I work at a place where data quality is not on anyone’s radar. We have a reporting team in our group so we do our best where we can, but combining any datasets with other groups (like marketing & sales) is next to impossible as each team is silo’d and do things their own way - think free-form text fields to tag content…
How can I politely and succinctly say the above? Also, anyone else in a similar boat?
We need shared definitions to tell meaningful stories with our data. And then use a company specific example like how a customer’s journey can not be understood with differing definition between marketing and sales. The marketing team can’t measure the quality of the leads they’re producing unless they can directly link a customer’s whole journey from acquisition to churn. Otherwise it’s just vanity metrics. But don’t be too harsh, vanity metrics are really common in business. A company needs strong data leadership to create a culture of using data to justify decisions to a culture of using data to inform decisions.
Definitely try to use examples to help them get a glimpse into the issue. I like to explain documentation errors by pointing out when what are supposed to be sequentially recorded timestamps are recorded out of order in my work’s database. Sometimes the data quality isn’t there.