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Automated data analysis

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What do the data say? Why should we care? The insights of the data are our guiding angels for the decision‐making process. Organizations that are successfully able to embrace and evangelize analytics have been able to differentiate themselves from their competition. Where do the insights come from? Insights are extracted from the data through analytics. Did you know that 1.5 million data savvy managers and analysts will be needed in the next 5 years to drive decisions? With a lot of discussion about big data in the past few years, we know that data volume is increasing, the speed of data collection is faster than ever, data types can be really different, and that data veracity is a concern. Companies are already feeling the growing talent gap of people who can manage and manipulate big data to generate valuable business insights. Automated data analysis is the initial step to relieve the burden from humans. It provides a systematic process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions and supporting decision making for further analysis. In this article, we will use examples to demonstrate how automated data analysis can be done and what values it will bring to the knowledge consumers. We will also discuss why automated data analysis is important to big data analytics. In the summary, we will discuss the possibility of further research directions. WIREs Comput Stat 2014, 6:359–366. doi: 10.1002/wics.1318 This article is categorized under: Software for Computational Statistics > Software/Statistical Software Software for Computational Statistics > Artificial Intelligence and Expert Systems
Automated data analysis.
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Software for Computational Statistics > Software/Statistical Software

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