The value of data quality

The other day I stumbled into an interesting blog post about software quality, and this brilliant quote (by Alan Weiss) kept flashing on my internal billboard over and over again...

Quality [...] is not the absence of something in management's eyes, that is, defects, but the presence of something in the consumer's eyes, that is, value.
What struck me was an explanation for one of the findings that I quite often get when people tell me that they are using DataCleaner or competing tools, and they find value in even some of the simplest functionalities in there - That even the simplest of features can provide a fortune of value. Coming from the world of tools and product development we tend to look at feature comparisons and technical capabilities a lot. And even customers also use such arguments for choosing a tool. And of course it makes a lot of sense because quality, as in the amount of value provided for the consumer, is very hard to measure and compare.

So how can a software product deliver high quality, in the sense of consumer value? I believe it is a mix of making the product fairly easy to use as well as solving concrete problems for the consumer. In DataCleaner we've done a lot of work to make the tool work as a generic Data Quality Analysis (DQA) tool for a wide variety of data types. But maybe we should also consider building more domain targeted packages where you can easily do a "data value assesment" (to twist the words of Alan Weiss a little) for particular domains, eg. customer data, product data, geographic data and more.

What do you think? Should data profiling and DQA stay generic, or should it target specific domains? Can it do both?

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