2026 Global: Big Data In Telecom Market -Competitive Review (2032) report
Description
The 2026 Global: Big Data In Telecom Market -Competitive Review (2031) report features the global market size and projected growth/decline data for the period 2021 through 2032. The report primarily provides an examination of the business strategies for the ten largest global companies in the market and how their strategies differ.
Perry/Hope Partners' reports provide the most accurate industry forecasts based on our proprietary economic models. Our forecasts project the product market size nationally and by regions for 2021 to 2032 using regression analysis in our modeling. and Perry/Hope is the only market research publisher that utilizes both longitudinal (historical) and vertical (from market section to market division to market class) analysis, since we study every manufactured product in the countries we analyze. The report also provides written analysis on the market definition, market segments, and SWOT analysis (market strengths, weaknesses, opportunities, and threats).
The market study aims at estimating the market size and the growth potential of this market. Topics analyzed within the report include a detailed breakdown of the global markets for big data in telecom market by geography and historical trend. The scope of the report extends to sizing of the big data in telecom market market and global market trends with market data for 2024 as the base year, 2025 and 2026 as the estimate years with projection of CAGR from 2027 to 2032.
The report also features a list of the top ten largest global players in the market. A review of each company includes 1) an estimate of the market share, 2) a listing of the products and/or services in the market, and 3) the features of these products and/or services in the market. The report has a chapter on Comparative Business Strategies for the largest four players. An example of the Comparative Business Strategies analysis would be -- How does Netflix's business strategy to expand its market share in the global online streaming compare to Amazon Prime's business strategy through its video products and services?
The ten market players in this report and a brief synopsis of their participation in the market are:
The Big Data in Telecom market is dominated by a mix of global cloud and analytics vendors, telecom-focused software firms, and systems integrators that provide data ingestion, real‑time streaming, AI/ML analytics, customer‑experience orchestration, and network analytics solutions. Amazon Web Services (AWS) offers managed big‑data services such as Amazon Redshift, Kinesis, EMR and SageMaker that telcos use for large‑scale event processing, streaming telemetry and ML model hosting at cloud scale. AWS also provides telco‑specific architectures and partner ecosystems for 5G‑edge deployments that accelerate operator analytics projects. Microsoft Azure supplies Azure Synapse, Data Explorer, Event Hubs and Azure ML that enable telco data lakes, high‑cardinality time‑series analytics and operational AI for network assurance and customer insights; Azure’s integrations with operator edge and private 5G offerings make it a major platform choice for telecom big‑data workloads. Google Cloud Platform (GCP) delivers BigQuery, Dataflow, Pub/Sub and Vertex AI used by carriers for petabyte‑scale analytics, near‑real‑time streaming analysis and ML‑driven use cases such as churn prediction, dynamic pricing and fraud detection; GCP’s investments in AI accelerators and telecom partnerships strengthen its role in operator data stacks.
Databricks provides a unified lakehouse platform that combines large‑scale data engineering, streaming and ML lifecycle management, which many service providers adopt to reduce ETL complexity and operationalize ML across network and customer domains. Snowflake’s cloud data platform is widely used by telcos for secure, shareable data lakes and cross‑organization analytics that support B2B services, roaming analytics and multi‑party revenue assurance; its cross‑cloud data sharing simplifies collaboration between operators and partners. Cisco offers network‑centric analytics through its network telemetry, streaming‑model collectors and AppDynamics for application and experience monitoring, enabling operators to correlate network events with service quality and automate remediation. Ericsson leverages its deep telco domain expertise to provide analytics for network optimization, OSS/BSS integration and AI‑driven automation, combining vendor‑grade network telemetry with advanced analytics targeted at 5G slice assurance and capacity planning.
IBM brings hybrid‑cloud analytics, streaming platforms and Watson AI to telecom customers for fraud prevention, customer‑experience analytics and workforce automation, often integrated with carriers’ legacy OSS environments. Accenture and Tata Consultancy Services (TCS) act as systems integrators and consultants that design end‑to‑end big‑data strategies, implement data pipelines and operationalize AI across billing, customer care and network operations for large operators worldwide. Splunk specializes in telecom observability and security analytics by ingesting machine data from network elements, CPE and cloud services to deliver real‑time diagnostics, incident correlation and SLA monitoring. Qualtrics and specialized vendors focused on customer‑experience analytics and QoE measurement round out the list by providing sentiment and quality analytics that feed into retention and monetization programs.
Perry/Hope Partners' reports provide the most accurate industry forecasts based on our proprietary economic models. Our forecasts project the product market size nationally and by regions for 2021 to 2032 using regression analysis in our modeling. and Perry/Hope is the only market research publisher that utilizes both longitudinal (historical) and vertical (from market section to market division to market class) analysis, since we study every manufactured product in the countries we analyze. The report also provides written analysis on the market definition, market segments, and SWOT analysis (market strengths, weaknesses, opportunities, and threats).
The market study aims at estimating the market size and the growth potential of this market. Topics analyzed within the report include a detailed breakdown of the global markets for big data in telecom market by geography and historical trend. The scope of the report extends to sizing of the big data in telecom market market and global market trends with market data for 2024 as the base year, 2025 and 2026 as the estimate years with projection of CAGR from 2027 to 2032.
The report also features a list of the top ten largest global players in the market. A review of each company includes 1) an estimate of the market share, 2) a listing of the products and/or services in the market, and 3) the features of these products and/or services in the market. The report has a chapter on Comparative Business Strategies for the largest four players. An example of the Comparative Business Strategies analysis would be -- How does Netflix's business strategy to expand its market share in the global online streaming compare to Amazon Prime's business strategy through its video products and services?
The ten market players in this report and a brief synopsis of their participation in the market are:
The Big Data in Telecom market is dominated by a mix of global cloud and analytics vendors, telecom-focused software firms, and systems integrators that provide data ingestion, real‑time streaming, AI/ML analytics, customer‑experience orchestration, and network analytics solutions. Amazon Web Services (AWS) offers managed big‑data services such as Amazon Redshift, Kinesis, EMR and SageMaker that telcos use for large‑scale event processing, streaming telemetry and ML model hosting at cloud scale. AWS also provides telco‑specific architectures and partner ecosystems for 5G‑edge deployments that accelerate operator analytics projects. Microsoft Azure supplies Azure Synapse, Data Explorer, Event Hubs and Azure ML that enable telco data lakes, high‑cardinality time‑series analytics and operational AI for network assurance and customer insights; Azure’s integrations with operator edge and private 5G offerings make it a major platform choice for telecom big‑data workloads. Google Cloud Platform (GCP) delivers BigQuery, Dataflow, Pub/Sub and Vertex AI used by carriers for petabyte‑scale analytics, near‑real‑time streaming analysis and ML‑driven use cases such as churn prediction, dynamic pricing and fraud detection; GCP’s investments in AI accelerators and telecom partnerships strengthen its role in operator data stacks.
Databricks provides a unified lakehouse platform that combines large‑scale data engineering, streaming and ML lifecycle management, which many service providers adopt to reduce ETL complexity and operationalize ML across network and customer domains. Snowflake’s cloud data platform is widely used by telcos for secure, shareable data lakes and cross‑organization analytics that support B2B services, roaming analytics and multi‑party revenue assurance; its cross‑cloud data sharing simplifies collaboration between operators and partners. Cisco offers network‑centric analytics through its network telemetry, streaming‑model collectors and AppDynamics for application and experience monitoring, enabling operators to correlate network events with service quality and automate remediation. Ericsson leverages its deep telco domain expertise to provide analytics for network optimization, OSS/BSS integration and AI‑driven automation, combining vendor‑grade network telemetry with advanced analytics targeted at 5G slice assurance and capacity planning.
IBM brings hybrid‑cloud analytics, streaming platforms and Watson AI to telecom customers for fraud prevention, customer‑experience analytics and workforce automation, often integrated with carriers’ legacy OSS environments. Accenture and Tata Consultancy Services (TCS) act as systems integrators and consultants that design end‑to‑end big‑data strategies, implement data pipelines and operationalize AI across billing, customer care and network operations for large operators worldwide. Splunk specializes in telecom observability and security analytics by ingesting machine data from network elements, CPE and cloud services to deliver real‑time diagnostics, incident correlation and SLA monitoring. Qualtrics and specialized vendors focused on customer‑experience analytics and QoE measurement round out the list by providing sentiment and quality analytics that feed into retention and monetization programs.
Table of Contents
32 Pages
- 1.0 Scope of Report and Methodology
- 2.0 Market SWOT Analysis and Players
- 2.1 Market Definition
- 2.2 Market Segments
- 2.3 Market Strengths
- 2.4 Market Weaknesses
- 2.5 Market Threats
- 2.6 Market Opportunities
- 2.7 Major Players
- 3.0 Competitive Analysis
- 3.1 Market Player 1
- 3.2 Market Player 2
- 3.3 Market Player 3
- 3.4 Market Player 4
- 3.5 Market Player 5
- 3.6 Market Player 6
- 3.7 Market Player 7
- 3.8 Market Player 8
- 3.9 Market Player 9
- 3.10 Market Player 10
- 4.0 Comparative Business Strategies
- 4.1 Comparative Business Strategies of Player 1 and 2
- 4.2 Comparative Business Strategies of Player 1 and 3
- 4.3 Comparative Business Strategies of Player 1 and 4
- 4.4 Comparative Business Strategies of Player 2 and 3
- 4.5 Comparative Business Strategies of Player 2 and 4
- 4.6 Comparative Business Strategies of Player 3 and 4
- 5.0 Appendix
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