'Certify Your Data Assets to Avoid Treating Your Data Engineers Like Catalogs' dataengineering datascience
: “Average query run time is a good place to start, but you may need to create a more nuanced metric .This process also enables you to configure granular alerting rules tailored to what matters most to the business.Setting SLAs for your data pipeline is a major step toward increasing your data reliability and is essential to a data certification program. SLAs need to be specific, measurable, and achievable.
To achieve this level of specificity and organization, teams should align early – and often – with stakeholders to understand what good data looks like. However you decide to approach it, I’d recommend against boiling the ocean. Most of my customers are implementing their data certification programs as “go forward” first and cleaning up older assets in a second wave.
While this may seem like table stakes, clear and transparent communication is essential to creating a culture of accountability. Nothing is broken and in need of fixing, but it’s still helpful for the team to know. After all, “expected” behavior to one person might still be newsworthy and critical to another member of the team – or even another domain.
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