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Big Data & Machine Learning in Telecom-Global Market Insights and Sales Trends 2025

Big Data & Machine Learning in Telecom-Global Market Insights and Sales Trends 2025

Publishing Date : Mar, 2025

License Type :
 

Report Code : 1856021

No of Pages : 111

Synopsis
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.
The global Big Data & Machine Learning in Telecom market size is expected to reach US$ million by 2029, growing at a CAGR of % from 2023 to 2029. The market is mainly driven by the significant applications of Big Data & Machine Learning in Telecom in various end use industries. The expanding demands from the Processing, Storage and Analyzing,, are propelling Big Data & Machine Learning in Telecom market. Descriptive Analytics, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Predictive Analytics segment is estimated at % CAGR for the next seven-year period.
The Global Mobile Economy Development Report 2023 released by GSMA Intelligence pointed out that by the end of 2022, the number of global mobile users would exceed 5.4 billion. The mobile ecosystem supports 16 million jobs directly and 12 million jobs indirectly.
According to our Communications Research Centre, in 2022, the global communication equipment was valued at US$ 100 billion. The U.S. and China are powerhouses in the manufacture of communications equipment. According to data from the Ministry of Industry and Information Technology of China, the cumulative revenue of telecommunications services in 2022 was ¥1.58 trillion, an increase of 8% over the previous year. The total amount of telecommunications business calculated at the price of the previous year reached ¥1.75 trillion, a year-on-year increase of 21.3%. In the same year, the fixed Internet broadband access business revenue was ¥240.2 billion, an increase of 7.1% over the previous year, and its proportion in the telecommunications business revenue decreased from 15.3% in the previous year to 15.2%, driving the telecommunications business revenue to increase by 1.1 percentage points.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Big Data & Machine Learning in Telecom, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Big Data & Machine Learning in Telecom market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Big Data & Machine Learning in Telecom market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Big Data & Machine Learning in Telecom sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Big Data & Machine Learning in Telecom covered in this report include Allot, Argyle data, Ericsson, Guavus, HUAWEI, Intel, NOKIA, Openwave mobility and Procera networks, etc.
The global Big Data & Machine Learning in Telecom market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
Allot
Argyle data
Ericsson
Guavus
HUAWEI
Intel
NOKIA
Openwave mobility
Procera networks
Qualcomm
ZTE
Google
AT&T
Apple
Amazon
Microsoft
Global Big Data & Machine Learning in Telecom market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Big Data & Machine Learning in Telecom market, Segment by Type:
Descriptive Analytics
Predictive Analytics
Machine Learning
Feature Engineering
Global Big Data & Machine Learning in Telecom market, by Application
Processing
Storage
Analyzing
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Big Data & Machine Learning in Telecom companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
Index
1 Market Overview of Big Data & Machine Learning in Telecom
1.1 Big Data & Machine Learning in Telecom Market Overview
1.1.1 Big Data & Machine Learning in Telecom Product Scope
1.1.2 Big Data & Machine Learning in Telecom Market Status and Outlook
1.2 Global Big Data & Machine Learning in Telecom Market Size Overview by Region 2018 VS 2022 VS 2029
1.3 Global Big Data & Machine Learning in Telecom Market Size by Region (2018-2029)
1.4 Global Big Data & Machine Learning in Telecom Historic Market Size by Region (2018-2023)
1.5 Global Big Data & Machine Learning in Telecom Market Size Forecast by Region (2024-2029)
1.6 Key Regions, Big Data & Machine Learning in Telecom Market Size (2018-2029)
1.6.1 North America Big Data & Machine Learning in Telecom Market Size (2018-2029)
1.6.2 Europe Big Data & Machine Learning in Telecom Market Size (2018-2029)
1.6.3 Asia-Pacific Big Data & Machine Learning in Telecom Market Size (2018-2029)
1.6.4 Latin America Big Data & Machine Learning in Telecom Market Size (2018-2029)
1.6.5 Middle East & Africa Big Data & Machine Learning in Telecom Market Size (2018-2029)
2 Big Data & Machine Learning in Telecom Market by Type
2.1 Introduction
2.1.1 Descriptive Analytics
2.1.2 Predictive Analytics
2.1.3 Machine Learning
2.1.4 Feature Engineering
2.2 Global Big Data & Machine Learning in Telecom Market Size by Type: 2018 VS 2022 VS 2029
2.2.1 Global Big Data & Machine Learning in Telecom Historic Market Size by Type (2018-2023)
2.2.2 Global Big Data & Machine Learning in Telecom Forecasted Market Size by Type (2024-2029)
2.3 Key Regions Market Size by Type
2.3.1 North America Big Data & Machine Learning in Telecom Revenue Breakdown by Type (2018-2029)
2.3.2 Europe Big Data & Machine Learning in Telecom Revenue Breakdown by Type (2018-2029)
2.3.3 Asia-Pacific Big Data & Machine Learning in Telecom Revenue Breakdown by Type (2018-2029)
2.3.4 Latin America Big Data & Machine Learning in Telecom Revenue Breakdown by Type (2018-2029)
2.3.5 Middle East and Africa Big Data & Machine Learning in Telecom Revenue Breakdown by Type (2018-2029)
3 Big Data & Machine Learning in Telecom Market Overview by Application
3.1 Introduction
3.1.1 Processing
3.1.2 Storage
3.1.3 Analyzing
3.2 Global Big Data & Machine Learning in Telecom Market Size by Application: 2018 VS 2022 VS 2029
3.2.1 Global Big Data & Machine Learning in Telecom Historic Market Size by Application (2018-2023)
3.2.2 Global Big Data & Machine Learning in Telecom Forecasted Market Size by Application (2024-2029)
3.3 Key Regions Market Size by Application
3.3.1 North America Big Data & Machine Learning in Telecom Revenue Breakdown by Application (2018-2029)
3.3.2 Europe Big Data & Machine Learning in Telecom Revenue Breakdown by Application (2018-2029)
3.3.3 Asia-Pacific Big Data & Machine Learning in Telecom Revenue Breakdown by Application (2018-2029)
3.3.4 Latin America Big Data & Machine Learning in Telecom Revenue Breakdown by Application (2018-2029)
3.3.5 Middle East and Africa Big Data & Machine Learning in Telecom Revenue Breakdown by Application (2018-2029)
4 Big Data & Machine Learning in Telecom Competition Analysis by Players
4.1 Global Big Data & Machine Learning in Telecom Market Size by Players (2018-2023)
4.2 Global Top Players by Company Type (Tier 1, Tier 2 and Tier 3) & (based on the Revenue in Big Data & Machine Learning in Telecom as of 2022)
4.3 Date of Key Players Enter into Big Data & Machine Learning in Telecom Market
4.4 Global Top Players Big Data & Machine Learning in Telecom Headquarters and Area Served
4.5 Key Players Big Data & Machine Learning in Telecom Product Solution and Service
4.6 Competitive Status
4.6.1 Big Data & Machine Learning in Telecom Market Concentration Rate
4.6.2 Mergers & Acquisitions, Expansion Plans
5 Company (Top Players) Profiles
5.1 Allot
5.1.1 Allot Profile
5.1.2 Allot Main Business
5.1.3 Allot Big Data & Machine Learning in Telecom Products, Services and Solutions
5.1.4 Allot Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.1.5 Allot Recent Developments
5.2 Argyle data
5.2.1 Argyle data Profile
5.2.2 Argyle data Main Business
5.2.3 Argyle data Big Data & Machine Learning in Telecom Products, Services and Solutions
5.2.4 Argyle data Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.2.5 Argyle data Recent Developments
5.3 Ericsson
5.3.1 Ericsson Profile
5.3.2 Ericsson Main Business
5.3.3 Ericsson Big Data & Machine Learning in Telecom Products, Services and Solutions
5.3.4 Ericsson Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.3.5 Guavus Recent Developments
5.4 Guavus
5.4.1 Guavus Profile
5.4.2 Guavus Main Business
5.4.3 Guavus Big Data & Machine Learning in Telecom Products, Services and Solutions
5.4.4 Guavus Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.4.5 Guavus Recent Developments
5.5 HUAWEI
5.5.1 HUAWEI Profile
5.5.2 HUAWEI Main Business
5.5.3 HUAWEI Big Data & Machine Learning in Telecom Products, Services and Solutions
5.5.4 HUAWEI Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.5.5 HUAWEI Recent Developments
5.6 Intel
5.6.1 Intel Profile
5.6.2 Intel Main Business
5.6.3 Intel Big Data & Machine Learning in Telecom Products, Services and Solutions
5.6.4 Intel Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.6.5 Intel Recent Developments
5.7 NOKIA
5.7.1 NOKIA Profile
5.7.2 NOKIA Main Business
5.7.3 NOKIA Big Data & Machine Learning in Telecom Products, Services and Solutions
5.7.4 NOKIA Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.7.5 NOKIA Recent Developments
5.8 Openwave mobility
5.8.1 Openwave mobility Profile
5.8.2 Openwave mobility Main Business
5.8.3 Openwave mobility Big Data & Machine Learning in Telecom Products, Services and Solutions
5.8.4 Openwave mobility Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.8.5 Openwave mobility Recent Developments
5.9 Procera networks
5.9.1 Procera networks Profile
5.9.2 Procera networks Main Business
5.9.3 Procera networks Big Data & Machine Learning in Telecom Products, Services and Solutions
5.9.4 Procera networks Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.9.5 Procera networks Recent Developments
5.10 Qualcomm
5.10.1 Qualcomm Profile
5.10.2 Qualcomm Main Business
5.10.3 Qualcomm Big Data & Machine Learning in Telecom Products, Services and Solutions
5.10.4 Qualcomm Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.10.5 Qualcomm Recent Developments
5.11 ZTE
5.11.1 ZTE Profile
5.11.2 ZTE Main Business
5.11.3 ZTE Big Data & Machine Learning in Telecom Products, Services and Solutions
5.11.4 ZTE Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.11.5 ZTE Recent Developments
5.12 Google
5.12.1 Google Profile
5.12.2 Google Main Business
5.12.3 Google Big Data & Machine Learning in Telecom Products, Services and Solutions
5.12.4 Google Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.12.5 Google Recent Developments
5.13 AT&T
5.13.1 AT&T Profile
5.13.2 AT&T Main Business
5.13.3 AT&T Big Data & Machine Learning in Telecom Products, Services and Solutions
5.13.4 AT&T Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.13.5 AT&T Recent Developments
5.14 Apple
5.14.1 Apple Profile
5.14.2 Apple Main Business
5.14.3 Apple Big Data & Machine Learning in Telecom Products, Services and Solutions
5.14.4 Apple Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.14.5 Apple Recent Developments
5.15 Amazon
5.15.1 Amazon Profile
5.15.2 Amazon Main Business
5.15.3 Amazon Big Data & Machine Learning in Telecom Products, Services and Solutions
5.15.4 Amazon Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.15.5 Amazon Recent Developments
5.16 Microsoft
5.16.1 Microsoft Profile
5.16.2 Microsoft Main Business
5.16.3 Microsoft Big Data & Machine Learning in Telecom Products, Services and Solutions
5.16.4 Microsoft Big Data & Machine Learning in Telecom Revenue (US$ Million) & (2018-2023)
5.16.5 Microsoft Recent Developments
6 North America
6.1 North America Big Data & Machine Learning in Telecom Market Size by Country (2018-2029)
6.2 U.S.
6.3 Canada
7 Europe
7.1 Europe Big Data & Machine Learning in Telecom Market Size by Country (2018-2029)
7.2 Germany
7.3 France
7.4 U.K.
7.5 Italy
7.6 Russia
7.7 Nordic Countries
7.8 Rest of Europe
8 Asia-Pacific
8.1 Asia-Pacific Big Data & Machine Learning in Telecom Market Size by Region (2018-2029)
8.2 China
8.3 Japan
8.4 South Korea
8.5 Southeast Asia
8.6 India
8.7 Australia
8.8 Rest of Asia-Pacific
9 Latin America
9.1 Latin America Big Data & Machine Learning in Telecom Market Size by Country (2018-2029)
9.2 Mexico
9.3 Brazil
9.4 Rest of Latin America
10 Middle East & Africa
10.1 Middle East & Africa Big Data & Machine Learning in Telecom Market Size by Country (2018-2029)
10.2 Turkey
10.3 Saudi Arabia
10.4 UAE
10.5 Rest of Middle East & Africa
11 Big Data & Machine Learning in Telecom Market Dynamics
11.1 Big Data & Machine Learning in Telecom Industry Trends
11.2 Big Data & Machine Learning in Telecom Market Drivers
11.3 Big Data & Machine Learning in Telecom Market Challenges
11.4 Big Data & Machine Learning in Telecom Market Restraints
12 Research Finding /Conclusion
13 Methodology and Data Source
13.1 Methodology/Research Approach
13.1.1 Research Programs/Design
13.1.2 Market Size Estimation
13.1.3 Market Breakdown and Data Triangulation
13.2 Data Source
13.2.1 Secondary Sources
13.2.2 Primary Sources
13.3 Disclaimer
13.4 Author List

Published By : QY Research

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