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We live in a world that is more globalised than ever before. Making connections is now easy. Technology is to thank for this as we use it to support everyday activities from sending emails, calling friends, shopping at the supermarket, travelling on the tube and even buying coffee. Every one of these actions, and in fact everything we do, is generating data.

Many companies have begun to realise that they already have a lot of data at their disposal, if only they knew how to utilise it. This dataset is only going to increase with research reporting that 90% of data in the world was created in the last three years. The growth of social media has contributed to this with businesses now having to monitor and react in real time to what is being said on channels including Twitter, LinkedIn, Facebook, Instagram and Google+. Companies can become true social businesses, by driving growth and superior profitability through a better understanding of the customer through social. They can capture, analyse and utilise these new forms of communication and data to drive real and measureable strategic value.

Every industry from automotive to financial services and retail are sitting on masses of datasets relating to everything from machine data to customer behaviour. Data has significant potential as it provides an insight into human behaviour. Organisations are investing in business processes which depend on the accurate understanding of this data. They recognise that what was once regarded as ‘information overload’ can now provide valuable insights. When extracted correctly, data can help predict behaviours, classify profiles, decrease risk, identify opportunity, prevent fraud and can be used to discover meaningful patterns and trends. In fact, predictive analysis can help companies with customer service, compliance, financial management and making better informed business decisions.

Now that we understand that big data has value in it, how do you go about finding it? Using big data intelligently involves more than just creating a huge database of internal and external business information. It requires adopting a new paradigm for production and service delivery, using methods of computational intelligence, machine learning and evolutionary programming within artificial intelligence.

The global adoption of smart phones, tablets, wearables and the hype around the internet of things means that datasets that were once merely observed can now be combined with volunteered data (as we see on social media) and cross referenced against intelligent statistics. These datasets are then analysed further using artificial intelligence methodologies.

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