Global Big Data & Machine Learning in Telecom Market Size, Status and Forecast 2019-2025

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Telecom big data spending includes distributed storage and computing Hadoop (and Spark) clusters, HDFS file systems, SQL and NoSQL software database frameworks, and other operational software. Telecom analytics software, such as for revenue assurance, business intelligence, strategic marketing, and network performance, are considered separately. The evolution from non-machine learning based descriptive analytics to machine learning driven predictive analytics is also considered. Telecom data meets the fundamental 3Vs criteria of big data: velocity, variety, and volume, and should be supported with a big data infrastructure (processing, storage, and analytics) for both real-time and offline analysis. 
In 2018, the global Big Data & Machine Learning in Telecom market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2019-2025.

This report focuses on the global Big Data & Machine Learning in Telecom status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Big Data & Machine Learning in Telecom development in United States, Europe and China.

The key players covered in this study
    Allot
    Argyle data
    Ericsson
    Guavus
    HUAWEI
    Intel
    NOKIA
    Openwave mobility
    Procera networks
    Qualcomm
    ZTE
    Google
    AT&T
    Apple
    Amazon
    Microsoft

Market analysis by product type
    Descriptive analytics
    Predictive analytics
    Machine learning
    Feature engineering

Market analysis by market
    Processing
    Storage
    Analyzing

Market analysis by Region
    United States
    Europe
    China
    Japan
    Southeast Asia
    India
    Central & South America

The study objectives of this report are:
    To analyze global Big Data & Machine Learning in Telecom status, future forecast, growth opportunity, key market and key players.
    To present the Big Data & Machine Learning in Telecom development in United States, Europe and China.
    To strategically profile the key players and comprehensively analyze their development plan and strategies.
    To define, describe and forecast the market by product type, market and key regions.

In this study, the years considered to estimate the market size of Big Data & Machine Learning in Telecom are as follows:
    History Year: 2018-2019
    Base Year: 2018
    Estimated Year: 2019
    Forecast Year 2019 to 2025
For the data information by region, company, type and application, 2018 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.
Table of Contents

1 Report Overview
    1.1 Study Scope
    1.2 Key Market Segments
    1.3 Players Covered
    1.4 Market Analysis by Type
  
        1.4.2 Descriptive analytics
        1.4.3 Predictive analytics
        1.4.4 Machine learning
        1.4.5 Feature engineering
    1.5 Market by Application
        1.5.1 Global Big Data & Machine Learning in Telecom Market Share by Application (2018-2025)
        1.5.2 Processing
        1.5.3 Storage
        1.5.4 Analyzing
    1.6 Study Objectives
    1.7 Years Considered

2 Executive Summary
    2.1 Big Data & Machine Learning in Telecom Market Size
    2.2 Big Data & Machine Learning in Telecom Growth Trends by Regions
        2.2.1 Big Data & Machine Learning in Telecom Market Size by Regions (2018-2025)
        2.2.2 Big Data & Machine Learning in Telecom Market Share by Regions (2018-2025)
    2.3 Industry Trends
        2.3.1 Market Top Trends
        2.3.2 Market Use Cases

3 Key Players
    3.1 Big Data & Machine Learning in Telecom Revenue by Manufacturers (2018-2019)
    3.2 Big Data & Machine Learning in Telecom Key Players Head office and Area Served
    3.3 Key Players Big Data & Machine Learning in Telecom Product/Solution/Service
    3.4 Date of Enter into Big Data & Machine Learning in Telecom Market
    3.5 Key Players Big Data & Machine Learning in Telecom Funding/Investment Analysis
    3.6 Global Key Players Big Data & Machine Learning in Telecom Valuation & Market Capitalization
    3.7 Mergers & Acquisitions, Expansion Plans

4 Breakdown Data by Type and Application
    4.1 Global Big Data & Machine Learning in Telecom Market Size by Type (2018-2025)
    4.2 Global Big Data & Machine Learning in Telecom Market Size by Application (2017-2025)

5 United States
    5.1 United States Big Data & Machine Learning in Telecom Market Size (2018-2025)
    5.2 Big Data & Machine Learning in Telecom Key Players in United States
    5.3 United States Big Data & Machine Learning in Telecom Market Size by Type
    5.4 United States Big Data & Machine Learning in Telecom Market Size by Application

6 Europe
    6.1 Europe Big Data & Machine Learning in Telecom Market Size (2018-2025)
    6.2 Big Data & Machine Learning in Telecom Key Players in Europe
    6.3 Europe Big Data & Machine Learning in Telecom Market Size by Type
    6.4 Europe Big Data & Machine Learning in Telecom Market Size by Application

7 China
    7.1 China Big Data & Machine Learning in Telecom Market Size (2018-2025)
    7.2 Big Data & Machine Learning in Telecom Key Players in China
    7.3 China Big Data & Machine Learning in Telecom Market Size by Type
    7.4 China Big Data & Machine Learning in Telecom Market Size by Application

8 Rest of World
    8.1 Japan
        8.1.1 Japan Big Data & Machine Learning in Telecom Market Analysis
        8.1.2 Key Players in 
    8.2 Southeast Asia
        8.2.1 Southeast Asia Big Data & Machine Learning in Telecom Market Analysis
        8.2.2 Key Players in Southeast Asia
    8.3 India
        8.3.1 India Big Data & Machine Learning in Telecom Market Analysis
        8.3.2 Key Players in India

9 International Players Profiles
    9.1 Allot
        9.1.1 Allot Company Details
        9.1.2 Company Description and Business Overview
        9.1.3 Big Data & Machine Learning in Telecom Introduction
        9.1.4 Allot Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.1.5 Allot Recent Development
    9.2 Argyle data
        9.2.1 Argyle data Company Details
        9.2.2 Company Description and Business Overview
        9.2.3 Big Data & Machine Learning in Telecom Introduction
        9.2.4 Argyle data Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.2.5 Argyle data Recent Development
    9.3 Ericsson
        9.3.1 Ericsson Company Details
        9.3.2 Company Description and Business Overview
        9.3.3 Big Data & Machine Learning in Telecom Introduction
        9.3.4 Ericsson Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.3.5 Ericsson Recent Development
    9.4 Guavus
        9.4.1 Guavus Company Details
        9.4.2 Company Description and Business Overview
        9.4.3 Big Data & Machine Learning in Telecom Introduction
        9.4.4 Guavus Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.4.5 Guavus Recent Development
    9.5 HUAWEI
        9.5.1 HUAWEI Company Details
        9.5.2 Company Description and Business Overview
        9.5.3 Big Data & Machine Learning in Telecom Introduction
        9.5.4 HUAWEI Revenue in Big Data & Machine Learning in Telecom Business (2017-2018)
        9.5.5 HUAWEI Recent Development
    9.6 Intel
        9.6.1 Intel Company Details
        9.6.2 Company Description and Business Overview
        9.6.3 Big Data & Machine Learning in Telecom Introduction
        9.6.4 Intel Revenue in Big Data & Machine Learning in Telecom Business (2017-2018)
        9.6.5 Intel Recent Development
    9.7 NOKIA
        9.7.1 NOKIA Company Details
        9.7.2 Company Description and Business Overview
        9.7.3 Big Data & Machine Learning in Telecom Introduction
        9.7.4 NOKIA Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.7.5 NOKIA Recent Development
    9.8 Openwave mobility
        9.8.1 Openwave mobility Company Details
        9.8.2 Company Description and Business Overview
        9.8.3 Big Data & Machine Learning in Telecom Introduction
        9.8.4 Openwave mobility Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.8.5 Openwave mobility Recent Development
    9.9 Procera networks
        9.9.1 Procera networks Company Details
        9.9.2 Company Description and Business Overview
        9.9.3 Big Data & Machine Learning in Telecom Introduction
        9.9.4 Procera networks Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.9.5 Procera networks Recent Development
    9.10 Qualcomm
        9.10.1 Qualcomm Company Details
        9.10.2 Company Description and Business Overview
        9.10.3 Big Data & Machine Learning in Telecom Introduction
        9.10.4 Qualcomm Revenue in Big Data & Machine Learning in Telecom Business (2018-2019)
        9.10.5 Qualcomm Recent Development
    9.11 ZTE
    9.12 Google
    9.13 AT&T
    9.14 Apple
    9.15 Amazon
    9.16 Microsoft

10 Market Dynamics
    10.1 Drivers
    10.2 Opportunities
    10.3 Challenges
    10.4 Market Ecosystem
    10.5 Market Value Chain Analysis

11 Key Findings in This Report

12 Appendix
    12.1 Research Methodology
        12.1.1 Methodology/Research Approach
            12.1.1.1 Research Programs/Design
            12.1.1.2 Market Size Estimation
            12.1.1.3 Market Breakdown and Data Triangulation
        12.1.2 Data Source
            12.1.2.1 Secondary Sources
            12.1.2.2 Primary Sources
    12.2 Disclaimer
    12.3 Author Details

List of Tables and Figures Table Big Data & Machine Learning in Telecom Key Market Segments Table Key Players Big Data & Machine Learning in Telecom Covered Table Global Big Data & Machine Learning in Telecom Market Size Growth Rate by Type 2019-2025 (Million US$) Figure Global Big Data & Machine Learning in Telecom Market Size Market Share by Type 2019-2025 Figure Descriptive analytics Figures Table Key Players of Descriptive analytics Figure Predictive analytics Figures Table Key Players of Predictive analytics Figure Machine learning Figures Table Key Players of Machine learning Figure Feature engineering Figures Table Key Players of Feature engineering Table Global Big Data & Machine Learning in Telecom Market Size Growth by Application 2019-2025 (Million US$) Figure Processing Case Studies Figure Storage Case Studies Figure Analyzing Case Studies Figure Big Data & Machine Learning in Telecom Report Years Considered Table Global Big Data & Machine Learning in Telecom Market Size 2018-2025 (Million US$) Figure Global Big Data & Machine Learning in Telecom Market Size and Growth Rate 2018-2025 (Million US$) Table Global Big Data & Machine Learning in Telecom Market Size by Regions 2019-2025 (Million US$) Table Global Big Data & Machine Learning in Telecom Market Size by Regions 2018-2025 (Million US$) Table Global Big Data & Machine Learning in Telecom Market Share by Regions 2014-2019 Figure Global Big Data & Machine Learning in Telecom Market Share by Regions 2018-2025 Figure Global Big Data & Machine Learning in Telecom Market Share by Regions 2019-2025 Table Market Top Trends Table Global Big Data & Machine Learning in Telecom Revenue by Manufacturers (2018-2019) (Million US$) Table Global Big Data & Machine Learning in Telecom Market Share by Manufacturers (2018-2019) Figure Global Big Data & Machine Learning in Telecom Market Share by Manufacturers in 2019 Table Global Key Players Big Data & Machine Learning in Telecom Funding/Investment Analysis (Million US$) Table Global Key Players Big Data & Machine Learning in Telecom Valuation & Market Capitalization (Million US$) Table Mergers & Acquisitions, Expansion Plans Table Global Big Data & Machine Learning in Telecom Market Size by Type (2018-2025) (Million US$) Table Global Big Data & Machine Learning in Telecom Market Share by Type (2018-2025) Figure Global Big Data & Machine Learning in Telecom Market Size Share by Type (2018-2025) Table Global Big Data & Machine Learning in Telecom Market Size by Application (2018-2025) (Million US$) Table Global Big Data & Machine Learning in Telecom Market Size Share by Application (2018-2025) Figure Global Big Data & Machine Learning in Telecom Market Size Market Share by Application (2018-2025) Figure Global Big Data & Machine Learning in Telecom Revenue Market Share by Application in 2018 Figure United States Big Data & Machine Learning in Telecom Market Size 2018-2025 (Million US$) Table United States Key Players Big Data & Machine Learning in Telecom Revenue (2018-2019) (Million US$) Table United States Key Players Big Data & Machine Learning in Telecom Market Share (2018-2019) Table United States Big Data & Machine Learning in Telecom Market Size by Type (2018-2025) (Million US$) Table United States Big Data & Machine Learning in Telecom Market Share by Type (2018-2025) Table United States Big Data & Machine Learning in Telecom Market Size by Application (2018-2025) (Million US$) Table United States Big Data & Machine Learning in Telecom Market Share by Application (2018-2025) Figure Europe Big Data & Machine Learning in Telecom Market Size 2018-2025 (Million US$) Table Europe Key Players Big Data & Machine Learning in Telecom Revenue (2018-2019) (Million US$) Table Europe Key Players Big Data & Machine Learning in Telecom Market Share (2018-2019) Table Europe Big Data & Machine Learning in Telecom Market Size by Type (2018-2025) (Million US$) Table Europe Big Data & Machine Learning in Telecom Market Share by Type (2018-2025) Table Europe Big Data & Machine Learning in Telecom Market Size by Application (2018-2025) (Million US$) Table Europe Big Data & Machine Learning in Telecom Market Share by Application (2018-2025) Figure China Big Data & Machine Learning in Telecom Market Size 2018-2025 (Million US$) Table China Key Players Big Data & Machine Learning in Telecom Revenue (2018-2019) (Million US$) Table China Key Players Big Data & Machine Learning in Telecom Market Share (2018-2019) Table China Big Data & Machine Learning in Telecom Market Size by Type (2018-2025) (Million US$) Table China Big Data & Machine Learning in Telecom Market Share by Type (2018-2025) Table China Big Data & Machine Learning in Telecom Market Size by Application (2018-2025) (Million US$) Table China Big Data & Machine Learning in Telecom Market Share by Application (2018-2025) Figure Market Size in Japan Big Data & Machine Learning in Telecom 2018-2025 (Million US$) Figure Market Size in Southeast Asia Big Data & Machine Learning in Telecom 2018-2025 (Million US$) Figure Market Size in India Big Data & Machine Learning in Telecom 2018-2025 (Million US$) Table Allot Company Details Table Allot Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Allot Recent Development Table Argyle data Company Details Table Argyle data Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Argyle data Recent Development Table Ericsson Company Details Table Ericsson Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Ericsson Recent Development Table Guavus Company Details Table Guavus Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Guavus Recent Development Table HUAWEI Company Details Table HUAWEI Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table HUAWEI Recent Development Table Intel Company Details Table Intel Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Intel Recent Development Table NOKIA Company Details Table NOKIA Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table NOKIA Recent Development Table Openwave mobility Company Details Table Openwave mobility Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Openwave mobility Recent Development Table Procera networks Company Details Table Procera networks Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Procera networks Recent Development Table Qualcomm Company Details Table Qualcomm Revenue in Big Data & Machine Learning in Telecom Business in 2018 and 2019 Table Qualcomm Recent Development Table ZTE Company Details Table Google Company Details Table AT&T Company Details Table Apple Company Details Table Amazon Company Details Table Microsoft Company Details Table Research Programs/Design for This Report Figure Bottom-up and Top-down Approaches for This Report Figure Data Triangulation Table Key Data Information from Secondary Sources Table Key Data Information from Primary Sources

This research study involved the extensive usage of both primary and secondary data sources.  The research process involved the study of various factors affecting the industry, including the government policy, market environment, competitive landscape, historical data, present trends in the market, technological innovation, upcoming technologies and the technical progress in related industry, and market risks, opportunities, market barriers and challenges. Top-down and bottom-up approaches are used to validate the global market size market and estimate the market size for manufacturers, regions segments, product segments and applications (end users). All possible factors that influence the markets included in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. The market size for top-level markets and sub-segments is normalized, and the effect of inflation, economic downturns, and regulatory & policy changes or other factors are not accounted for in the market forecast. This data is combined and added with detailed inputs and analysis from QYResearch and presented in this report.
 

After complete market engineering with calculations for market statistics; market size estimations; market forecasting; market breakdown; and data triangulation, extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. In the complete market engineering process, both top-down and bottom-up approaches were extensively used, along with several data triangulation methods, to perform market estimation and market forecasting for the overall market segments and sub segments listed in this report. Extensive qualitative and further quantitative analysis is also done from all the numbers arrived at in the complete market engineering process to list key information throughout the report.
 

Secondary Sources occupies Approximately 25% of Sources, such as press releases, annual reports, Non-Profit organizations, industry associations, governmental agencies and customs data, and so on; This research study involved the usage of widespread secondary sources; directories; databases such as Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), TRADING ECONOMICS, and avention; Investing News Network; statista; Federal Reserve Economic Data; annual reports; BIS Statistics; ICIS; company house documents; CAS(American Chemical Society); investor presentations; and SEC filings of companies. Secondary research was used to identify and collect information useful for the extensive, technical, market-oriented, and commercial study of the Light Aircraft market. It was also used to obtain important information about the top players, market classification and segmentation according to industry trends to the bottom-most level, and key developments related to market and technology perspectives.
 

In the primary research process, various sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side include product manufacturers (and their competitors), opinion leaders, industry experts, research institutions, distributors, dealer and traders, as well as the raw materials suppliers and producers etc.
 

The primary sources from the demand side include industry experts such as business leaders, marketing and sales directors, technology and innovation directors, supply chain executive, end users (product buyers), and related key executives from various key companies and organizations operating in the global market.
 

Primary research was conducted to identify segmentation types, product price range, product applications, key players, raw materials supply and the downstream demand, industry status and outlook, and key market dynamics such as risks, influence factors, opportunities, market barriers, industry trends, and key player strategies.
 

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