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New perspectives can shed light on data quality

Paul Newman Archive

The big data phenomenon is moving forward at full speed, which is great news for companies that want to tap into the petabytes of content being generated on a daily basis. However, the trend won't be as promising for businesses without a grasp on data quality.

What's in your company's data?
In the most recent and glaring example of the possible consequences of poor information, it was discovered that meat being sold as beef actually contained horse. However, there is a new twist that further illustrates the importance of accurate and honest information. Following news about the meat contamination, inspectors in Iceland began testing food products and discovered that an item labeled as a "meat pie" actually contained no meat at all, according to The Associated Press. 

"It was labeled as beef pie, so it should be beef pie," said Icelandic meat inspector Kjartan Hreinsson, upon inspecting the items at Reykjavik supermarket, the source quotes. The pies actually contained a blend of vegetable matter, inspectors reported and further stated that authorities are still investigating the issue. 

Would you consume what you create?
It may seem intuitive that quality is a primary concern for businesses in the food industry, but a recent post for the Integrated Modeling Method blog points out that companies can often lose sight of product purity until the outcome impacts them directly. 

To demonstrate this problem, the source cites Edward De Bono's book 'The Use of Lateral Thinking,' which explained that it was once difficult to keep British manufacturing plants from polluting the rivers on which they were situated. The organizations drew water for internal processes and pumped it back into the rivers once it was contaminated and therefore, unsuitable for human consumption or use by other companies. The manufacturers couldn't be stopped from the practice with fines or penalties, but they immediately cleaned up their operations once they were told they could only use the downstream water, meaning they would be polluting their own processes if it was not first cleaned of all discharge. 

The same idea can be applied to data quality within any enterprise. Products and services are only as good as the quality of the information that's used to create them. If businesses aren't certain about their data's path and whether sets were altered between creation and consumption in a way that can compromise validity, decision makers should think twice about using that content to generate actionable insights. Fortunately, data quality tools can help firms flag issues and identify incorrect information, so they can track down the source of the contamination and make the necessary changes. 

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