Hi Wade, thanks for your comments and readership. Trust in using data is layered. For those who have been developing their own reports, they trust their own production and as long as the self serve mirrors that, they have no problems. Challenge is that often, the self serve reveals errors in the prev production and this shakes the trust foundation. The other issue with trust is when the self serve user does something different like ad hoc analysis. They typically don’t trust the output because they have no baseline. On both instances, it is the job of the data analytics team to run education programmes and to create self serve in such a way that the labels and supporting glossaries provide layman explanations on the data structures and data sources.