2.2.12 Big data analytics (cont.)
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Enormous amounts of data are being generated every day. And most companies are collecting, storing, and analysing that data.
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Their goal? Transform data into strategic information and discoveries. Two out of three IT managers say big data will be a priority for their company in 2013 and for the next five years. But there are challenges.
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And there are concerns.
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Big data is just the beginning. Data from devices, sensors, and monitors often provide the most value while interacting in real time. Cisco calls this "data in motion." It enables actions and decisions to be made instantly.
For example, think of machine-to-machine communication. And by 2017 more than 1.7 billion machine-to-machine connections are expected. We are just starting to realise the true potential of data.
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Big data applications must be able to gather this data and structure it in a way that can create value for organisations. For example, big data applications must account for changing data sources and trends, such as:
- mobility − mobile devices, events, sharing, and sensor integration
- data access and consumption − internet, interconnected systems, social networking, and access models
- ecosystem capabilities − major changes in the information processing model and the availability of an open source framework
As a result, the cost and complexity of these models has increased, prompting changes in the way big data is stored, analysed, and accessed. Organisations must adjust their current data models to accommodate big data. As a result, organisations are increasingly using virtualisation and cloud computing to support their big data needs.