Use cases and challenges in telecom big data analytics

There has been much hype about big data analytics – a collection of technologies, including the Hadoop distributed file system, NoSQL databases, and machine learning tools. One study estimated that it can generate hundreds of billions of dollars of value across industries [1]. Another study reported that 75 of telecom operators surveyed would implement big data initiatives by 2017 [2]. Every operator is seeking new ways to increase operational efficiency and marketing effectiveness by leveraging big data technologies. But the question is how does big data analytics differ from prior arts such as data warehousing and statistical methods, in terms of the capabilities of uncovering insights from large volume of datasets? What are the compelling use cases in telecom, and what are the challenges? This paper provides a retrospect on how telecom operators have been striving, before the era of big data, to analyze large volumes of data in order to support their business and operation. We then examine the driving forces of big data analytics in the telecom domain and the benefits it offers. Finally we provide example use cases of big data analytics and the associated challenges, with the hope to inspire new research ideas that can eventually benefit the practice of the telecommunication industry.