Every data project has the same hidden cost. Before a pipeline gets built, someone spends two days emailing a client admin about access. Before a dashboard goes live, someone spends hours figuring out what a confusing report measure actually means. None of this is hard work. It just takes time, and nobody has automated it, because it depends on the account and the situation.

In today's fast-paced business world, data is only valuable if it leads to actionable insights. Yet, many organizations still view their Data and Analytics (D&A) implementation as a process culminating in a static, scheduled report.

Introduction

One challenge every enterprise faces in its data and AI journey (and we did too) is: what do you do with audit data that never stops growing?