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6-16 Identity three decisions that were improved by using big data.
The British Library is the largest library in the world by number of items cataloged. “Each year more than six million searches are generated by the British Library online catalog, and nearly 400,000 people visit the British Library reading rooms, looking for information.” Back in 2010, the average life expectancy of a website was just 44-75 days meaning that every six months 10 percent of web pages on the UK domain were lost. IBM BigSheets helped the British Library collect these at-risk of termination web pages before they could be lost for good. IBM BigSheets helps extract, annotate and analyze insane amounts of web information using a web browser. The analytic technology helped the British Library archive and preserve massive amounts of web pages before it they were gone forever.
Law enforcement was able to use big data to predict future crime patterns and become more proactive in efforts to fight crime before it occurs. The Durham (North Carolina) police department used IBM analytics to help reduce the amount of violent crime in a two square-mile region of the city by more than 50 percent during a four year span (2007-2011). “Through its work with IBM, the Charleston Police Department joins an elite group that includes New York, Vancouver, Northern Ireland, Memphis and many others that are using advanced analytics to gain a more accurate understanding of their data, detect patterns, preempt and forecast critical information to prevent incidents, and taking action in real time.“
Vestas Wind Systems is a Danish manufacturer of wind turbines. It is also the largest in the world. Precise placement of a wind turbine can affect its performance and usefulness. Vestas uses big data for more accurate turbine placement decisions. “We gather data from 35,000 meteorological stations scattered around the world and from our own turbines…that gives us a picture of the global flow scenario.” This allowed them to establish a “wind library” where they can point to specific location at a specific time of day and tell you what the weather would be like at that location.