As long ago as 2015, the analyst firm Gartner ‘retired’ big data from its Hype Cycle – its method of tracking emerging technologies from innovation through to the ‘peak of inflated expectations’, ‘trough of disillusionment’ and the sunnier ‘plateau of productivity’. It reasoned that big data was no longer an emerging technology. Yet, at the same time, it’s said that technologies often take five to ten years to move from the trough to the plateau.
While, I don’t for one minute think that Gartner has dismissed big data as worthless, I do agree with its decision. The term ‘big data’ has become so pervasive that instead of an exciting new concept ready to transform sales and marketing as we know it – it’s turned into a cliché.
Yet, we need to get one thing straight; just because the term itself is overused, it doesn’t make whatever it describes less valuable. However, many companies have started capturing large volumes of data, but don’t know how to realise its value in a practical and affordable way. Data scientists who can help analyse the data are expensive to hire and hard to come by anyway and much data is unusable as it stands – incomplete and lacking integrity and context. More often than not, it’s stored in discrete or siloed sources which are difficult to integrate into a single source of information,
So like householders addicted to clutter, many businesses sit and watch their data gather dust and wonder why it’s meant to be such a good thing.
But, of course the technology world is moving at such a phenomenal pace that further new concepts are taking centre stage – technologies that can inject data with fresh insight so that instead of forcing us to make decisions based on past behaviour, it can project the way we will act in the future.
Perhaps from now on, we should stop talking about ‘big data’ and start thinking about ‘living data’ instead?
Living data is fluid and is constantly being revised and updated. It’s the reason that the large IT houses such as Salesforce and IBM have heavily invested in artificial intelligence (AI) and tools such as Einstein and Watson; technology that uses significant quantities of data to constantly learn and drive a business’s predictive capacity. So instead of looking at past patterns, it’s looking at predictive ‘living’ trends.
Of course, the idea of AI – or the idea of computers thinking like humans – in itself isn’t new. But previously it was considered to be science fiction and something that could work against humanity rather than a business tool that could be used to move our insight and understanding forward.
Previously there just wasn’t the huge volumes of data available for computers to learn from. Now, with the internet and social media and as time goes on, the Internet of Things we have access to virtually unlimited amounts. This has brought the ideas of Machine Learning and Deep Learning to prominence – enabling computers to learn and refine their output accordingly the more data they use. Further methods such as Natural Language Processing and Predictive Analytics – are also maturing on back of these AI advances.
Data scientists have been called the ‘new rock stars’ because they are so elusive but also badly in demand. Up until recently this meant it was difficult for businesses to analyse their data. Today, emerging new AI tools make it possible to bypass their expertise in all but the most complex of cases.
The other innovation that has made the use of AI for business feasible is cloud computing. Previously the processing power required to crunch the data required would have put it out of reach of all but the largest and wealthiest of businesses. Business data was usually held within a mismatch of internal and external sources – often in systems that didn’t talk to one another. Cloud-based CRM solutions connect all this data to create a single view of each individual customer. This central hub of integrated data is essential to an AI or living data approach.
Today, businesses of all sizes can take advantage of living data when AI is baked into an enterprise system they already use. This doesn’t necessarily mean a “one size fits all” approach – these systems are invariably customised for each individual business anyhow. But intelligence will be embedded within the context of the business, automatically discovering relevant insights, predicting future behaviour and proactively recommending next best actions. It will learn, self-tune and become smarter with every interaction and additional piece of data.
This is already the approach Salesforce is taking with its AI technology, Einstein. This is designed to bring the benefits of AI to the sales and CRM worlds, embracing for example, the huge challenge of social media data analysis, monitoring and assessing to recognise trends, sentiment and relevant events
When AI is integrated into the fabric of the business in this way it becomes a powerful and valuable tool, making businesses smarter and more forward-looking. It will be up to a good systems integrator or vendor partner to help businesses explore the possibilities and customise the solution accordingly.
Computers have not always been able to think like humans – but they are good at doing things that we find difficult – for example, remembering every detail. AI brings these details to life and apply them to real world situations. . In other words, turning big data to living data.
[su_box title=”About Sean Harrison-Smith” style=”noise” box_color=”#336588″][short_info id=’102776′ desc=”true” all=”false”][/su_box]
About the Author
The opinions expressed in this post belongs to the individual contributors and do not necessarily reflect the views of Information Security Buzz.
