Measuring Impact As A Data Engineer
How data engineers can more accurately trace the impact of your data, your work and your team within your organization.
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The 1 Data Point We Don’t Have
For data engineering, a discipline whose product is precise and tangible, it’s surprisingly difficult to gauge your work’s impact.
It shouldn’t be that surprising that data engineering’s output often flies under the organizational radar, especially since few even know exactly what a data engineer does.
Although a data engineering team’s product is, well, data, we’re essentially mining a raw material; while it is easy to determine its origins, it is difficult to claim ownership of any resulting product.
Like an oil refinery, we take our hours of hard, brain-frying work and simply hand it off to the individual who does something with it — and, by the way, gets the credit.
Data analysts can measure the accuracy or utility of their reports.
Data scientists can measure the precision and ROI of their ML models.
