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Some weeks back, UK and a big portion of the rest of the world were awed and probably shocked by the result of the referendum to poll public opinion upon whether UK should remain or leave EU. This event is now better known as the ‘Brexit’. But why was the result so surprising? Couldn’t it have been predicted given the knowledge derivable from computing and information technology? Well, most probably it had given the interests that some well-known political leaders have been giving to an area called ‘Big Data’.

It is well known that the president of USA, Barack Obama, is a great supporter of the use of data and predictive analysis. It is widely documented how the Democrat party in the USA has been making use of Big Data to steer the campaign of Barack Obama’s elections in a dynamic way. Thus, the words and tones of his messages were carefully produced after intense data analysis. This mastery of data had even been cited as one of the most prominent reason of his re-election in 2012, arguing that the Republican Party didn’t possess the corresponding skillset back at the time.

Politics and history follow some kind of level two chaotic systems, meaning that the chaos reacts to predictions about it. Hence, pre-Big Data tools and techniques such as data mining or business intelligence (BI) are very good at spotting trends and patterns, but they suffer from some response time and incomplete domain coverage issues. However, we are living in the era of ‘now-casting’; politicians would want to be able to change the contents of their message five minutes before going on stage, health professionals would want to know the evolution of the ‘zika’ virus on an hourly basis and financial advisors would want to predict the stock exchange levels at a very fine grained level.

So, what exactly is Big Data? It evidently refers to the gigantic amounts of data, measured in yotabytes. However, it’s not just a question of quantity of data but it’s also about the variety of the data; thus, to be able to know if a new product would be successful amongst potential customers, an organisation would not only use its own data but would try to reference it with data coming from social networking sites such as Facebook and at the same time also reference it with geolocation data coming from mobile phones of customers. Hence, it would be an amalgamation of clearly structured data such as customer names and loosely structured data such as comments from tweets and coordinate values.

The next major defining factor of Big Data is velocity; as is being discussed in the last paragraph, the production of data could be continuous so that it should be possible to perform analytics not on some finite amount of data but the results should be ever changing based upon new data being used.

However, not all organisations possess the capacity of the 3v’s (volume, variety, veracity), in terms of their datasets operation. At this point, it is mostly global players which have been trying to master techniques involved with Big Data. Unsurprisingly, tech companies such as Google and Facebook have been pioneers, but now most global players in lots of other industries are also adopting this technology.

Definitely, governments also possess the will and power to work with Big Data. As an example, the Barack Obama government had launched the Big Data Research and Development initiative back in 2012. This resulted in lots of research groups getting funding for Big Data research and caused data scientist to become one of the highest paid job in the IT industry in 2015.

So, should non-global organisations care about Big Data even if they don’t currently have the operational capacity and neither the current need to use such kind of data? The answer is definitely yes!

Firstly, there has been the emergence of ‘open’ datasets, so that even if your organisation is not currently producing this huge amount of data, you can still access data being produced by others but which can enhance your decision making capacity.

Secondly, the production of data is already increasing exponentially via the use of sensors, especially in the context of the ‘Internet of Things’, and also as I said before via the use of mobile devices and social networking sites.

Hence, as an organisation of any size, your concern will most probably about your capacity to be a ‘prophet’, i.e. to be able to most precisely forecast not only long term future, but also medium and short term ones. Definitely, Big Data mastery would not be the only thing to guarantee this higher decision taking and therefore managerial competency, but without it, there is a greater probability your organisation would lag behind.

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