“As a single stone causes concentric ripples in a pond,” Martin Doyle commented on my blog post There is No Such Thing as a Root Cause, “there will always be one root cause event creating the data quality wave. There may be interference after the root cause event which may look like a root cause, creating eddies of side effects and confusion, but I believe there will always be one root cause. Work backwards from the data quality side effects to the root cause and the data quality ripples will be eliminated.”
Martin Doyle and I continued our congenial blog comment banter on my podcast episode The Johari Window of Data Quality, but in this blog post I wanted to focus on the stone-throwing metaphor for root cause analysis.
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