Dirty Data Kills Automation Projects Before They Start. Here’s What to Look for Before You Build.

Automation can execute perfectly and still produce poor outcomes when the underlying data is inconsistent. Before development begins, teams should profile historical formats, indexing conventions, missing fields, duplicate records, and exception patterns.

What to consider

Use this topic as a starting point for reviewing your own workflows, risk controls, operating metrics, and automation opportunities. Editors can expand this starter in Gutenberg with customer-approved examples, images, tables, links, and video.