This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.
Never before has there been so much information available to businesses and individuals. In January 2015, Google estimated that there were 300 exabytes (that's 300 followed by 18 zeros) of human-made information in the world. In 2011, there were just 30 exabytes. In just 48 months, the amount of human-made information increased by 1000% and we are now at a point whereby more information has been created in the past few years than in all of human history before.
The growing maturity around the Internet of Things, the massively increasing number of connected devices, the explosion of video, social media, user generated content have all resulted in exponential growth in the amount of data at our fingertips. In July 2015, YouTube reported that is was uploading 400 hours of video content every minute. So for every hour of YouTube videos you watch, you're already 23,999 hours behind - that's nearly three years!
From a business perspective, there are two types of data that need to be analysed, understood and trawled through; structured and unstructured. Analysing the structured data is a well-established business requirement - vast amounts of data stored in well-organised databases can be interpreted and presented with relative ease. The challenge lies with analysing all the unstructured data residing in an organisation - from emails to voicemails, social media, video, contracts, letters. This unstructured information doesn't clearly display any underlying patterns or trends. We also have to consider context. A contract, for example, is the final output. A negotiated, distilled and agreed-upon entity. But it is really just a snap-shot, a point in time. What about all the information that surrounds the contract, the email discussions the multiple revisions. What was actually meant by the parties negotiating the deal?
Historically, the only way to gain insight into a big stack of reports - or see patterns in customer complaint letters or supplier payment issues - was for a person to read through them manually and hope their knowledge, diligence or intuition picked up on common themes. However, in a digital world, relying on people alone isn't going to cut it. It could be argued that there is so much data, so much potential information that organisations are starting to suffer information-overload. Where do you start when you know you can never catch-up? Organisations need to change the rules and move from a traditional "human-speed" approach to embracing "machine-speed" only then will they become masters of this information.
Advances in analytics, semantic understanding and machine-learning has given organisations more power to interrogate this unstructured content in ways previously unavailable, transforming "I think" into "I know". And increasingly, predictive analytics will start to play a part, transforming "I know what happened" to "I know what will happen."
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