There are a lot of different words for data quality improvement activities like data cleaning, data cleansing, data scrubbing and data hygiene.
Today I stumbled upon “data laundering” and the site http://www.datalaundering.com that is owned by an old colleague of mine from way back when we were doing stuff not focused on data quality.
Joseph is specializing in laundering data from surveys. The issue is that surveys always have some unreliable responses that lead to wrong conclusions that again lead to wrong decisions. This is a trail well known in data and information quality.
Unreliable responses resemble outliers in business intelligence. These are responses from respondents that provide answers distant from the most conceivable result. What I like about the presentation of the business value is that the example is about food: What we say that we eat and what we actually consume. Then there is a lot of math and even induction mechanism to support the proposition. Read all about it here.
Liliendahl on Data Quality 