The evolution of social networking platforms and rapid increase in the production and exchange of information has served as the basis for the realisation of big data and big data analytics – both of which are the drivers behind business development and brand recognition.
Google’s Executive Chairman Eric Schmidt is on record as having said, “From the dawn of civilisation until 2003, humankind generated five exabytes of data. Now we produce five exabytes every two days … and the pace is accelerating.”
It is quite clear that big data has radically altered the traditional paradigms of marketing, client service and brand development. Yesterday, the brand relied on advertising, launches and gimmick marketing to lock in the customer and sustain a level of service to secure loyalty.
Today, the emphasis is on analytics incorporated into the social network framework, mobile infrastructure and the cloud strengthen word-of-mouth to create brand awareness.
Analytics or the ability to extract data and utilise this information strategically adds value in terms of building the brand and the business behind the brand. But, of equal importance, is the ability to use this information to enhance operations.
In an information-centric market, the customer is now in a position to direct and influence companies and not the other way around.
The Moore’s Law influence
Industry analysts have made the point that the increase in volume of data correlates with the product lifecycle as prescribed by Moore’s Law – which, in terms of computer hardware, the number of transistors on integrated circuits doubles about every two years.
There is no doubt about the inherent ability of today’s users to generate huge volumes of data and how this affects brand recognition.
However, in order to truly benefit from this growing trend and reinforce key areas of the business, including customer services and marketing, there is a necessity to understand why big data analytics is taken on board and if it is being applied for the right reasons.
Often businesses are not in a position to take analytics on board – they do not possess the skills or technology to implement solutions or concepts in order to take real advantage.
With this scenario in mind and the escalating levels of data, it is no surprise that cloud has emerged as the catalyst for the adoption and value-added rollout of big data analytics.
This resource makes big data management and adoption easier for business – irrespective of size or scope.
It is difficult to predict the pace of market growth or the ramifications, it is quite clear that big data and the cloud will develop as disruptive technologies.