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Editor's note: Want to learn all there is to know about the cloud? Don't miss our Cloud QCamp coming up on April 7, 2010.



The assessment of what went wrong in the recent Christmas Day airliner attack over Detroit is clear: we should have done a better job identifying the warning signs of a pending attack by connecting the dots across a series of data sources.

Because of the severity of the potential outcome, this incident takes on a level of scrutiny that is unparalleled. But terrorism is just one example where the ability to "connect the dots across data sources" and share the results can have tremendous benefits.

Criminal activity is climbing as individuals attempt to conceal their identity in the darkest reaches of the Internet. Countless situations such as fraud, money laundering, cyber attacks, data breaches, illegal gambling, and child pornography exist where the ability to obtain relevant, timely analytical results could prevent serious harm from happening to people and organizations.

The need to connect the dots is not limited to law enforcement and counter terrorism. Data analysis plays an important role in virtually every industry. Businesses, for example, need to better understand financial performance. Manufacturers need to be aware of the dependencies between orders, inventory, shipments, and delivery timetables. Pharmaceutical companies need to understand the results of new, vitally important drug trials and the resulting interactions on patients. Energy companies need to explore sources of energy, to name a few.

Unfortunately, traditional business intelligence (BI) and data mining applications provide only a modicum of analysis. Imagine what the result would be if the analyst could visualize disparate data in rich pictures and draw linkages between people, places, and events? How much better could the result be if the same analyst could quickly connect to new data sources and uncover meaningful insight in minutes? How beneficial would it be if results could be shared in real time with someone halfway around the world?

Traditional BI solutions do not allow for this level of exploration. Rigid in nature, they can be hard to install and difficult to learn. Most existing BI tools rely on underlying data models used in the analysis. If the data needed for the analysis is not present, long cycle times and missed opportunities follow.

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