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DESCRIPTION:Click for Latest Location Information: http://unstructured2012.dataversity.net/sessionPop.cfm?confid=69&proposalid=4681\nFor decades, credit card transactions have generated mountains of data about consumer spending habits, but the data formats were designed for archiving and reporting rather than for data mining and pattern discovery.  For example, the merchant's name is embedded in a text field, which also contains other information, without any standard format.\nBundle.com is a new startup that is building a business on the extraction of value from this legacy data source. To create powerful insights about consumer spending behavior, the analytics team must first "tame" large data sets of poorly structured, low quality, inconsistent data, using a variety of methods including text analytics, clustering analysis, and linking open data sources with internal proprietary data sets.
DTSTART:20120501T101500
SUMMARY:From Big Legacy Data to Insight:  Lessons Learned Creating New Value from a Billion Low Quality Records Per Year
DTEND:20120501T110459
LOCATION: See Description
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