Big Data, BI and Advanced Analytics


Big Data BI and AnalyticsBig data, which includes unstructured data and social media content, just keeps growing. Despite the complexities to store, manage, access and derive insight from this vast pool of information, businesses can gain great business value from it – so much that it can increase revenues and reduce costs significantly. This can be achieved by deploying advanced analytics methods such as sentiment analysis and segmentation to big data as well.It is no surprise that the explosive growth in the amount of data, continues to accelerate in terms of sheer volume. In fact, industry reports reveal that 90% of the data in the world today was created within the last two years. Although many experts and businesses could see the signposts along the way, few were prepared for how quickly and by how much data would grow within such a short space of time.

Absolutely everything, including every micro activity, can be logged, stored and analysed today, to the extent that some businesses have become intimidated by this information overload. The term “big data” has emerged to describe this growth along with the technology and systems required to manage and leverage it. Big data typically refers to too much data to store on one machine. Generally speaking, big data extends beyond structured data as well, whereby data sets can no longer be easily analysed or managed with traditional data management tools, methods and platforms.

One such example of unstructured data is the ever increasing social network – which is an exciting source of big data as it contains information on the perceptions that the customers have of the organisation.  Any business able to capitalise on these perceptions certainly has a competitive advantage. However, this information usually sits outside the organisation’s boundaries and as such makes organising and managing it an enormously complex task – as organisations need to decide where they are going to put this data and what they are going to do with it.

By empowering business decision makers with timely insight into this bigger set of data, combined with their customers’ sentiments, decision makers can be equipped to increase business agility and customer loyalty and obviously to reduce churn. This in turn will drive top and bottom line growth, reduce risk and achieve a significantly higher return on the cost of data.

One solution in this space is to segment the organisation’s customer base to ensure a more interactive channel – and allow for more engagement with specific segments to ascertain what those particular customers are feeling, thinking and saying about the brand. This can be done through the inventive utilisation of advanced analytics technologies combined with unstructured data approaches, such as sentiment analysis combined with segmentation.

Big data technology will play an increasingly important role within the data ecosystem that supports analytics and BI in the future – especially as social and mobile usage keeps growing. In the meantime, BI users will continue to demand integrated BI platforms with ‘big data’ combined together with collaborative components. Solution providers will now need to deliver on the increased promise of business value, which has been moved even higher up on the strategic agenda.

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