The Importance of Big Data
When big data is distilled and analysed in combination with traditional enterprise data, enterprises can develop a more thorough and insightful understanding of their business, which can lead to enhanced productivity, a stronger competitive position and greater innovation - all of which can have a significant impact on the bottom line.
For example, in the delivery of healthcare services, management of chronic or long-term conditions is expensive. Use of in-home monitoring devices to measure vital signs, and monitor progress is just one way that sensor data can be used to improve patient health and reduce both office visits and hospital admittance.
Manufacturing companies deploy sensors in their products to return a stream of telemetry. Sometimes this is used to deliver services like OnStar, that delivers communications, security and navigation services. Perhaps more importantly, this telemetry also reveals usage patterns, failure rates and other opportunities for product improvement that can reduce development and assembly costs.
The proliferation of smartphones and other GPS devices offers advertisers an opportunity to target consumers when they are in close proximity to a store, a coffee shop or a restaurant. This opens up new revenue for service providers and offers many businesses a chance to target new customers.
Retailers usually know who buys their products. Use of social media and Web log files from their e-commerce sites can help them understand who didn't buy and why they chose not to, information not available to them today. This can enable much more effective micro customer segmentation and targeted marketing campaigns, as well as improve supply chain efficiencies.
Finally, social media sites like Facebook and LinkedIn simply wouldn't exist without big data. Their business model requires a personalised experience on the Web, which can only be delivered by capturing and using all the available data about a user or member.
How Enterprises can use Analytics to make sense of Big Data
To make the most of big data, enterprises must evolve their IT infrastructures to handle the rapid rate of delivery of extreme volumes of data, with varying data types, which can then be integrated with an organisation's other enterprise data to be analysed.
This infrastructure, required for analysing big data, must be able to support deeper analytics such as statistical analysis and data mining, on a wider variety of data types stored in diverse systems; scale to extreme data volumes; deliver faster response times driven by changes in behaviour; and automate decisions based on analytical models. Most importantly, the infrastructure must be able to integrate analysis on the combination of big data and traditional enterprise data. New insight comes not just from analysing new data, but from analysing it within the context of the old to provide new perspectives on old problems.
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