Telecom Operators Turn To Real-Time Analytics For Enhanced Network Performance And Customer Satisfaction

(MENAFN- GlobeNewsWire - Nasdaq) Growth in the Big Data Analytics in Telecom Market is driven by telecom operators' need for real-time analytics to enhance network efficiency and customer experience. The European Commission's Digital Decade initiative further propels demand for advanced analytics. Dominated by the solutions segment, the market leverages data management tools and cloud-based platforms. Key players like AWS and IBM focus on AI and machine learning for predictive insights.

Dublin, Sept. 23, 2025 (GLOBE NEWSWIRE) -- The "Big Data Analytics in Telecom Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025-2034" report has been added to ResearchAndMarkets's offering.
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.

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.
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.
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.
Comprehensive Market Analysis and Forecast

• Industry trends, key growth drivers, challenges, future opportunities, and regulatory landscape
• Competitive landscape with Porter's Five Forces and PESTEL analysis
• Market size, segmentation, and regional forecasts
• In-depth company profiles, business strategies, financial insights, and SWOT analysis
  • 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

Key Attributes:

Report Attribute	Details
No. of Pages	185
Forecast Period	2024 - 2034
Estimated Market Value (USD) in 2024	$3.6 Billion
Forecasted Market Value (USD) by 2034	$19 Billion
Compound Annual Growth Rate	18.3%
Regions Covered	Global

Key Topics Covered:
Chapter 1 Methodology & Scope
Chapter 2 Executive Summary
2.1 Industry synopsis, 2021-2034
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Impact of Trump administration tariffs
3.3 Pricing and product strategies
3.4 Technology & innovation landscape
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
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
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
7.1 Key trends
7.2 Small & medium-sized enterprises (SME)
7.3 Large Enterprises
Chapter 8 Market Estimates & Forecast, by Deployment, 2021-2034
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
9.1 Key trends
9.1.1.1 Customer analysis
9.1.1.1.1 Customer churn prediction
9.1.1.1.2 Customer lifetime value analysis
9.1.1.1.3 Customer segmentation
9.1.1.2 Network analysis
9.1.1.2.1 Network optimization
9.1.1.2.2 Fault management
9.1.1.2.3 Traffic management
9.1.1.3 Operational analysis
9.1.1.3.1 Resource optimization
9.1.1.3.2 Process automation
9.1.1.4 Marketing analysis
9.1.1.4.1 Campaign management
9.1.1.4.2 Social media analytics
9.1.1.5 Revenue analysis
9.1.1.5.1 Fraud detection
9.1.1.5.2 Revenue assurance
9.1.2 Others
Chapter 10 Market Estimates & Forecast, by End Use, 2021-2034
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
Chapter 12 Company Profiles
12.1 Accenture
12.2 Alibaba
12.3 Alphabet
12.4 Altair Engineering
12.5 Amazon Web Services (AWS)
12.6 ATOS SE
12.7 Databricks
12.8 Hewlett Packard Enterprise Development
12.9 Huawei Technologies
12.10 IBM
12.11 Informatica
12.12 Infosys
12.13 L&T
12.14 Microsoft
12.15 Oracle
12.16 SAP
12.17 Snowflake
12.18 TATA Consultancy Services
12.19 Tencent
12.20 Wipro
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• Big Data Analytics in Telecom Market

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