Big Data Big Reward

Topics: Crime, Law enforcement agency, Business intelligence Pages: 3 (684 words) Published: September 15, 2013
Big data, Big rewards
1.Describe the kinds of big data collected by the organizations described in this case.

There are mainly three kinds of big data collected by the organizations described in this case. First, IBM Bigsheets help the British Library to handle with huge quantities of data and extract the useful knowledge. Second, State and federal law enforcement agencies are analyzing big data to discover hidden patterns in criminal activity. The Real Time Crime Center data warehouse contains millions of data points on city crime and criminals. Third, Vestas implemented a solution consisting of IBM InfoSphere BigInsights software running on a high-performance IBM System x iDataPlex server.

2. List and describe the business intelligence technologies described in this case.

IBM Bigsheets is an insight engine that helps extract, annotate, and visually analyze vast amounts of unstructured Web data, delivering the results via a Web browser. State and federal law enforcement agencies are analyzing big data to discover hidden patterns in criminal activity such as correlations between time, opportunity, and organizations, or non-obvious relationships between individuals and criminal organizations that would be difficult to uncover in smaller data sets. The Real Time Crime Center data warehouse contains millions of data points on city crime and criminals. Vestas relies on location-based data to determine the best spots to install their turbines. It implemented a solution consisting of IBM InfoSphere BigInsights software running on a high-performance IBM System x iDataPlex server.

3. Why did the companies described in this case need to maintain and analyze? What business benefits did they obtain?

There are mainly three reasons. First, Traditional data management methods proved inadequate to archive millions of these Web pages, and legacy analytics tools couldn’t extract useful knowledge from such quantities of data. Second, It would be difficult to...
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