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Telecom Carrier Big Data Operations, Applications, and Services

  • October 2015
  • -
  • Mind Commerce Publishing
  • -
  • 59 pages

Overview:

Telcos have a major advantage in that they have many sources of data but if they want to monetize that data and derive meaningful, actionable analytics it could be challenging due to the complexities of correlation, prediction, and the massive volumes of data from different sources. Identifying and leveraging available data sources, especially for external and commercial interests is an important matter. It is also a matter of trust while using Big Data technologies since data comes from customers who willingly provide their details.

All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Target Audience:
Regulatory and Policy Groups
Exporters, Importers and Traders
Business and Financial Institutions
Associations and Technology Groups
Corporate and Institutional Investors
Government and International Bodies
Lawyers, Bankers, Libraries, Embassies
Patent Offices and Technology Executives
Venture Capitalists, Consultants and more
Management Consulting and Advisory Firm

Table Of Contents

Telecom Carrier Big Data Operations, Applications, and Services
Table of Contents:

1.0 EXECUTIVE SUMMARY 4
2.0 INTRODUCTION 8
2.1 WHAT IS BIG DATA? 8
2.2 WHY IS BIG DATA IMPORTANT? 10
2.3 WHAT ABOUT ANALYTICS? 12
2.4 WHAT ABOUT BUSINESS INTELLIGENCE? 14
3.0 TELECOM AND BIG DATA 16
3.1 SOURCES OF BIG DATA IN TELECOM 16
3.2 TELECOM A KEY SOURCE OF ANALYTICS 20
3.3 ENTERPRISE BENEFITS FROM TELECOM BUSINESS INTELLIGENCE 23
4.0 CARRIERS AND BIG DATA 28
4.1 CARRIER BIG DATA STRENGTHS 28
4.1.1 MANY DATA CAPTURE SOURCES 28
4.1.2 CARRIERS ARE TRUSTED ENTITIES 30
4.2 CARRIER BIG DATA WEAKNESSES 31
4.2.1 NOT GOOD AT ORGANIC APP DEVELOPMENT 31
4.2.2 NEED HELP IDENTIFYING ENTERPRISE SOLUTIONS 32
5.0 NEW TELECOM BIG DATA APPLICATIONS AND SCENARIOS 35
5.1 FRAUD DETECTION AND PREVENTION 35
5.2 SUPPORT FOR MARKETING AND SALES 38
5.3 MOBILE LOCAL SOCIAL COMMERCE 40
5.4 PUBLIC SAFETY AND LAW ENFORCEMENT 42
6.0 THE FUTURE OF BIG DATA DRIVEN APPLICATIONS 44
6.1 TECHNOLOGY VS. SOCIAL ACCEPTANCE 44
6.1.1 PRIVACY AND SECURITY ISSUES 44
6.1.2 ANONYMIZING DATA IS NOT ENOUGH 47
6.2 ECOSYSTEM EVOLUTION 48
6.2.1 THE NEED FOR DATA MEDIATORS/BROKERS 48
6.2.2 THE NEED FOR ENTERPRISE INVOLVEMENT 50
6.3 THE ONGOING ROLE OF THE CARRIER 52
6.3.1 CARRIER INTERNAL USE OF BIG DATA 52
6.3.2 CARRIER TWO-SIDED BUSINESS MODEL 53
7.0 CONCLUSIONS AND RECOMMENDATIONS 56
7.1 CONCLUSIONS 56
7.2 RECOMMENDATIONS 57

Figures

Figure 1: Worldwide Quantity of Data 2009 - 2020 8
Figure 2: Cost of Data Management 2005 - 2015 9
Figure 3: BI, Big Data and Analytics 12
Figure 4: Structured Data Sources in Telecom 19
Figure 5: Unstructured (Big) Data Sources in Telecom 19

Tables

Table 1: Big Data-Internal Data Sources and Elements 19
Table 2: Big Data Operational Sources 20
Table 3: Data Analysis Areas and Benefits 25

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