In 1876 Alexander Graham Bell made the first telephone calls using electrical signals conducted over telegraph wires. The Bell Telephone Company was founded in 1877 and by 1886 more than 150,000 people in the U.S. owned a telephone. Since these early pioneering days innovation in telecommunications has grown at an incredible pace and today generates vast quantities of associated data that is collected and stored by telecommunications companies as ‘Big Data’. In his book ‘The Rise of Humans: How to outsmart the digital deluge’, David Coplin, Chief Envisioning Officer at Microsoft UK, suggests that the biggest change we have undertaken over the last 10 years is that we no longer use technology just to connect over great distances, we are increasingly using it to connect when the distances are inconsequential, thus generating a rising tide of ‘Big Data’.
Big Data in Telecoms is a broadly used term that references both the quantity of data being generated and stored within the industry and the data analysis techniques for extracting business intelligence from that data. Within the industry there are many approaches used to derive meaning from the data sets, and there are many challenges also. These include the storage of data in silos that are not linked, the complexity of the applications available to mine the data, and the lack of in-house knowledge to interpret the results and derive actionable meaning from them. Additionally, Big Data analysis is resource intensive and tends to produce generalisations, in part due to the difficulty in ensuring that the source data is accurate and contextually relevant.
In recent online discussions some new ideas are emerging that help to produce more focussed and relevant results through the use of smaller, more consolidated data sets. This technique is being termed Smart or Skinny Data. The benefits are that researchers can be more confident that the results being produced come from relevant data sets because irrelevant data has not been included.
Today’s increasing diversity of channels, devices and digital touch points is generating higher degrees of complexity which continue to inhibit our understanding of data, and whilst this may in itself be a headache it is also an opportunity to gain real business intelligence.
According to McKinsey, many organizations have yet to fully exploit the data or analytics capabilities they currently possess. So how would you go about taking advantage of the data you already have – or ‘Skinny Data’ as we now refer to it. This boils down to empowering a wide range of business users across you organization to access, understand and build insights from easily accessible data sources in a quick and easy format.
Here at CTI Group we have taken ‘Skinny Data’ to heart and by consolidating data from targeted data sources the sample data set is smaller and more relevant to the task in hand. This leads to several benefits. Firstly, the speed with which data can be analysed is much greater, making real-time analysis a reality. Secondly, using a consolidated and summarised data set requires less storage and resource to process. Thirdly the results are reliable and relevant and can easily be interpreted by staff with little or no training in data analysis.