Global Big Data & Machine Learning in Telecom Market Research Report 2023

Publication ID:

PB510240335

Publication Date:

October 11, 2023

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

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 is projected to reach US$ million in 2029, increasing from US$ million in 2022, with the CAGR of % during the period of 2023 to 2029. Influencing issues, such as economy environments, COVID-19 and Russia-Ukraine War, have led to great market fluctuations in the past few years and are considered comprehensively in the whole Big Data & Machine Learning in Telecom 91制片厂.
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 楼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 楼1.75 trillion, a year-on-year increase of 21.3%. In the same year, the fixed Internet broadband access business revenue was 楼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 Scope
This report, based on historical analysis (2018-2022) and forecast calculation (2023-2029), aims to help readers to get a comprehensive understanding of global Big Data & Machine Learning in Telecom market with multiple angles, which provides sufficient supports to readers鈥� strategy and decision making.
By Company
Allot
Argyle data
Ericsson
Guavus
HUAWEI
Intel
NOKIA
Openwave mobility
Procera networks
Qualcomm
ZTE
Google
AT&T
Apple
Amazon
Microsoft
Segment by Type
Descriptive Analytics
Predictive Analytics
Machine Learning
Feature Engineering
Segment by Application
Processing
Storage
Analyzing
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
The Big Data & Machine Learning in Telecom report covers below items:
Chapter 1: Product Basic Information (Definition, Type and Application)
Chapter 2: Global market size, regional market size. Market Opportunities and Challenges
Chapter 3: Companies鈥� Competition Patterns
Chapter 4: Product Type Analysis
Chapter 5: Product Application Analysis
Chapter 6 to 10: Country Level Value Analysis
Chapter 11: Companies鈥� Outline
Chapter 12: Market Conclusions
Chapter 13: Research Methodology and Data Source

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Big Data & Machine Learning in Telecom Market Size Growth Rate by Type: 2018 VS 2022 VS 2029
1.2.2 Descriptive Analytics
1.2.3 Predictive Analytics
1.2.4 Machine Learning
1.2.5 Feature Engineering
1.3 Market by Application
1.3.1 Global Big Data & Machine Learning in Telecom Market Growth by Application: 2018 VS 2022 VS 2029
1.3.2 Processing
1.3.3 Storage
1.3.4 Analyzing
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Big Data & Machine Learning in Telecom Market Perspective (2018-2029)
2.2 Big Data & Machine Learning in Telecom Growth Trends by Region
2.2.1 Global Big Data & Machine Learning in Telecom Market Size by Region: 2018 VS 2022 VS 2029
2.2.2 Big Data & Machine Learning in Telecom Historic Market Size by Region (2018-2023)
2.2.3 Big Data & Machine Learning in Telecom Forecasted Market Size by Region (2024-2029)
2.3 Big Data & Machine Learning in Telecom Market Dynamics
2.3.1 Big Data & Machine Learning in Telecom Industry Trends
2.3.2 Big Data & Machine Learning in Telecom Market Drivers
2.3.3 Big Data & Machine Learning in Telecom Market Challenges
2.3.4 Big Data & Machine Learning in Telecom Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Big Data & Machine Learning in Telecom Players by Revenue
3.1.1 Global Top Big Data & Machine Learning in Telecom Players by Revenue (2018-2023)
3.1.2 Global Big Data & Machine Learning in Telecom Revenue Market Share by Players (2018-2023)
3.2 Global Big Data & Machine Learning in Telecom Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Big Data & Machine Learning in Telecom Revenue
3.4 Global Big Data & Machine Learning in Telecom Market Concentration Ratio
3.4.1 Global Big Data & Machine Learning in Telecom Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Big Data & Machine Learning in Telecom Revenue in 2022
3.5 Big Data & Machine Learning in Telecom Key Players Head office and Area Served
3.6 Key Players Big Data & Machine Learning in Telecom Product Solution and Service
3.7 Date of Enter into Big Data & Machine Learning in Telecom Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Big Data & Machine Learning in Telecom Breakdown Data by Type
4.1 Global Big Data & Machine Learning in Telecom Historic Market Size by Type (2018-2023)
4.2 Global Big Data & Machine Learning in Telecom Forecasted Market Size by Type (2024-2029)
5 Big Data & Machine Learning in Telecom Breakdown Data by Application
5.1 Global Big Data & Machine Learning in Telecom Historic Market Size by Application (2018-2023)
5.2 Global Big Data & Machine Learning in Telecom Forecasted Market Size by Application (2024-2029)
6 North America
6.1 North America Big Data & Machine Learning in Telecom Market Size (2018-2029)
6.2 North America Big Data & Machine Learning in Telecom Market Growth Rate by Country: 2018 VS 2022 VS 2029
6.3 North America Big Data & Machine Learning in Telecom Market Size by Country (2018-2023)
6.4 North America Big Data & Machine Learning in Telecom Market Size by Country (2024-2029)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Big Data & Machine Learning in Telecom Market Size (2018-2029)
7.2 Europe Big Data & Machine Learning in Telecom Market Growth Rate by Country: 2018 VS 2022 VS 2029
7.3 Europe Big Data & Machine Learning in Telecom Market Size by Country (2018-2023)
7.4 Europe Big Data & Machine Learning in Telecom Market Size by Country (2024-2029)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Big Data & Machine Learning in Telecom Market Size (2018-2029)
8.2 Asia-Pacific Big Data & Machine Learning in Telecom Market Growth Rate by Region: 2018 VS 2022 VS 2029
8.3 Asia-Pacific Big Data & Machine Learning in Telecom Market Size by Region (2018-2023)
8.4 Asia-Pacific Big Data & Machine Learning in Telecom Market Size by Region (2024-2029)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Big Data & Machine Learning in Telecom Market Size (2018-2029)
9.2 Latin America Big Data & Machine Learning in Telecom Market Growth Rate by Country: 2018 VS 2022 VS 2029
9.3 Latin America Big Data & Machine Learning in Telecom Market Size by Country (2018-2023)
9.4 Latin America Big Data & Machine Learning in Telecom Market Size by Country (2024-2029)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Big Data & Machine Learning in Telecom Market Size (2018-2029)
10.2 Middle East & Africa Big Data & Machine Learning in Telecom Market Growth Rate by Country: 2018 VS 2022 VS 2029
10.3 Middle East & Africa Big Data & Machine Learning in Telecom Market Size by Country (2018-2023)
10.4 Middle East & Africa Big Data & Machine Learning in Telecom Market Size by Country (2024-2029)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Allot
11.1.1 Allot Company Detail
11.1.2 Allot Business Overview
11.1.3 Allot Big Data & Machine Learning in Telecom Introduction
11.1.4 Allot Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.1.5 Allot Recent Development
11.2 Argyle data
11.2.1 Argyle data Company Detail
11.2.2 Argyle data Business Overview
11.2.3 Argyle data Big Data & Machine Learning in Telecom Introduction
11.2.4 Argyle data Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.2.5 Argyle data Recent Development
11.3 Ericsson
11.3.1 Ericsson Company Detail
11.3.2 Ericsson Business Overview
11.3.3 Ericsson Big Data & Machine Learning in Telecom Introduction
11.3.4 Ericsson Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.3.5 Ericsson Recent Development
11.4 Guavus
11.4.1 Guavus Company Detail
11.4.2 Guavus Business Overview
11.4.3 Guavus Big Data & Machine Learning in Telecom Introduction
11.4.4 Guavus Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.4.5 Guavus Recent Development
11.5 HUAWEI
11.5.1 HUAWEI Company Detail
11.5.2 HUAWEI Business Overview
11.5.3 HUAWEI Big Data & Machine Learning in Telecom Introduction
11.5.4 HUAWEI Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.5.5 HUAWEI Recent Development
11.6 Intel
11.6.1 Intel Company Detail
11.6.2 Intel Business Overview
11.6.3 Intel Big Data & Machine Learning in Telecom Introduction
11.6.4 Intel Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.6.5 Intel Recent Development
11.7 NOKIA
11.7.1 NOKIA Company Detail
11.7.2 NOKIA Business Overview
11.7.3 NOKIA Big Data & Machine Learning in Telecom Introduction
11.7.4 NOKIA Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.7.5 NOKIA Recent Development
11.8 Openwave mobility
11.8.1 Openwave mobility Company Detail
11.8.2 Openwave mobility Business Overview
11.8.3 Openwave mobility Big Data & Machine Learning in Telecom Introduction
11.8.4 Openwave mobility Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.8.5 Openwave mobility Recent Development
11.9 Procera networks
11.9.1 Procera networks Company Detail
11.9.2 Procera networks Business Overview
11.9.3 Procera networks Big Data & Machine Learning in Telecom Introduction
11.9.4 Procera networks Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.9.5 Procera networks Recent Development
11.10 Qualcomm
11.10.1 Qualcomm Company Detail
11.10.2 Qualcomm Business Overview
11.10.3 Qualcomm Big Data & Machine Learning in Telecom Introduction
11.10.4 Qualcomm Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.10.5 Qualcomm Recent Development
11.11 ZTE
11.11.1 ZTE Company Detail
11.11.2 ZTE Business Overview
11.11.3 ZTE Big Data & Machine Learning in Telecom Introduction
11.11.4 ZTE Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.11.5 ZTE Recent Development
11.12 Google
11.12.1 Google Company Detail
11.12.2 Google Business Overview
11.12.3 Google Big Data & Machine Learning in Telecom Introduction
11.12.4 Google Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.12.5 Google Recent Development
11.13 AT&T
11.13.1 AT&T Company Detail
11.13.2 AT&T Business Overview
11.13.3 AT&T Big Data & Machine Learning in Telecom Introduction
11.13.4 AT&T Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.13.5 AT&T Recent Development
11.14 Apple
11.14.1 Apple Company Detail
11.14.2 Apple Business Overview
11.14.3 Apple Big Data & Machine Learning in Telecom Introduction
11.14.4 Apple Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.14.5 Apple Recent Development
11.15 Amazon
11.15.1 Amazon Company Detail
11.15.2 Amazon Business Overview
11.15.3 Amazon Big Data & Machine Learning in Telecom Introduction
11.15.4 Amazon Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.15.5 Amazon Recent Development
11.16 Microsoft
11.16.1 Microsoft Company Detail
11.16.2 Microsoft Business Overview
11.16.3 Microsoft Big Data & Machine Learning in Telecom Introduction
11.16.4 Microsoft Revenue in Big Data & Machine Learning in Telecom Business (2018-2023)
11.16.5 Microsoft Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

Companies Mentioned:

Allot
Argyle data
Ericsson
Guavus
HUAWEI
Intel
NOKIA
Openwave mobility
Procera networks
Qualcomm
ZTE
Google
AT&T
Apple
Amazon
Microsoft

License Types:

Single User License (PDF)

This license allows for use of a publication by one person.
This person may print out a single copy of the publication.
This person can include information given in the publication in presentations and internal reports by providing full copyright credit to the publisher.
This person cannot share the publication (or any information contained therein) with any other person or persons.
Unless a Enterprise License is purchased, a Single User License must be purchased for every person that wishes to use the publication within the same organization.
Customers who infringe these license terms are liable for a Global license fee.

听

Site License (PDF)*

This license allows for use of a publication by all users within one corporate location, e.g. a regional office.
These users may print out a single copy of the publication.
These users can include information given in the publication in presentations and internal reports by providing full copyright credit to the publisher.
These users cannot share the publication (or any information contained therein) with any other person or persons outside the corporate location for which the publication is purchased.
Unless a Enterprise License is purchased, a Site User License must be purchased for every corporate location by an organization that wishes to use the publication within the same organization.
Customers who infringe these license terms are liable for a Global license fee.

听

Global License (PDF)*

This license allows for use of a publication by unlimited users within the purchasing organization e.g. all employees of a single company.
Each of these people may use the publication on any computer, and may print out the report, but may not share the publication (or any information contained therein) with any other person or persons outside of the organization.
These employees of purchasing organization can include information given in the publication in presentations and internal reports by providing full copyright credit to the publisher.

*If Applicable.