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8 Ways You're Failing At Data Science
Data scientists and the Wizard of Oz have something in common: Few people really know what they do behind the curtain, which makes it hard to tell good from bad data science. These tips can help you discern the difference.
November 26, 2015
About the Author(s)
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.
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