Global Big Data & Machine Learning in Telecom Market 2024 by Company, Regions, Type and Application, Forecast to 2030

Global Big Data & Machine Learning in Telecom Market 2024 by Company, Regions, Type and Application, Forecast to 2030

According to our (Global Info Research) latest study, the global Big Data & Machine Learning in Telecom market size was valued at USD million in 2023 and is forecast to a readjusted size of USD million by 2030 with a CAGR of % during review period.

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 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.

The Global Info Research report includes an overview of the development of the Big Data & Machine Learning in Telecom industry chain, the market status of Processing (Descriptive Analytics, Predictive Analytics), Storage (Descriptive Analytics, Predictive Analytics), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Big Data & Machine Learning in Telecom.

Regionally, the report analyzes the Big Data & Machine Learning in Telecom markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Big Data & Machine Learning in Telecom market, with robust domestic demand, supportive policies, and a strong manufacturing base.

Key Features:

The report presents comprehensive understanding of the Big Data & Machine Learning in Telecom market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Big Data & Machine Learning in Telecom industry.

The report involves analyzing the market at a macro level:

Market Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., Descriptive Analytics, Predictive Analytics).

Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Big Data & Machine Learning in Telecom market.

Regional Analysis: The report involves examining the Big Data & Machine Learning in Telecom market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.

Market Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Big Data & Machine Learning in Telecom market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.

The report also involves a more granular approach to Big Data & Machine Learning in Telecom:

Company Analysis: Report covers individual Big Data & Machine Learning in Telecom players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.

Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Big Data & Machine Learning in Telecom This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Processing, Storage).

Technology Analysis: Report covers specific technologies relevant to Big Data & Machine Learning in Telecom. It assesses the current state, advancements, and potential future developments in Big Data & Machine Learning in Telecom areas.

Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Big Data & Machine Learning in Telecom market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.

Market Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.

Market Segmentation

Big Data & Machine Learning in Telecom market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.

Market segment by Type
Descriptive Analytics
Predictive Analytics
Machine Learning
Feature Engineering

Market segment by Application
Processing
Storage
Analyzing

Market segment by players, this report covers
Allot
Argyle data
Ericsson
Guavus
HUAWEI
Intel
NOKIA
Openwave mobility
Procera networks
Qualcomm
ZTE
Google
AT&T
Apple
Amazon
Microsoft

Market segment by regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Argentina and Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)

The content of the study subjects, includes a total of 13 chapters:

Chapter 1, to describe Big Data & Machine Learning in Telecom product scope, market overview, market estimation caveats and base year.

Chapter 2, to profile the top players of Big Data & Machine Learning in Telecom, with revenue, gross margin and global market share of Big Data & Machine Learning in Telecom from 2019 to 2024.

Chapter 3, the Big Data & Machine Learning in Telecom competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.

Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.

Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Big Data & Machine Learning in Telecom market forecast, by regions, type and application, with consumption value, from 2025 to 2030.

Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.

Chapter 12, the key raw materials and key suppliers, and industry chain of Big Data & Machine Learning in Telecom.

Chapter 13, to describe Big Data & Machine Learning in Telecom research findings and conclusion.