2.6 billion mobile telephony subscriptions exist globally today, while it is predicted that 6.1 billion users will exploit mobile devices by 2020, overtaking the number of active fixed line subscriptions [Ericsson Mobility Report, 2016]. This huge number of smartphone users will be increased to 9.2 billion, if Internet of Things (IoT) and Machine to Machine (M2M) services are taken into account. When mobile broadband is also considered, 26 billion interconnected mobile devices is expected to increase after 5 years’ time. All such mobile devices will produce a huge amount of data, which will provide a great impact on society and offer important opportunities for business exploitation. In addition, a large amount of data will be produced from the IoT devices and sensors incorporated into moving machines/vehicles.
The characteristics of such data are specific and process, as well as analysis of it, will be required very soon for business analytics purposes. In this framework, big data and mobile analytics is an emerging scientific topic, which will be thoroughly studied during next years to support the efficient collection, analysis and process of such data, towards achieving interesting and useful information for enhanced business development and effective mobile marketing purposes [Guo, Ah-Chung, Dohler, Zheng & Kim, 2016]. The results of such big data analysis will provide insights to understand mobile users’ behavior and requirements and support the provision of real-time decision making decisions.
In addition, such rapid expansion of mobile networks has enabled for the realization of a global infrastructure, generating spatio-temporal network-level data. The big data and mobile analytics will support the discovery of new meaningful patters and knowledge from a huge amount of collected data, generated from mobile users at the network-level or the application-level [Yazti & Krishnaswamy, 2014]. Such analysis, will also identify and debate the main challenges and opportunities, in terms of new applications and frameworks, to which the mobile data management and mobile data mining experts should elaborate on.
The new era of Visual Mobile Analytics
In this framework, businesses develop software solutions, emphasizing on the data analysis process. Several analytics solutions already exist on the web, but since mobile data traffic now outperforms web data traffic, expecting a huge increase during the next years, the future is in visual mobile analytics. The existing visual mobile analytics tools provide visual reports, allowing to analyze the mobile users’ behavior. Next-generation visual mobile analytics tools will provide actionable insights, which will move businesses forward by not only indicating exactly what the issues are, but also suggesting which measures need to be taken to correct them [venturebeat]. In this direction, future mobile devices will exploit several sensors to create data, allowing real-time analysis.
Whenever an event is triggered by the data analysis, it can be pushed to the users via the mobile devices. If the mobile device also allows the user to respond immediately, the efficiency as well perhaps customer satisfaction will increase [datafloq]. The big data and mobile analytics represent a competitive advantage to businesses for advertising, marketing and public relations purposes. Big data metrics and measurements will eclipse traditional social media monitoring and analytics tools. This is okay with the most of the social media marketers, since counting metrics does not deliver value by itself. Big data analytics offer marketers the promise of replacing valuations based on size to actionable business analysis.
If a business can afford to subscribe to a social media monitoring tool, such as Mentionlytics, Mention etc, it is time to start thinking in terms of the big data and mobile future [maximizesocialbusiness]. For example, by using Mentionlytics, businesses are able to have available a huge number of data regarding customers’ information, trying to understand them better, take more efficient marketing decisions and monitor what they wish. A tool like that continues to change the way that businesses approach market research and customer relationships, while brands can no longer afford not to be listening through social media and the web. This tool is able to provide insights for a target audience and interests that other brands talk about, as well as plenty of data, which can help a brand tailor customers’ communications to get the most from them.
Big data and mobile analytics could also help with product development, meaning that consumers ultimately get a better product or service. By listening to what customers’ wish, where there is a gap in the offering, how existing products can be improved and so on, businesses can make decisions on the direction of their product development and offerings. They can get instant feedback regarding their marketing activities, can respond to complaints and understand, if there is a recurring issue.
The future will bring the case, where customers can contact a brand, by using social media and that brand instantly knows their purchase history, their contact details, as well as their relationship to the brand, in order to respond promptly. This could be seen as an opportunity for businesses to better understand and please customers [fourthsource].
 Ericsson Mobility Report, mobile world congress edition, February 2016
 J. Guo, T. Ah-Chung, M. Dohler, K. Zheng, W.-Y. Yura Kim, Special Issue on “Mobile Big Data”, IEEE Network Magazine, 2016.
 D. Z. Yazti, S. Krishnaswamy, “Mobile big data analytics: research, practice, and opportunities”, in 15th IEEE International Conference on Mobile Data Management (MDM 2014), July 2014.