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【マーケットデータ】通信会社のビッグデータ、解析、機械学習

Telco Big Data, Analytics and Machine Learning

Updated Semiannually | Data | MD-BDAM-101 | 9 tables | 9 charts | Excel

 

出版社 出版年月価格 図表数
ABI Research
ABIリサーチ
2016年9月お問い合わせください 18

サマリー

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

 

ABIリサーチの調査レポートの詳細については、サンプルをご請求ください。

(株式会社データリソース 03-3582-2531、office@dri.co.jp)

 



目次

  1. Telecom Big Data, ML, and Non-ML Analytics Revenue, World Markets, Forecast: 2015 to 2021
  2. Telecom and IT Big Data, World Markets, Forecast: 2015 to 2021
  3. Telecom Big Data by Component, World Markets, Forecast: 2015 to 2021
  4. Telecom Big Data Revenue by Region, World Markets, Forecast: 2015 to 2021
  5. Telecom Analytics Revenue by Region, World Markets, Forecast: 2015 to 2021
  6. Telecom Analytics Machine Learning Revenue by Region, World Markets, Forecast: 2015 to 2021
  7. Telecom Analytics Non-machine Learning Revenue by Region, World Markets, Forecast: 2015 to 2021
  8. ML Telcom Analytics Revenue by Component, World Markets, Forecast: 2015 to 2021
  9. Non-ML Telcom Analytics Revenue by Component, World Markets, Forecast: 2015 to 2021

 

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