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Overview:

Smart Cities are much more than just an effort by sovereign nations to modernize their infrastructure - they are a focal point for growth drivers in several key ICT areas including: M2M/IoT, Connected Devices, Broadband Wireless, Cloud Computing, Big Data and Analytics. Smart City developments are causing many technologies and solutions to integrate with convergence seen across with many resource areas including energy, water, sanitation, and other essential services.

Mind Commerce sees significant opportunities for global wireless carriers in Smart Cities, Homes, and Solutions in the areas of LTE-Advanced, M2M, IoT, Connected Devices, Big Data and Analytics as well as a vast number of applications. The importance of wireless carrier investment in Smart Cities and Homes cannot be understated. By way of example, our research indicates that a significant majority of IoT applications will occur within metropolitan areas and will ultimately integrate within a Smart City ecosystem. Our research indicates up to 15% of all carrier revenue will be dependent upon Smart Cities by 2019.

This research offering includes comprehensive analysis in all key areas for global wireless carriers including:

Smart City and Homes
LTE Advanced (LTE-A)
Big Data and Analytics
M2M Internet of Things
M2M/IoT Smart City Apps
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:

Global wireless carriers
Telecom equipment providers
Global infrastructure suppliers
Communications component providers
Cloud services and datacenter companies
Smartgrid and energy management companies
Sovereign investment funds, hedge funds and private
Big data, analytics, and information processing companies

Report Benefits:

Smart City and Smart Home forecasts
Market data for LTE-A, M2M, IoT, Big Data and Analytics
Identify Market opportunities for carriers in Smart Cities/Homes
Identify the market drivers for Smart Cities and Homes and impact on ICT
Understand the impact of Smart Cities/Homes on telecom services evolution
Understand the technologies and investment areas for supporting Smart Cities/Homes

Table Of Contents

Market Opportunities for Global Wireless Carriers in Smart Cities, Homes, and Solutions
Smart Cities: Global Outlook and Forecasts

1.0 EXECUTIVE SUMMARY 4
2.0 INTRODUCTION 5
2.1 WHAT IS SMART CITY 5
2.2 MARKET DRIVERS FOR SMART CITIES 8
2.3 SMART CITY SUPPORTING TECHNOLOGIES 9
3.0 SMART CITY PLANNING 15
3.1 URBAN DEVELOPMENT 15
3.2 UTILITIES AND SMART GRIDS 16
3.3 TELECOM INFRASTRUCTURE 17
4.0 SMART CITIES COMPANIES AND SOLUTIONS 19
4.1 ABB 19
4.2 ACCENTURE 21
4.3 ALCATEL LUCENT 22
4.4 CISCO SYSTEMS 23
4.5 CUBIC 24
4.6 HONEYWELL 24
4.7 IBM 25
4.8 INTEL 26
4.9 ORACLE 27
4.10 SIEMENS AG 28
5.0 SMART CITY IMPACT ON INDUSTRY VERTICALS 30
5.1 TELECOM AND SMART HOME 30
5.2 ENERGY MANAGEMENT 32
5.3 INDUSTRIAL AUTOMATION 33
5.4 TRANSPORTATION 33
5.5 SECURITY 34
6.0 GLOBAL SMART CITY INVESTMENT, PLANNING AND PROJECTS 36
6.1 ASIA PACIFIC 36
6.2 EUROPE 42
6.3 NORTH AMERICA 44
6.4 SOUTH AMERICA 45
7.0 MARKET OUTLOOK AND FORECASTING 47
7.1 GLOBAL METROPOLITAN GROWTH AND SMART CITY INVESTMENTS 47
7.2 SMART HOME REVENUE 2014 - 2019 49
7.3 CONNECTED CONSUMER DEVICES 2014 - 2019 50
7.4 FORECASTING THE INTERNET OF THINGS (IOT) IN THE SMART CITY IMPACT 50
8.0 CONCLUSIONS AND RECOMMENDATIONS 52
8.1 ECOSYSTEM IMPACT 52
8.2 NEED FOR CITIZEN ENGAGEMENT AND TECHNOLOGY COLLABORATION 53
8.3 CONSTITUENT COLLABORATION 53
8.4 FINAL CONCLUSIONS 54

Figures

Figure 1: Smart City Concept 6
Figure 2: Smart City Participants 7
Figure 3: HetNet Topology 11
Figure 4: WiMAX Communications 12
Figure 5: Smart City Infrastructure 18
Figure 6: ABB Smart City Offerings 19
Figure 7: Accenture Smart City Offerings 21
Figure 8: Trends and Smart City Future 35
Figure 9: Smart City Market Sizing 36
Figure 10: Smart City Investment Asia Pac 2014 - 2023 37

Tables

Table 1: Global Consumer Smart Home Products and Services Revenue 2014 - 2019 49
Table 2: Global Households, Broadband, and Smart Homes 2014 - 2019 50
Table 3: Global Connected Consumer Device Revenue by Type 2014 - 2019 50
Table 4: Global Internet of Things Objects 2014 - 2019 51

Smart Homes: Companies and Solutions 2014

INTRODUCTION TO SMART HOMES 8
WHAT IS SMART HOME TECHNOLOGY? 8
SMART HOME ENVIRONMENT 8
Home Automation System 8
Home Automation Standards and Architectures 9
Centralized Architecture 10
Distributed Architecture 10
Mixed Architecture 10
Home Automation Network 10
Bus Standards 11
Open Standards or Proprietary Protocols and Procedures 11
European Installation Bus (EIB _ 11
KNX 11
Local Operating Network (LON) 11
X10 12
BACnet 12
Internet protocol (IP) 12
Mediums for transfer of signals 13
Communication In-House and Out-of-House 14
Interface 14
Standard Units 14
Mobile Phone 14
Cordless DECT Telephones 15
BENEFITS OF HOME AUTOMATION 16
Convenience 16
Security 16
Savings 16
Value 16
SMART HOMES GLOBAL MARKET ASSESSMENT 16
Smart Homes Market Demand 16
Smart Home Market Growth Drivers 17
Always-Connected Customers 17
Energy Conservation 18
New Technologies 19
Market Segments and Potential 19
Smart Homes in the Developed Market 20
Demographics Analysis 20
Age 20
Education and Culture 21
Cost 21
Usability 21
Quality 21
Developing Market 21
Home Automation Usage and Purchase Factors 22
Cost 22
Quality 22
Usability 22
Warranty and Support 22
Emerging Market 22
Demographics Analysis 23
Age 23
Trust 23
Financially-Safe 24
Warranty and Support 24
HOME AUTOMATION APPLICATIONS 25
SMART LIGHTING 25
Smart Lighting Market Demand 25
Types of Lamps 26
Phased out Lamps 26
Conventional Incandescent Lamp (GLS) 26
Conventional Halogen Lamps 26
Available Alternatives 27
Conventional Low-voltage Halogen lamps 27
Halogen lamps with xenon gas filling (C-class) 27
Halogen Lamps with Infrared Coating (B-class) 28
Compact fluorescent lamps (CFLs) 29
Light-emitting Diodes (LEDs) 30
Techniques of Smart Lighting 32
Smart Lighting Control 32
Daylight Sensing 33
Occupancy Sensing 34
An Internet Address for Every Light Bulb 35
HOME ENTERTAINMENT 36
Home Entertainment Market Demand 36
Home Entertainment Applications 37
Home Theater 37
Whole House Audio 38
Video Distribution 41
SMART HOME SECURITY 42
Smart Home Security Market Demand 42
Smart Home Security Components 43
Doors and Windows Security 43
Motion Sensors 45
Security Alarm 46
Surveillance Cameras 47
Home Health Monitoring - Telehealth 48
SMART GRID AND SMART APPLIANCES 50
Smart Grid Market Demand 51
SMART HOMES FUTURE OUTLOOK 54
TOWARDS LESS PRICE AND HIGHER AWARENESS 54
BUILDING DIFFERENT CUSTOMERS BASE 55
DIY AUTOMATION 55
THE INTERNET OF THINGS: CONNECTING THE SMART HOME 56

Figures

FIGURE 1: INSTALLED SMART HOMES US 2012 - 2017 17
FIGURE 2: MOBILE DEVICES PER USER 2014 - 2018 18
FIGURE 3: US RESIDENTIAL AND COMMERCIAL LIGHTING CONSUMPTION 25
FIGURE 4: ENERGY SAVINGS BY LAMP TECHNOLOGIES 31
FIGURE 5: SONY REVENUE BY SECTOR 2012 - 2014 37
FIGURE 6: HOME SECURITY MARKET GROWTH 2011 - 2017 43
FIGURE 7: MARKET VALUE FOR THE SMARTGRID COMMUNICATION NETWORKS IN US 2010 - 2015 51
FIGURE 8: PROJECTED GLOBAL SMART GRID INVESTMENT 2009 - 2015 52
FIGURE 9: GROWTH OF MOBILE DEVICES 2015 - 2020 54
FIGURE 10: CELLULAR CONNECTION GROWTH 2010 - 2020 55
FIGURE 11: ENERGY SMART HOME LAB 56

Machine-to-Machine Communications: What Executives and IT Leaders Need to Know about M2M and its Role in Support of IoT

1 Executive Summary 5
2 Introduction to M2M 7
2.1 M2M Overview 7
2.2 M2M Basics 7
2.2.1 Data Acquisition 8
2.2.2 Data Transmission 8
2.2.3 Data Analysis 9
2.3 M2M in Industry Sectors 10
2.3.1 Smart Grid 10
2.3.2 Water Meters 10
2.3.3 Healthcare 10
2.3.4 Smart Meters 11
2.3.5 Smart Cities 12
2.3.6 Retail 12
2.3.7 Connected Building 12
2.3.8 Connected People 12
2.3.9 Connected Vehicles 12
2.3.10 Connected Infrastructure 13
2.3.11 Connected Industrial Processes 13
2.3.12 Connected Money 13
2.3.13 M2M and Big Data 13
2.4 M2M Ecosystem 13
2.4.1 End Device/Equipment 14
2.4.2 Consumer/End-user 14
2.4.3 End Device/Equipment 14
2.4.4 Sensors 15
2.4.5 Applications 15
2.4.6 Middleware Platform 16
2.4.7 Embedded Module 17
2.4.8 Subscriber Identity Module (SIM) 17
2.5 M2M and the Internet of Things (IoT) 18
2.6 M2M Applications 20
2.6.1 Fleet and Field Service Management 20
2.6.2 Manufacturing 20
2.6.3 Healthcare 20
2.6.4 Automotive 20
2.6.5 Supply Chain Management 21
2.6.6 Retail Management 21
2.6.7 Smart Homes and Buildings 21
2.6.8 Security and Surveillance 21
2.6.9 Usage Based Insurance 22
3 M2M Market Adoption and Barrier 23
3.1 M2M Adoption 23
3.2 M2M Barriers/Challenges 23
3.3 Improving M2M 24
4 M2M Market Opportunities and Future Outlook 27
4.1 Market Forecast 27
4.2 M2M Market Predictions 29
4.2.1 Big Data Aligned with M2M 29
4.2.2 Standards Strengthen 29
4.2.3 Open Hardware 29
4.2.4 Open Interfaces 29
4.2.5 More Innovation by Start-ups 30
4.2.6 M2M based Consumer Electronics will Reach Consumers 30
4.2.7 Connected cars in Spot-light 30
4.2.8 Transport Management Extends 30
4.2.9 New products for Insurance Industry 31
4.2.10 More installations of Smart Meters 31
4.2.11 Smart Cities Thrive 31
4.3 Future M2M Applications 31
5 Recommended Further Reading 37

Figures

Figure 1: Basic Building Blocks of M2M 7
Figure 2: The M2M Ecosystem (A) 14
Figure 3: The M2M Ecosystem (B) 15
Figure 4: The M2M Ecosystem © 16
Figure 5: The M2M Ecosystem (D) 17
Figure 6: Cellular M2M Connections Forecast 2014 - 2020 28
Figure 7: Cellular M2M as a Percentage of Total Mobile Connections 28

Smart Home, Building, and City Machine-to-Machine (M2M) Applications

EXECUTIVE SUMMARY
1.0 SMART HOME 1
2.1 Primary Elements of Smart Home 1
2.1.1 Infrastructure 1
2.1.2 Sensors 2
2.1.3 Actuators 2
2.1.4 Applications 3
2.1.5 Hub 4
2.2 Real-life applications and solutions available for Smart Home 7
2.3 Smart Home Vision 17
2.4 Requirement of Smart Home Services 18
2.4.1 Affordability 19
2.4.2 Usability 19
2.4.3 Reliability 20
2.5 Stages of Smart Home Services 20
2.5.1 Stage 1 - Connected Standalone Devices 21
2.5.2 Stage 2 - Connected Service Silos 22
2.5.3 Stage 3 - Integrated Smart Home 24
2.6 Smart Home Ecosystem Requirements 25
2.6.1 Home Environment 26
2.6.2 Wide Area Connectivity 27
2.6.3 Back-end Environment 27
2.6.4 Enabling Service Features 28
2.6.5 Third Party Service Providers 28
2.0 SMART HOME SOLUTION FOR SUSTAINABLE HOMES 32
3.1 Sustainability 32
3.2 Smart Home parameters to support sustainable home concept 32
3.2.1 Thermal Comfort 33
3.2.2 Water 34
3.2.3 Communications and Entertainment 34
3.2.4 Safety and Security 35
3.2.5 Lighting 35
3.2.6 Heath and Wellbeing 36
3.2.7 Smart Meter 36
3.2.8 Protecting the Building fabric 37
3.0 SMART BUILDING 38
4.1 Security Solution 39
4.2 Facilities Control 40
4.3 Standardization in Smart Home Arena 42
4.0 CASE STUDY - SMART HOME AND SMART BUILDING 43
5.1 Case: Smart Home Solution for Art Collector 43
5.1.1 The Challenge 43
5.1.2 The Solution 43
5.1.3 The Result 45
5.2 Case: Total Home Control Solution 45
5.2.1 The Challenge 45
5.2.2 The Solution 45
5.2.3 The Result 46
5.3 Case: Sir Richard Branson's Caribbean Smart Home 47
5.3.1 The Challenge 47
5.3.2 The Solution 47
5.3.3 The Result 48
5.4 Case: Energy Management 48
5.4.1 The Challenge 48
5.4.2 The Solution 49
5.4.3 The Result 49
5.5 Case : Real-time monitoring of oil levels 50
5.5.1 The Challenge 50
5.5.2 The Solution 50
5.5.3 The Result 50
5.5.4 Author's Note 50
5.6 Case: Professional Golfer's Smart Home 50
5.6.1 The Challenge 51
5.6.2 The Solution 51
5.6.3 The Result 53
5.7 Case : Monitor Structural parameters in Real time 53
5.7.1 The Challenge 54
5.7.2 The Solution 54
5.7.3 The Result 54
5.7.4 Author's Note 55
5.0 CONCEPTS OF SMART CITY 56
5.8 Objective of Smart City 57
5.9 Essential Elements of Smart City 59
5.10 Initial Steps for Creating Smart Cities 60
5.11 Framework for Smart City 60
5.12 Features of Smart City 63
5.13 Use of M2M for Smart City 65
5.14 Development activities for Smart City in India 67
5.15 Development activities for Smart City in China 69
5.16 Development activities for Smart City in Spain 70
5.16.1 Wireless network in Santander 70
5.17 Development activities for Smart City in Brazil 72
5.18 Development activities for Smart City across the Globe 73
5.19 Standards (or lack of it) for Smart City 75
5.20 Open-Source Platform for developing Applications 75
6.0 CASE STUDY - SMART CITY 78
6.1 Case : Solution for Traffic Safety 78
6.1.1 The Challenge 78
6.1.2 The Solution 78
6.1.3 The Result 79
6.1.4 Author's Note 79
6.2 Case : Solution for Parking Meters 80
6.2.1 The Challenge 80
6.2.2 The Solution 80
6.2.3 The Result 81
6.2.4 Author's Note 81
6.3 Case : Solution for 'smart' public convenience system 81
6.3.1 The Challenge 81
6.3.2 The Solution 82
6.3.3 The Result 83
6.3.4 Author's Note 83
6.4 Case : Solution for Waste Disposal 83
6.4.1 The Challenge 83
6.4.2 The Solution 84
6.4.3 The Result 84
6.4.4 Author's Note 84
6.5 Case : Experimental Research Facility for Smart City 85
6.5.1 The Challenge 85
6.5.2 The Solution 85
6.5.3 The Result 85
6.5.4 Author's Note 86
7.0 CONCLUDING REMARKS 87

Figures

Figure 1: Primary Elements of Smart Home 6
Figure 2: Samsung Smart Home Service 7
Figure 3: Revolv 8
Figure 4: Device by Savant Systems 9
Figure 5: Archos 10
Figure 6: HAPIfork 10
Figure 7: Belkin WeMo Smart Slow Cooker 11
Figure 8: LeakSmart Water Valve 11
Figure 9: Sleep Number x12 Bed 12
Figure 10: Whirlpool Smart Dishwasher 12
Figure 11: Netatmo Connected Weather Station 13
Figure 12: Koubachi Wi-Fi Plant Sensor 14
Figure 13: Nest Thermostat 15
Figure 14: Canary's multi-sensor security hub 15
Figure 16: Staples Connect 16
Figure 17: Belkin WeMo Home Automation 17
Figure 18: Smart Home Vision 18
Figure 19: Requirement of Smart Home Services 19
Figure 20: Stages of Smart Home Services 21
Figure 21: Stage 1: Connected Standalone Devices 22
Figure 22: Stage 2: Connected Service Silos 23
Figure 23: Stage 3: Integrated Smart Home 25
Figure 24: Smart Home Ecosystem Requirements 26
Figure 25: Smart Home parameters to support sustainable home concept 33
Figure 26: Intelligent Building 40
Figure 27: Objectives of Smart City 57
Figure 28: Essential elements of Smart City 59
Figure 29: Initial Steps for Creating Smart Cities 60
Figure 30: Important Tasks for Smart City 61
Figure 31: Smart City Framework 62
Figure 32: Features of Smart City 64

LTE Advanced: State of the Market and Future Prospects

Executive Summary 1
Background 5
Overview of Mobile Broadband 5
Overview 5
First Generation (1G) 6
1G Features 7
Second Generation (2G) 7
2G Features 9
2.5G Wireless System 9
2.75G (EDGE) Wireless System 10
2.75G Features 10
Third Generation (3G) 10
Fourth Generation (4G) 12
4G Features 12
Fifth Generation (5G) 13
5G Features 13
Long Term Evolution (LTE) 14
LTE Advanced 15
Overview 15
Major LTE-Advanced Features 18
Carrier Aggregation (CA) 18
Enhanced Uplink Multiple Access and Enhanced Multiple Antenna Transmission 19
Coordinated Multipoint Transmission and Reception (CoMP) 19
Home Enhanced-node-B (HeNB) Mobility Enhancements (HetNet) 20
Competitive Analysis (LTE-Advanced vs. WiMAX 2) 21
Network Nature 22
Using OFDMA 22
Adaptive Modulation and Coding 23
Conclusion 24
LTE-Advanced Market Drivers 25
Key Enabler for Growth 25
Increased Adoption of Mobile Broadband 25
Speed and Cost 26
Hardware 27
Major LTE-Advanced Players 29
LTE-Advanced Demonstration 29
LTE-Advanced Demonstrations Distribution by Country 37
LTE-Advanced Deployments (Active, Planned) 39
LTE-Advanced Deployments Distribution by Country 43
Future Outlook and Forecasts 45
More Capacity will be followed by Great Demand 45
Fifth Generation (5G) 46
Appendix 47
LTE Infrastructure Elements and Architecture 47
LTE E-UTRAN 47
LTE Remote Radio Heads 48
LTE Base Station 49
LTE Femtocells 50
LTE Antenna Schemes 51
LTE RAN Infrastructure and Frequency Reuse 52
LTE EPC Infrastructure Elements 52
Serving and Packet Gateway 53
Mobility Management Entity 55
Policy and Charging Rules Function 55
IP Multimedia Subsystem 55
EPC and Core Network Equipment Reuse in LTE 56
LTE Architecture Details 57
Service Architecture 58
Layer 2 of LTE 59
Downlink Logical 60
Uplink Logical 61
Mobility Across eNBs 62

Figures

Figure 1: 1G Mobile Phone 7
Figure 2: 2G Specifications 9
Figure 3: 2G Mobile Phone 9
Figure 4: 3G Specifications 11
Figure 5: 3G Mobile Phone 11
Figure 6: 4G Mobile Phone 13
Figure 7: Release of 3GPP Specification 15
Figure 8: Key Radio Access Targets for LTE-Advanced as set by 3GPP 17
Figure 9: Upgrade from LTE to LTE-Advanced 17
Figure 10: Wireless Technology Evolution 21
Figure 11: Comparing Wireless Technologies based on Speed 25
Figure 12: Top Application Growth 26
Figure 13: Traffic Growth 26
Figure 14: End-users use WiFi Service when Available 27
Figure 15: LTE-Advanced Demonstrations and Trials by Country 2014 39
Figure 16: LTE Advanced Deployments by Country 44
Figure 17: LTE Advanced Deployments Target Speed (Maximum DL) (Mbps) 45
Figure 18: Mobile Traffic Forecast 2010 - 2020 45
Figure 19: LTE E-UTRAN Infrastructure Network Elements 48
Figure 20: LTE EPC Infrastructure Network Elements 53
Figure 21: Understanding LTE Network Elements and Channels 59

Fundamentals of Big Data, Predictive Analysis, and Business Intelligence

INTRODUCTION 3
TECHNICAL OVERVIEW 4
BIG DATA OVERVIEW 4
TECHNOLOGY TRENDS 5
MARKET OVERVIEW 12
MARKET FORECAST 12
MARKET ANALYSIS 17
MARKET PREDICTIONS 19
MARKET SECTORS 21
Science/Research 21
Government 22
Private Sector 23
Finance 28
BUSINESS OVERVIEW 31
BIG DATA TRANSITION CHALLENGES 31
RISKS AND ISSUES 32
SUMMARY 36
APPENDIX 37

The Big Data and Telco Analytics Market: Business Case, Market Analysis and Forecasts 2014 - 2019

1 Chapter 1: Introduction 8
1.1 Executive Summary 8
1.2 Topics Covered 9
1.3 Key Findings 10
1.4 Target Audience 11
1.5 Companies Mentioned 12
2 Chapter 2: Big Data Technology and Business Case 15
2.1 Defining Big Data 15
2.2 Key Characteristics of Big Data 15
2.2.1 Volume 15
2.2.2 Variety 16
2.2.3 Velocity 16
2.2.4 Variability 16
2.2.5 Complexity 16
2.3 Big Data Technology 17
2.3.1 Hadoop 17
2.3.1.1 MapReduce 17
2.3.1.2 HDFS 17
2.3.1.3 Other Apache Projects 18
2.3.2 NoSQL 18
2.3.2.1 Hbase 18
2.3.2.2 Cassandra 18
2.3.2.3 Mongo DB 18
2.3.2.4 Riak 19
2.3.2.5 CouchDB 19
2.3.3 MPP Databases 19
2.3.4 Others and Emerging Technologies 20
2.3.4.1 Storm 20
2.3.4.2 Drill 20
2.3.4.3 Dremel 20
2.3.4.4 SAP HANA 20
2.3.4.5 Gremlin and Giraph 20
2.4 Market Drivers 21
2.4.1 Data Volume and Variety 21
2.4.2 Increasing Adoption of Big Data by Enterprises and Telcos 21
2.4.3 Maturation of Big Data Software 21
2.4.4 Continued Investments in Big Data by Web Giants 21
2.5 Market Barriers 22
2.5.1 Privacy and Security: The 'Big' Barrier 22
2.5.2 Workforce Re-skilling and Organizational Resistance 22
2.5.3 Lack of Clear Big Data Strategies 23
2.5.4 Technical Challenges: Scalability and Maintenance 23
3 Chapter 3: Key Investment Sectors for Big Data 24
3.1 Industrial Internet and M2M 24
3.1.1 Big Data in M2M 24
3.1.2 Vertical Opportunities 24
3.2 Retail and Hospitality 25
3.2.1 Improving Accuracy of Forecasts and Stock Management 25
3.2.2 Determining Buying Patterns 25
3.2.3 Hospitality Use Cases 25
3.3 Media 26
3.3.1 Social Media 26
3.3.2 Social Gaming Analytics 26
3.3.3 Usage of Social Media Analytics by Other Verticals 26
3.4 Utilities 27
3.4.1 Analysis of Operational Data 27
3.4.2 Application Areas for the Future 27
3.5 Financial Services 27
3.5.1 Fraud Analysis and Risk Profiling 27
3.5.2 Merchant-Funded Reward Programs 27
3.5.3 Customer Segmentation 28
3.5.4 Insurance Companies 28
3.6 Healthcare and Pharmaceutical 28
3.6.1 Drug Development 28
3.6.2 Medical Data Analytics 28
3.6.3 Case Study: Identifying Heartbeat Patterns 28
3.7 Telcos 29
3.7.1 Telco Analytics: Customer/Usage Profiling and Service Optimization 29
3.7.2 Speech Analytics 29
3.7.3 Other Use Cases 29
3.8 Government and Homeland Security 30
3.8.1 Developing New Applications for the Public 30
3.8.2 Tracking Crime 30
3.8.3 Intelligence Gathering 30
3.8.4 Fraud Detection and Revenue Generation 30
3.9 Other Sectors 31
3.9.1 Aviation: Air Traffic Control 31
3.9.2 Transportation and Logistics: Optimizing Fleet Usage 31
3.9.3 Sports: Real-Time Processing of Statistics 31
4 Chapter 4: The Big Data Value Chain 32
4.1 How Fragmented is the Big Data Value Chain? 32
4.2 Data Acquisitioning and Provisioning 33
4.3 Data Warehousing and Business Intelligence 33
4.4 Analytics and Virtualization 33
4.5 Actioning and Business Process Management (BPM) 34
4.6 Data Governance 34
5 Chapter 5: Big Data in Telco Analytics 35
5.1 How Big is the Market for Telco Analytics? 35
5.2 Improving Subscriber Experience 36
5.2.1 Generating a Full Spectrum View of the Subscriber 36
5.2.2 Creating Customized Experiences and Targeted Promotions 36
5.2.3 Central 'Big Data' Repository: Key to Customer Satisfaction 36
5.2.4 Reduce Costs and Increase Market Share 37
5.3 Building Smarter Networks 37
5.3.1 Understanding the Usage of the Network 37
5.3.2 The Magic of Analytics: Improving Network Quality and Coverage 37
5.3.3 Combining Telco Data with Public Data Sets: Real-Time Event Management 37
5.3.4 Leveraging M2M for Telco Analytics 37
5.3.5 M2M, Deep Packet Inspection and Big Data: Identifying and Fixing Network Defects 38
5.4 Churn/Risk Reduction and New Revenue Streams 38
5.4.1 Predictive Analytics 38
5.4.2 Identifying Fraud and Bandwidth Theft 38
5.4.3 Creating New Revenue Streams 39
5.5 Telco Analytics Case Studies 39
5.5.1 T-Mobile USA: Churn Reduction by 50% 39
5.5.2 Vodafone: Using Telco Analytics to Enable Navigation 39
6 Chapter 6: Key Players in the Big Data Market 41
6.1 Vendor Assessment Matrix 41
6.2 Apache Software Foundation 42
6.3 Accenture 42
6.4 Amazon 42
6.5 APTEAN (Formerly CDC Software) 43
6.6 Cisco Systems 43
6.7 Cloudera 43
6.8 Dell 43
6.9 EMC 44
6.10 Facebook 44
6.11 GoodData Corporation 44
6.12 Google 44
6.13 Guavus 45
6.14 Hitachi Data Systems 45
6.15 Hortonworks 45
6.16 HP 46
6.17 IBM 46
6.18 Informatica 46
6.19 Intel 46
6.20 Jaspersoft 47
6.21 Microsoft 47
6.22 MongoDB (Formerly 10Gen) 47
6.23 MU Sigma 48
6.24 Netapp 48
6.25 Opera Solutions 48
6.26 Oracle 48
6.27 Pentaho 49
6.28 Platfora 49
6.29 Qliktech 49
6.30 Quantum 50
6.31 Rackspace 50
6.32 Revolution Analytics 50
6.33 Salesforce 51
6.34 SAP 51
6.35 SAS Institute 51
6.36 Sisense 51
6.37 Software AG/Terracotta 52
6.38 Splunk 52
6.39 Sqrrl 52
6.40 Supermicro 53
6.41 Tableau Software 53
6.42 Teradata 53
6.43 Think Big Analytics 54
6.44 Tidemark Systems 54
6.45 Vmware (Part of EMC) 54
7 Chapter 7: Market Analysis 55
7.1 Big Data Revenue: 2014 - 2019 55
7.2 Big Data Revenue by Functional Area: 2014 - 2019 56
7.2.1 Supply Chain Management 57
7.2.2 Business Intelligence 58
7.2.3 Application Infrastructure and Middleware 59
7.2.4 Data Integration Tools and Data Quality Tools 60
7.2.5 Database Management Systems 61
7.2.6 Big Data Social and Content Analytics 62
7.2.7 Big Data Storage Management 63
7.2.8 Big Data Professional Services 64
7.3 Big Data Revenue by Region 2014 - 2019 65
7.3.1 Asia Pacific 66
7.3.2 Eastern Europe 67
7.3.3 Latin and Central America 68
7.3.4 Middle East and Africa 69
7.3.5 North America 70
7.3.6 Western Europe 71

Figures

Figure 1: The Big Data Value Chain 32
Figure 2: Telco Analytics Investments Driven by Big Data: 2013 - 2019 ($ Million) 35
Figure 3: Big Data Vendor Ranking Matrix 2013 41
Figure 4: Big Data Revenue: 2013 - 2019 ($ Million) 55
Figure 5: Big Data Revenue by Functional Area: 2013 - 2019 ($ Million) 56
Figure 6: Big Data Supply Chain Management Revenue: 2013 - 2019 ($ Million) 57
Figure 7: Big Data Supply Business Intelligence Revenue: 2013 - 2019 ($ Million) 58
Figure 8: Big Data Application Infrastructure and Middleware Revenue: 2013 - 2019 ($ Million) 59
Figure 9: Big Data Integration Tools and Data Quality Tools Revenue: 2013 - 2019 ($ Million) 60
Figure 10: Big Data Database Management Systems Revenue: 2013 - 2019 ($ Million) 61
Figure 11: Big Data Social and Content Analytics Revenue: 2013 - 2019 ($ Million) 62
Figure 12: Big Data Storage Management Revenue: 2013 - 2019 ($ Million) 63
Figure 13: Big Data Professional Services Revenue: 2013 - 2019 ($ Million) 64
Figure 14: Big Data Revenue by Region: 2013 - 2019 ($ Million) 65
Figure 15: Asia Pacific Big Data Revenue: 2013 - 2019 ($ Million) 66
Figure 16: Eastern Europe Big Data Revenue: 2013 - 2019 ($ Million) 67
Figure 17: Latin and Central America Big Data Revenue: 2013 - 2019 ($ Million) 68
Figure 18: Middle East and Africa Big Data Revenue: 2013 - 2019 ($ Million) 69
Figure 19: North America Big Data Revenue: 2013 - 2019 ($ Million) 70
Figure 20: Western Europe Big Data Revenue: 2013 - 2019 ($ Million) 71

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