Now-a-days, a trend is fast catching on as how telecom big data is being increasingly harnessed in disease control thereby bettering healthcare system. Various ways and methods are being employed to harness telecom big data in this direction. Recently, various studies and instances (in which telecom big data has been used in preventing the epidemic) came to the fore substantiating the claims. For example, such an episode came into the light when telecom big data was used to stem the spread of the Chikungunya virus in the Caribbean. United Nations Economic Commission for Latin America and the Caribbean (ECLAC) recently published report titled An assessment of big data for official statistics in the Caribbean in which it noted that the use of big data through geospatial (or location) of mobiles was used to support healthcare, and to design measures to tackle the eruption of Chikungunya transversing the region. KEY QUESTIONS ANSWERED 1. What is the current state of the global big data market? 2. Why big data management and utilisation is quickly turning to... Research Beam Model: Research Beam Product ID: 647686 3995 USD New
Worldwide Mobile Big Data Market 2016-2020
 
 

Worldwide Mobile Big Data Market 2016-2020

  • Category : ICT & Media
  • Published On : March   2016
  • Pages : 120+
  • Publisher : Tele Research Labs
 
 
 
Now-a-days, a trend is fast catching on as how telecom big data is being increasingly harnessed in disease control thereby bettering healthcare system. Various ways and methods are being employed to harness telecom big data in this direction. Recently, various studies and instances (in which telecom big data has been used in preventing the epidemic) came to the fore substantiating the claims. For example, such an episode came into the light when telecom big data was used to stem the spread of the Chikungunya virus in the Caribbean.

United Nations Economic Commission for Latin America and the Caribbean (ECLAC) recently published report titled An assessment of big data for official statistics in the Caribbean in which it noted that the use of big data through geospatial (or location) of mobiles was used to support healthcare, and to design measures to tackle the eruption of Chikungunya transversing the region.

KEY QUESTIONS ANSWERED

1. What is the current state of the global big data market?
2. Why big data management and utilisation is quickly turning to be a prerequisite for operators?
3. How are big data explorations affecting the telecom market dynamics?
4. What are the various big data use cases for operators?
5. How is big data currently being used by telco operators?
6. How is big data helping operators to improve operational efficiency and generate new revenue streams?
7. Which operators have exhaustively planned/ executed big data strategies?
8. What are the key advantages operators hold vis-à-vis big data?
9. How to identify the business problems that big data can solve?
10. How big data can be explored to create multiple fresh and innovative revenue streams?
11. Which operators are the pioneers/ leading in big data monetisation?
12. Who should develop in house and who should outsource?
13. What should be the criterion for big as well as small operators for vendor differentiation and assessment?
14. What are the recent developments vis-à-vis big data products and services?
15. What are the telcos’ best practices in big data?
16. Who are the top telco-focused big data vendors?
1 PROLOGUE: A FRESH PERSPECTIVE FOR BIG DATA

2 BIG DATA: SIMPLIFIED TECHNICAL CONCEPTS, MARKET DRIVERS, CHALLENGES, VALUE CREATION, RISK ASSESSMENT AND INVESTMENT PRIORITIES

2.1 Prime reasons for telcos to explore big data
2.1.1 Market saturation slowing conventional growth prospects
2.1.2 ARPU is continuously falling
2.1.3 Telcos need to preserve existing revenue sources
2.1.4 Overcoming churn
2.1.5 Declining profitability from mobile data business: Dumb pipe scenario
2.1.6 OTTs are hurting telcos’ business bottom lines
2.1.7 Telcos continuously losing their relevance in the value chain
2.1.8 Telcos need to add new business and create new sources of revenue
2.2 Telecom perspective on Big Data
2.3 Gauzing Big data strength of telco operators
2.4 Big data monetisation challenges for telco operators
2.5 Advanced analytics and big Data can create big business value

3 BIG DATA: MODERN BUSINESS USE CASES, ANALYSIS & DECISION MAKING

3.1 Big data Innovative Business models
3.1.1 Enhanced API Enablement and NextGen VAS
3.1.2 Explore transaction data for boosting sales
3.2 Leverage Big Data for Precision Marketing
3.2.1 Offer Optimisation at Individual level
3.2.2 Enhanced Churn Prediction and Prevention
3.2.3 Profitable Product Packaging for Specific OTT
3.3 Improved Operational Efficiency
3.3.1 Smart and pre-emptive Customer care
3.3.2 Intelligent Network Planning and monetisation
3.3.3 Cell-Site Optimisation
3.3.4 Subscriber-Centric Wireless Offloading
3.4 Real Time Network and Subscriber Intelligence
3.4.1 Enhanced prediction and management of temporary/ sudden Network Congestion
3.4.2 Enable Location Based and Personalized Advertising
3.4.3 Social Media and Sentiment Analysis
3.5 Quality of service (QoS) enhancement
3.5.1 Dynamic Subscriber Profiling and Segmentation

4 WORLDWIDE SIGNIFICANT TELCO CASE STUDIES: PROJECTS, EVOLUTION, TIMELINES AND FUTURE STRATEGIES

4.1 Verizon’s Precision Market Insights
4.2 Telefonica Dynamic Insights
4.3 Weve, O2
4.4 China Mobile Guangdong billing and customer service.
4.5 LIVE Singapore!
4.6 Singtel’s DataSpark

5 TOP TELCO-FOCUSED BIG DATA VENDORS: PROFILE, MARKET POSITIONING, INVESTMENTS AND SOLUTIONS

5.1 Accenture
5.2 Argyle Data
5.3 Capgemini
5.4 Cloudera
5.5 CSC
5.6 Ericsson
5.7 Hewlett-Packard (HP)
5.8 Huawei
5.9 IBM
5.10 Microsoft
5.11 Nokia Networks
5.12 Platfora
5.13 SAP
5.14 TIBCO

6 GLOBAL BIG DATA MARKET FORECAST 2015-2020

6.1 Europe
6.2 North America
6.3 Latin America
6.4 Asia-Pacific
6.5 Middle East & Africa Big Data Best Practices & Recommendations for Telco Operators

7 BIG DATA BEST PRACTICES & RECOMMENDATIONS FOR TELCO OPERATORS

7.1 Setting investment priorities for Big Data
7.2 Network Optimization & multilayer Monetization
7.3 Subscriber Insight data & Personalized Services
7.4 Mobile Advertising and LBS
7.5 Data Risks and Regulations are highly crucial

LIST OF FIGURES

Figure 1 Levels of big data operator
Figure 2 Shift in telecom market leadership & competition
Figure 3 ARPU per year in (In US$), 2015
Figure 4 Global Voice & Messaging Revenues Lost to OTT applications (In US$ Billion), 2014-2020
Figure 5 Global Voice Revenue (In US$ Billion), 2012-2014
Figure 6 Global Voice Revenue by Region (In US$ Billion), 2012-2014
Figure 7 Global SMS Revenue (In US$ Billion), 2012-2014
Figure 8 Global SMS Revenue by Region (In US$ Billion), 2012- 2014
Figure 9 Common telco data sources and information
Figure 10 Formulating steps to use big data
Figure 11 The progression to next-generation customer analytics
Figure 12 Global big data revenue forecasts (In US$ Million), 2016-2020
Figure 13 North America big data revenue forecasts (In US$ Million), 2016-2020
Figure 14 Europe big data revenue forecasts (In US$ Million), 2016-2020
Figure 15 Latin America big data revenue forecasts (In US$ Million), 2016-2020
Figure 16 Asia-Pacific big data revenue forecasts (In US$ Million), 2016-2020
Figure 17 Middle East & Africa big data
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