Telco Big Data, Analytics and Machine Learning

ABI Research has been tracking the telecom market since its inception, both in research services and through individual application report analysis. It is this basis, in addition to data gathered from primary research, secondary research, and consulting engagements that guides the segmentation analysis in the forecasts. Data were generated through tracking of companies and trends in different and compared with publicly available industry data.  This analysis is top-down with bottom up data points referenced for triangulation.

Regional segmentation is algorithmically derived based on a number of ABI Research databases that considers subscribers, telecom technology (e.g. 2G, 3G, 4G) and operator revenues.   Forecasts are through 2021. 

Segmentation definitions:

Big Data:  Big Data spending includes hardware, software and services to set up Big Data Lakes, Hadoop (or Spark) clusters, to capture, store, and manage large datasets typical of telecom operators. 

Analytics:  These are the Big Data analytics software used for a wide variety of applications use by telecom operators, ranging from Fraud and Risk Management, Marketing, Pricing and Churn management, operations, facility management, and network optimization.  Many mobile operators will use analytic packages from their vendors, who have built them using Machine Learning.  

Services:  Professional services to install and maintain Big Data and Analytics solutions at the telecom operators.

Revenue:  Spending by telecom operators to procure Big Data Analytics and Machine Learning solutions.  Does not include spending by telecom operators pursuing internally developed solutions that might be developed using custom programming or based on Machine Learning platforms, for example, Python and various ML libraries. 

Descriptive:  Analytics and Machine Learning for analyzing current performance, including Business Intelligence when a part of a Big Data solution.  Non-Machine Learning based analytics are largely descriptive.

Predictive:  This is Machine Learning and Big Data applied for forecasting, and typically includes any number of Machine Learning tools, such as regression analysis and Deep Learning, and operators currently

Companies Mentioned