Abstract
Big data analysis is different from traditional analysis as it involves a lot of unstructured, non RDBMS types of data. This type of analysis is usually related to text analytics, natural language processing. Areas like video and image analytics are still evolving. Big data analysis attempts to interpret and find insightful patterns in the customer behavior that perhaps the sales force already had some idea about, but did not have the data to support it. Big data analysis methods are used to analyze social media interactions, bank transactions for fraud patterns, customer sentiments for online product purchases, etc. Let’s look at some patterns that may help discover and analyze this unstructured data.
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© 2013 Nitin Sawant
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Sawant, N., Shah, H. (2013). Data Discovery and Analysis Patterns. In: Big Data Application Architecture Q & A. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-6293-0_6
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DOI: https://doi.org/10.1007/978-1-4302-6293-0_6
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4302-6292-3
Online ISBN: 978-1-4302-6293-0
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