Table of Content


1 Executive Summary
2 Big Data in Telecom Analytics
2.1 Telecom Analytics Market 2015 - 2020
2.2 Improving Subscriber Experience
2.2.1 Generating a Full Spectrum View of the Subscriber
2.2.2 Creating Customized Experiences and Targeted Promotions
2.2.3 Central Big Data Repository: Key to Customer Satisfaction
2.2.4 Reduce Costs and Increase Market Share
2.3 Building Smarter Networks
2.3.1 Understanding Network Utilization
2.3.2 Improving Network Quality and Coverage
2.3.3 Combining Telecom Data with Public Data Sets: Real-Time Event Management
2.3.4 Leveraging M2M for Telecom Analytics
2.3.5 M2M, Deep Packet Inspection and Big Data: Identifying & Fixing Network Defects
2.4 Churn/Risk Reduction and New Revenue Streams
2.4.1 Predictive Analytics
2.4.2 Identifying Fraud and Bandwidth Theft
2.4.3 Creating New Revenue Streams
2.5 Telecom Analytics Case Studies
2.5.1 T-Mobile USA: Churn Reduction by 50%
2.5.2 Vodafone: Using Telco Analytics to Enable Navigation
2.6 Carriers, Analytics, and Data as a Service (DaaS)
2.6.1 Carrier Data Management Operational Strategies
2.6.2 Network vs. Subscriber Analytics
2.6.3 Data and Analytics Opportunities to Third Parties
2.6.4 Carriers to offer Data as s Service (DaaS) on B2B Basis
2.6.5 DaaS Planning and Strategies
2.6.6 Carrier Monetization of Data with DaaS
2.7 Opportunities for Carriers in Cloud Analytics
2.7.1 Carrier NFV and Cloud Analytics
2.7.2 Carrier Cloud OSS/BSS Analytics
2.7.3 Carrier Cloud Services, Data, and Analytics
2.7.4 Carrier Performance Management and the Cloud Analytics
3 Structured Data in Telecom Analytics
3.1 Telecom Data Sources and Repositories
3.1.1 Subscriber Data
3.1.2 Subscriber Presence and Location Data
3.1.3 Business Data: Toll-free and other Directory Services
3.1.4 Network Data: Deriving Data from Network Operations
3.2 Telecom Data Mining
3.2.1 Data Sources: Rating, Charging, and Billing Examples
3.2.2 Privacy Issues
3.3 Telecom Database Services
3.3.1 Calling Name Identity
3.3.2 Subscriber Data Management (SDM) Services
3.3.3 Other Data-intensive Service Areas
3.3.4 Emerging Service Area: Identity Verification
3.4 Structured Telecom Data Analytics
3.4.1 Dealing with Telecom Data Fragmentation
3.4.2 Deep Packet Inspection
4 Summary and Recommendations

Figure 1: Telco Analytics Investments Driven by Big Data: 2015 – 2020
Figure 2: Different Data Types within Telco Environment
Figure 3: Presence-enabled Application
Figure 4: Calling Name (CNAM) Service Operation
Figure 5: Subscriber Data Management (SDM) Ecosystem
Figure 6: Data Fragmented across Telecom Databases
Figure 7: Telecom Deep Packet Inspection Revenue 2015 - 2020
Figure 8: Telecom Data and Third-party Applications
Figure 9: Telecom Data, Cloud, and Third-party Applications