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巨量資料

市場調查報告書

商品編碼

1755191

電信市場巨量資料分析機會、成長動力、產業趨勢分析及 2025 - 2034 年預測

Big Data Analytics in Telecom Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034

出版日期: 2025年05月20日 | 出版商:

Global Market Insights Inc. | 英文 185 Pages | 商品交期: 2-3個工作天內

價格

簡介目錄

2024年，全球電信巨量資料分析市場規模達36億美元，預計2034年將以18.3%的複合年成長率成長，達到190億美元。受資料驅動業務決策的驅動，對即時分析的需求日益成長。電信公司日益需要分析大量客戶和網路資料，以提高網路效率、改善客戶體驗並制定數據驅動的策略決策，這推動了這一成長。歐盟委員會旨在提高數位素養和互聯互通水準的「數位十年」計劃，也推動了對電信基礎設施高級分析的需求。

隨著電信網路不斷擴展以滿足智慧城市和物聯網 (IoT) 日益成長的需求，對預測和即時分析的需求也日益重要。電信業者依靠這些先進的分析技術來提升網路效能、最佳化資源配置，並確保跨多個平台的無縫用戶體驗。在快速發展的電信產業中，能夠預測並及時解決潛在的服務中斷問題，從而在客戶受到影響之前，是保持競爭優勢的關鍵因素。即時資料分析使營運商能夠監控網路流量、識別問題並立即實施糾正措施，從而確保高品質的服務交付和更高的客戶滿意度。

市場範圍
起始年份	2024
預測年份	2025-2034
起始值	36億美元
預測值	190億美元
複合年成長率	18.3%

2024年，解決方案部門佔據了55%的市場佔有率，預計到2034年將創造105億美元的收入。解決方案部門包括資料管理工具、分析軟體、資料視覺化平台和報告系統，幫助電信業者從其龐大的資料集中獲得寶貴的洞察。這些平台使營運商能夠即時監控網路效能，預測和預防網路中斷，並改善客戶分析。基於雲端的分析解決方案的日益普及進一步支持了這項擴展，幫助電信公司降低營運成本，同時改善服務交付。

大型企業在2024年佔了78%的市場。各大電信巨頭利用巨量資料分析來管理龐大的客戶群、複雜的網路基礎設施並提供卓越的服務。透過利用預測分析，這些大型公司可以預測網路擁塞、中斷或其他問題，並採取主動措施避免服務中斷。這種預測能力，加上即時分析大量資料的能力，使電信業者能夠做出明智的、數據驅動的策略決策。

2024年，美國電信市場巨量資料分析創收9億美元。憑藉成熟的電信基礎設施和對資料分析的大量投資，美國將繼續在該領域佔據主導地位。美國消費者的高資料消費水準催生了對分析解決方案的強烈需求，這些解決方案使電信公司能夠更好地了解客戶行為、減少客戶流失並提供個人化服務。美國的電信業者正在利用巨量資料分析提供客製化服務套餐，提升顧客滿意度並培養忠誠度。

電信市場巨量資料分析的主要參與者包括埃森哲、亞馬遜網路服務 (AWS)、ATOS、Alphabet、IBM、華為技術、微軟、甲骨文、SAP 和騰訊。為了鞏固市場地位，電信業大巨量資料分析公司正專注於透過採用高階分析功能來擴展其服務產品。這些參與者正在整合基於雲端的分析解決方案，以提供可擴展、經濟高效的服務，以滿足日益成長的即時資料處理需求。他們還利用人工智慧和機器學習技術提供更準確的預測見解，使電信業者能夠最佳化網路效能、防止停機並增強客戶體驗。與電信業者的策略合作夥伴關係也幫助這些公司獲得有價值的資料，而研發投資使他們能夠開發出滿足電信業不斷變化的需求的創新解決方案。

產業生態系統分析
- 供應商格局
  - 雲端平台提供者
  - 數據整合和管理提供商
  - 分析解決方案提供商
  - 應用程式提供者
  - 最終用戶
- 利潤率分析。
川普政府關稅的影響
- 對貿易的影響
  - 貿易量中斷
  - 報復措施
- 對產業的影響
  - 供應方影響（原料）
    - 主要材料價格波動
    - 供應鏈重組。
    - 生產成本影響
  - 需求面影響（售價）
    - 價格傳輸至終端市場。
    - 市佔率動態
    - 消費者反應模式
- 策略產業反應
  - 供應鏈重組。
定價和產品策略
技術與創新格局
- 當前的技術趨勢
  - 人工智慧驅動的網路最佳化
  - 支援5G的邊緣運算
  - 電信雲端編排和自動化
- 新興技術
  - 用於電信分析的量子計算
  - 整合AI的6G網路
  - 區塊鏈驅動的網路安全
  - 智慧虛擬網路功能
- 先進材料科學
定價策略
專利分析
用例。
重要新聞和舉措
監管格局
對部隊的影響
- 成長動力
  - 高速資料處理能力
  - 先進的網路最佳化技術
  - 即時分析以增強客戶體驗
  - 與新興科技（AI、IoT、5G）的融合
- 產業陷阱與挑戰
  - 基礎設施和維護成本高
  - 資料整合和管理的複雜性
成長潛力分析
波特的分析
PESTEL分析

第4章：競爭格局

介紹
公司市佔率分析
競爭定位矩陣
戰略展望矩陣

第5章：市場估計與預測：按組件，2021 - 2034 年

主要趨勢
解決方案
- 資料管理
- 分析軟體
- 數據視覺化
- 報告工具
- 其他
服務
- 專業服務
- 託管服務
- 諮詢與培訓

第6章：市場估計與預測：按分析，2021 - 2034 年

主要趨勢
描述性分析
診斷分析
預測分析
規範分析

第7章：市場估計與預測：依組織規模，2021 - 2034 年

主要趨勢
中小型企業（SME）
大型企業

第8章：市場估計與預測：按部署，2021 - 2034 年

主要趨勢
本地
基於雲端
- 公共雲端
- 私有雲端
- 混合雲端

第9章：市場估計與預測：按應用，2021 - 2034 年

主要趨勢
客戶分析
- 客戶流失預測
- 客戶終身價值分析
- 客戶區隔
網路分析
- 網路最佳化
- 故障管理
- 交通管理
營運分析
- 資源最佳化
- 流程自動化
市場分析
- 行銷活動管理
- 社群媒體分析
收入分析
- 詐欺偵測
- 收入保障
其他

第10章：市場估計與預測：依最終用途，2021 - 2034 年

主要趨勢
電信服務供應商
網際網路服務供應商 (ISP)
行動虛擬網路營運商（MVNO）
其他

第 11 章：市場估計與預測：按地區，2021 年至 2034 年

北美洲
- 美國
- 加拿大
歐洲
- 英國
- 德國
- 法國
- 義大利
- 西班牙
- 比利時
- 瑞典
亞太地區
- 中國
- 印度
- 日本
- 澳洲
- 新加坡
- 韓國
- 東南亞
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
MEA
- 南非
- 沙烏地阿拉伯
- 阿拉伯聯合大公國

第12章：公司簡介

Accenture
Alibaba
Alphabet
Altair Engineering
Amazon Web Services (AWS)
ATOS SE
Databricks
Hewlett Packard Enterprise Development
Huawei Technologies
IBM
Informatica
Infosys
L&T
Microsoft
Oracle
SAP
Snowflake
TATA Consultancy Services
Tencent
Wipro

簡介目錄

Product Code: 13936

The Global Big Data Analytics in Telecom Market was valued at USD 3.6 billion in 2024 and is estimated to grow at a CAGR of 18.3% to reach USD 19 billion by 2034, driven by the dependency on data to drive business decisions, the demand for real-time analytics is growing. This expansion is fueled by the increasing need for telecom companies to analyze massive amounts of customer and network data to enhance network efficiencies, improve customer experience, and make data-driven strategic decisions. The European Commission's Digital Decade initiative, aiming to increase digital literacy and connectivity, is also driving the demand for advanced analytics in telecom infrastructure.

Big Data Analytics in Telecom Market - IMG1

As telecom networks expand to accommodate the growing demands of smart cities and the Internet of Things (IoT), the need for predictive and real-time analytics has become increasingly essential. Telecom operators are relying on these advanced analytics to enhance network performance, optimize resource allocation, and ensure seamless user experience across multiple platforms. The ability to predict and address potential service disruptions before they impact customers is a key factor in maintaining a competitive edge in the rapidly evolving telecom landscape. Real-time data analytics allow operators to monitor network traffic, identify issues, and implement corrective measures instantly, ensuring high-quality service delivery and greater customer satisfaction.

Market Scope
Start Year	2024
Forecast Year	2025-2034
Start Value	$3.6 Billion
Forecast Value	$19 Billion
CAGR	18.3%

In 2024, the solutions segment dominated the market with a 55% share, and it is expected to generate USD 10.5 billion in revenue by 2034. The solutions segment includes data management tools, analytics software, data visualization platforms, and reporting systems, which help telecom operators gain valuable insights from their vast data sets. These platforms enable operators to monitor network performance in real-time, predict and prevent network disruptions, and improve customer analytics. The growing adoption of cloud-based analytics solutions further supports this expansion, helping telecom companies reduce operational costs while improving service delivery.

The large enterprises segment accounted for a 78% share in 2024. Major telecom giants leverage big data analytics to handle vast customer bases, manage complex network infrastructures, and deliver superior services. By utilizing predictive analytics, these large companies can anticipate network congestion, outages, or other issues and take proactive measures to avoid service disruptions. This predictive capability, coupled with the ability to analyze large volumes of data in real time, enables telecom operators to make well-informed, data-driven strategic decisions.

U.S. Big Data Analytics in Telecom Market generated USD 900 million in 2024. The U.S. continues to be a dominant player in this space due to its established telecommunications infrastructure and significant investment in data analytics. High data consumption levels by consumers in the U.S. create a strong need for analytics solutions, allowing telecom companies to better understand customer behavior, reduce churn, and personalize services. Telecom operators in the U.S. are leveraging big data analytics to offer tailored service packages, enhance customer satisfaction, and foster loyalty.

Major players in the Big Data Analytics in Telecom Market include Accenture, Amazon Web Services (AWS), ATOS, Alphabet, IBM, Huawei Technologies, Microsoft, Oracle, SAP, and Tencent. To strengthen their market position, companies in big data analytics for the telecom sector are focusing on expanding their service offerings by adopting advanced analytics capabilities. These players are integrating cloud-based analytics solutions to offer scalable, cost-effective services that can handle the growing demand for real-time data processing. They are also leveraging AI and machine learning technologies to deliver more accurate predictive insights, allowing telecom operators to optimize network performance, prevent downtimes, and enhance customer experience. Strategic partnerships with telecom operators are also helping these companies access valuable data, while R&D investments are enabling them to develop innovative solutions that cater to the evolving needs of the telecommunications industry.

Chapter 1 Methodology & Scope

1.1 Research design
- 1.1.1 Research approach
- 1.1.2 Data collection methods
1.2 Base estimates & calculations
- 1.2.1 Base year calculation
- 1.2.2 Key trends for market estimation
1.3 Forecast model.
1.4 Primary research and validation
- 1.4.1 Primary sources
- 1.4.2 Data mining sources
1.5 Market scope & definition

Chapter 2 Executive Summary

2.1 Industry synopsis, 2021 - 2034

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
- 3.1.1 Supplier landscape
  - 3.1.1.1 Cloud platform providers
  - 3.1.1.2 Data integration and management providers
  - 3.1.1.3 Analytics solution providers
  - 3.1.1.4 Application provider
  - 3.1.1.5 End users
- 3.1.2 Profit margin analysis.
3.2 Impact of Trump administration tariffs
- 3.2.1 Impact on trade
  - 3.2.1.1 Trade volume disruptions
  - 3.2.1.2 Retaliatory measures
- 3.2.2 Impact on industry
  - 3.2.2.1 Supply-side impact (raw materials)
    - 3.2.2.1.1 Price volatility in key materials
    - 3.2.2.1.2 Supply chain restructuring.
    - 3.2.2.1.3 Production cost implications
  - 3.2.2.2 Demand-side impact (selling price)
    - 3.2.2.2.1 Price transmission to end markets.
    - 3.2.2.2.2 Market share dynamics
    - 3.2.2.2.3 Consumer response patterns
- 3.2.3 Strategic industry responses
  - 3.2.3.1 Supply chain reconfiguration.
3.3 Pricing and product strategies
3.4 Technology & innovation landscape
- 3.4.1 Current technological trends
  - 3.4.1.1 AI-powered network optimization
  - 3.4.1.2 5G-enabled edge computing
  - 3.4.1.3 Telecom cloud orchestration and automation
- 3.4.2 Emerging Technologies
  - 3.4.2.1 Quantum computing for telecom analytics
  - 3.4.2.2 6G networks with AI integration
  - 3.4.2.3 Blockchain-driven network security
  - 3.4.2.4 Intelligent virtual network functions
- 3.4.3 Advanced material sciences
3.5 Pricing strategies
3.6 Patent analysis
3.7 Use cases.
3.8 Key news & initiatives
3.9 Regulatory landscape
3.10 Impact on forces
- 3.10.1 Growth drivers
  - 3.10.1.1 High-speed data processing capabilities
  - 3.10.1.2 Advanced network optimization techniques
  - 3.10.1.3 Real-time analytics for enhanced customer experience
  - 3.10.1.4 Integration with emerging technologies (AI, IoT, 5G)
- 3.10.2 Industry pitfalls & challenges
  - 3.10.2.1 High infrastructure and maintenance costs
  - 3.10.2.2 Complexity of data integration and management
3.11 Growth potential analysis
3.12 Porter's analysis
3.13 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

5.1 Key trends
5.2 Solution
- 5.2.1 Data management
- 5.2.2 Analytics software
- 5.2.3 Data visualization
- 5.2.4 Reporting tools
- 5.2.5 Others
5.3 Services
- 5.3.1 Professional services
- 5.3.2 Managed services
- 5.3.3 Consulting & training

Chapter 6 Market Estimates & Forecast, By Analytics, 2021 - 2034 ($Bn)

6.1 Key trends
6.2 Descriptive analytics
6.3 Diagnostic analytics
6.4 Predictive analytics
6.5 Prescriptive analytics

Chapter 7 Market Estimates & Forecast, By Organization Size, 2021 - 2034 ($Bn)

7.1 Key trends
7.2 Small & medium-sized enterprises (SME)
7.3 Large Enterprises

Chapter 8 Market Estimates & Forecast, By Deployment, 2021 - 2034 ($Bn)

8.1 Key trends
8.2 On-premises
8.3 Cloud-based
- 8.3.1 Public cloud
- 8.3.2 Private cloud
- 8.3.3 Hybrid cloud

Chapter 9 Market Estimates & Forecast, By Application, 2021 - 2034 ($Bn)

9.1 Key trends
9.2 Customer analysis
- 9.2.1 Customer churn prediction
- 9.2.2 Customer lifetime value analysis
- 9.2.3 Customer segmentation
9.3 Network analysis
- 9.3.1 Network optimization
- 9.3.2 Fault management
- 9.3.3 Traffic management
9.4 Operational analysis
- 9.4.1 Resource optimization
- 9.4.2 Process automation
9.5 Marketing analysis
- 9.5.1 Campaign management
- 9.5.2 Social media analytics
9.6 Revenue analysis
- 9.6.1 Fraud detection
- 9.6.2 Revenue assuranc
9.7 Others

Chapter 10 Market Estimates & Forecast, By End Use, 2021 - 2034 ($Bn)

10.1 Key trends
10.2 Telecom service providers
10.3 Internet service providers (ISPs)
10.4 Mobile virtual network operators (MVNOs)
10.5 Others

Chapter 11 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn)

11.1 North America
- 11.1.1 U.S.
- 11.1.2 Canada
11.2 Europe
- 11.2.1 UK
- 11.2.2 Germany
- 11.2.3 France
- 11.2.4 Italy
- 11.2.5 Spain
- 11.2.6 Belgium
- 11.2.7 Sweden
11.3 Asia Pacific
- 11.3.1 China
- 11.3.2 India
- 11.3.3 Japan
- 11.3.4 Australia
- 11.3.5 Singapore
- 11.3.6 South Korea
- 11.3.7 Southeast Asia
11.4 Latin America
- 11.4.1 Brazil
- 11.4.2 Mexico
- 11.4.3 Argentina
11.5 MEA
- 11.5.1 South Africa
- 11.5.2 Saudi Arabia
- 11.5.3 UAE