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The Search for Intelligent (Business) Life on Earth

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Since the 1890s, man has been using technology to try and find signs of intelligent life in the universe. Nicola Tesla, the brilliant inventor and engineer, was said to be one of the first when he suggested that an extreme version of his wireless electrical transmission system could be used to contact Martians.

Some years later, when Tesla was investigating atmospheric electricity, he observed repetitive signals that he thought came from Mars. It turned out that he had just misunderstood the technology he was using. Tesla was followed by Guglielmo Marconi, Lord Kelvin and David Peck Todd who all believed they could use radio technology to contact Martians. No one to date has managed to contact any extraterrestrials (that we know of), sadly. However, their devotion to using new types of technology to prove a fascinating theory is reflected in many 21st-century technology innovators.

Today's search for intelligent life orbits a little closer to planet Earth, with companies delving into universes of data rather than looking to the stars. Their goal is to make their business operations more intelligent by integrating analytics, social and mobile technologies into their processes and the applications that enable them. This is called intelligent business operations (IBO).

Firms are working to integrate proprietary and historical data with exponentially expanding masses of valuable new and real-time data, known as big data, in order to improve the way in which they respond to outside challenges.

This new data follows years of technology innovation, which has created billions of online devices, which in turn create data. Mountains of new information flows in from social media, new internal corporate processes, retail and market transactions, electronic sensors and other devices every day. In terms of the rate of change and throughput of the data - it's not just big data - it's fast data too.

By 2020, Gartner predicts there will be up to 30 billion devices -- or things -- connected to the Internet with unique IP addresses. This compares with 2009, when there were a "mere" 2.5 billion connected devices.

This digital revolution, the Internet of Things, is a virtual world where things can be anything from a person with a heart monitor to a digital tire pressure sensor in your car, or smart electricity grids communicating with each other. All of these things create data, and the data can tell a story. The story might be about the personal spending habits of an iPhone user, or it could be about the engine capabilities of an 18-wheel truck.

If you can get the story right, there is a pot of gold at the end. Gartner predicts that the total economic value-add from the Internet of Things will be $1.9 trillion dollars in 2020. The trick is to winkle out the story, thus identifying a trend or a pattern or an anomaly that you can use intelligently.

Enter IBO. IBO puts real-time analytic intelligence and decision-making into the very lifeblood processes of the business. The result of this is being intelligent business-adapting decisions, based on the big, fast data blood flowing through the business' veins.

This might be pushing real-time offers to mobile consumers based on their locations, optimizing logistics operations to re-route shipping to reduce carbon footprints, or detecting and preventing fraud while (not after) it is in process.

An IBO platform converges a number of powerful technologies into a modern in-memory analytics and "decisioning" architecture -- including real-time messaging, in-memory data grid, complex event processing and streaming analytics, business process analytics and visual analytics.

Together these capabilities can give a business 180 degrees of visibility -- and the ability to respond at lightning speed. Using IBO, the next generation of big, "fast" data at Internet-of-Things scale can be collected, analyzed and responded to intelligently.

As businesses look to the discover intelligent life in big data, IBO is the new technology that will enable this. Tesla would be envious.

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