Data Outliers: 10 Ways To Prevent Big Data Damage - InformationWeek

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Data Management // Big Data Analytics
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4/18/2016
07:06 AM
Lisa Morgan
Lisa Morgan
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Data Outliers: 10 Ways To Prevent Big Data Damage

Most business decision-makers aren't trained to understand data outliers, but they can learn the basics. Executives, managers, and employees without math degrees can ask smarter questions about analyses they're basing crucial judgments on. Here are some things to know.
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There's A Data Quality Problem 

People and machines may be responsible for poor quality data that makes its way into an analysis. Someone may have typed a wrong number or transposed digits in a number. Alternatively, a piece of equipment may report an erroneous value that skews the analysis. It is also possible for data to be corrupted while it is transported across a network. 
'The importance of removing or fixing an outlier depends on how extreme it is. If it was caused by a minor mistake, it may not matter very much. But if the outlier is extreme, it may negatively impact your analysis and lead to the wrong conclusion,' said Spencer Greenberg. 'If your outlier is caused by a mistake, you want to remove the value or fix it. And the more extreme it is, the more important it is to do that.'     
(Image: stevepb via Pixabay)

There's A Data Quality Problem

People and machines may be responsible for poor quality data that makes its way into an analysis. Someone may have typed a wrong number or transposed digits in a number. Alternatively, a piece of equipment may report an erroneous value that skews the analysis. It is also possible for data to be corrupted while it is transported across a network.

"The importance of removing or fixing an outlier depends on how extreme it is. If it was caused by a minor mistake, it may not matter very much. But if the outlier is extreme, it may negatively impact your analysis and lead to the wrong conclusion," said Spencer Greenberg. "If your outlier is caused by a mistake, you want to remove the value or fix it. And the more extreme it is, the more important it is to do that."

(Image: stevepb via Pixabay)

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