Until now, the supply, management and interpretation of data has run rather like the Matrix – it’s happening all the time in the background, but hardly anybody outside of analysts and scientists knows it’s there or how it works.
It has taken the recent advances in cognitive computing to give us a glimpse under the bonnet and an idea of how the data engine works. Cognitive’s ability to process millions of data points and turn them into practical, useful information has revolutionised data processing and made it accessible to anyone with a question to ask.
On one side of the coin, this means industry-specific cognitive apps for health, fitness, retail and so on such as those powered by Watson, which understand natural language and allow the user to ask questions and rate answers, enabling the app to become smarter with each use. Watson is available through the cloud and hundreds of partners are already building apps with it – this aspect of cognitive is available to anyone who wants to put it to the test.
The flipside is, in Watson’s case especially, its ability to take any and all kinds of structured data – huge databases, information spreadsheets, years’ worth of information about individuals and their behaviour – and find relationships between them which might not occur to even the most skilled data scientist. And it’s all done in real time, such is its processing power – individuals from any business area can ask questions relevant to their discipline and get an informed answer based on statistically-significant information.
Predicting the future
The expanse of information available also allows for predictions of future behaviour. In health, for example, medical professionals can assess how healthy eating initiatives have impacted the use of primary healthcare services, ascertain with a good degree of accuracy the outcome of similar projects and make a judgement on whether they are a worthwhile investment. And in retail, businesses have the ability to pinpoint the time, place and mechanism of their most profitable promotions, enabling them to target future initiatives very precisely.
What makes the most fundamental difference is that, in the past, databases and their subsequent methods of analysis were almost universally built by people who would not be making practical use of the data. Though they may be experts in the art of complex information architecture, more often than not they would be unaware of the real-life, ‘human’ questions which would make that information relevant and useful.
Services such as Watson Analytics allow end users to get their hands on the information they need in a way they can understand without having to gen up on the science behind it. Any person from any part of any business can ask a question such as ‘What would happen if the marketing team send out more promotional emails to customers?’ and receive an answer based on real customer behaviour and sentiment. It’s an invaluable tool which can only improve the quality and accuracy of industry activity across the board – not to mention reductions in cost and increased return on investment.
The democratisation of data analysis is one more step towards cognitive computing realising its full potential as an aid to human existence – expect new developments to come hot on its heels, as individuals become more familiar and comfortable with its capabilities.
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