The prime objective of this report is to help the user understand the market in terms of its definition, segmentation, market potential, influential trends, and the challenges that the market is facing with 10 major regions and 30 major countries.
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 market research includes historical and forecast market data, demand, application details, price trends, and company shares of the leading Big Data and Machine Learning in Telecom by geography. The report splits the market size, by volume and value, on the basis of application type and geography.
The report forecast global Big Data and Machine Learning in Telecom market to grow to reach xxx Million USD in 2020 with a CAGR of xx% during the period 2021-2027.
Note – In order to provide more accurate market forecast, all our reports will be updated before delivery by considering the impact of COVID-19.
First, this report covers the present status and the future prospects of the global Big Data and Machine Learning in Telecom market for 2015-2027.
Key Companies
Allot
Argyle data
Ericsson
Guavus
HUAWEI
Intel
NOKIA
Openwave mobility
Procera networks
Qualcomm
ZTE
Google
AT&T
Apple
Amazon
Microsoft
At the same time, we classify Big Data and Machine Learning in Telecom according to the type, application by geography. More importantly, the report includes major countries market based on the type and application.
Market by Order Type
Descriptive analytics
Predictive analytics
Machine learning
Feature engineering
Market by Application
Processing
Storage
Analyzing
Market Segment as follows:
By Region
Asia-Pacific[China, Southeast Asia, India, Japan, Korea, Western Asia]
Europe[Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
North America[United States, Canada, Mexico]
Middle East & Africa[GCC, North Africa, South Africa]
South America[Brazil, Argentina, Columbia, Chile, Peru]
The research provides answers to the following key questions:
• What is the estimated growth rate and market share and size of the Big Data and Machine Learning in Telecom market for the forecast period 2021 - 2027?
• What are the driving forces in the Big Data and Machine Learning in Telecom market for the forecast period 2021 - 2027?
• Who are the prominent market players and how have they gained a competitive edge over other competitors?
• What are the market trends influencing the progress of the Big Data and Machine Learning in Telecom industry worldwide?
• What are the major challenges and threats restricting the progress of the industry?
• What opportunities does the market hold for the prominent market players?
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