Big Data analytics has been remained a backbone and mainstay of many enterprises most especially Telecommunication and Information Technology enterprises Storage processing extraction as well as the utilization of the insight from this data has been of immense contribution to the enterprise operations In previous times when many Information technology systems existed as disparate systems in silos and not interconnected data analysis and consumption at just one system was rampant However with the advent of the internet there arose urgent need and requirement for data and the processed information to be shared across systems This necessitated the birth of the ETL Extract Transform and Load in Business Intelligence where data transformation and reloading as well as re use was made possible Telecommunication companies as a result made huge investments in this ETL technology spanning across data warehousing staff software and hardware A huge volume of data generation occurs daily with the advent of smart devices leveraging on digital technologies on the telecommunication operators network network probes click streams for browsing sessions and call detail records are generated daily on the network Growth in Internet of Things and advanced communication technologies and digital sensors also is seeing an increasing volume of data to be analyzed for valuable insights for the enterprise on the cellular operator s network There are challenges in utilizing the traditional mode of processing data to analyze this big data as it requires great parallel processing
