measure-the-roi-of-data-analytics-the-simple-way-a61790eff7d1>


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