Enterprise Mobility 2015: BYOD, Cloud, Social, Big Data and Application Management




Published: October 2015   Pages: 952
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Overview:

One of the biggest challenges for enterprise is optimizing mobility to realize business strategies and integrate disparate technologies in a blended manner. Major factors driving enterprise mobility today include Bring Your Own Device (BYOD), enterprise Cloud management, social networking, and application management.

Data management is also a major challenge for enterprise as corporations seek to optimize business operations and customer behaviors to better direct enterprise resources. Big Data and Analytics, Data as a Service (DaaS), and Cloud systems are all important areas for the entire enterprise ecosystem including CSPs, software providers, and ICT platform and infrastructure providers.

This research package includes:

  • Cloud Application Marketplace 2015 – 2020
  • Data as a Service (DaaS) Market and Forecasts 2015 – 2020
  • Big Data Market: Business Case, Market Analysis & Forecasts 2015 - 2020
  • Social Business Services in the Cloud: Market Analysis and Forecast 2015 - 2020
  • BYOD in Enterprise Applications and Cloud Environment: Market Challenge and Opportunity Analysis 2015 – 2020
  • Mobile Application Marketplace 2015: Market Analysis and Assessment of Future Evolution and Opportunities

This research evaluates the challenges, opportunities, and market outlook for BYOD in enterprise and cloud environments. This research assesses the potential users of cloud service and includes a SWOT analysis, cloud social vendor analysis, market trends, and industry forecasts. The report also analyzes the technology and solution providers in certain key areas including marketing automation, social media monitoring, enterprise collaboration, web experience management, information governance, digital commerce, CRM and customer support, ECM and File sharing, and workforce management. This includes evaluation of the key benefits, challenges, trends and development process impacting the market for cloud-based applications.

This research also provides an in-depth assessment of the global Big Data market, including a study of the business case, application use cases, vendor landscape, value chain analysis, case studies and a quantitative assessment of the industry. 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:

  • Medium-to-large business
  • Wireless network operators
  • Mobile apps stores providers
  • Data as a Service (DaaS) providers
  • Big Data and Analytics services companies
  • Mobile device management solution providers
  • Enterprise mobility management and IT personnel
  • Cloud software, platform, and infrastructure providers

Table of Contents:

BYOD in Enterprise Applications and Cloud Environment: Market Challenge and Opportunity Analysis 2015 – 2020

1.0 EXECUTIVE SUMMARY
2.0 INTRODUCTION
2.1 CONSUMERIZATION OF IT AND BYOD
2.2 MDM AND EMM
2.3 MOBILE VIRTUALIZATION
2.4 CYOD/HYOD/COPE VS. BYOD
2.5 MAM, MIM, AND IDENTITY MANAGEMENT
3.0 BYOD TRENDS
3.1 HIGH PENETRATION OF MOBILE
3.2 MOBILITY OF WORKFORCE
3.3 FLEXIBLE WORK ENVIRONMENT
3.4 AVAILABILITY AND PERFORMANCE OF MOBILE DEVICE
3.5 BYOD PRODUCTIVITY
3.6 BYOD SECURITY
3.7 OPEX REDUCTION
3.8 EMPLOYEE EMPOWERMENT
3.9 MOBILE OS
3.10 MANDATING BYOD AS APPROACH
3.11 MOBILE DEVICE MANAGEMENT
3.12 MODERNIZING LEGACY APPLICATION
3.13 VIRTUAL WORKING ENVIRONMENT
3.14 WEARABLE TECHNOLOGY
3.15 ENTERPRISE IT
3.16 TABLET COMPUTING
4.0 BYOD IN ENTERPRISE
4.1 WHY BYOD FOR ENTERPRISE MOBILITY
4.2 BENEFITS OF BYOD
4.3 BYOD OBSTACLES
4.3.1 REDUCE EMPLOYEE’S PRODUCTIVITY
4.3.2 LICENSING
4.3.3 COST RISK
4.4 STRATEGY TO SECURE ENTERPRISE
4.4.1 CONTAINERIZATION
4.4.2 MAM
4.4.3 IDENTITY AND ACCESS MANAGEMENT
4.5 BYOD IN SMBS
4.6 OTHER CONSIDERATIONS FOR SMBS
4.6.1 NOTIFICATION
4.6.2 BEST PRACTICES ADOPTION
4.6.3 TRANSPARENT POLICY
4.6.4 EMPLOYEE EDUCATION
4.6.5 DATA SEGREGATION
4.6.6 SOCIAL FACTOR
4.6.7 PREVENT DATA LEAKAGE
4.6.8 IT SUPPORT
4.7 LOCATION IMPACT AND SOLUTION
4.7.1 LOCAID: FULL SCALE ENTERPRISE LOCATION SOLUTION
5.0 BYOD APPLICATIONS IN ENTERPRISE SECTORS
5.1 TRAVEL AGENCY
5.2 HEALTHCARE INDUSTRY
5.3 GOVERNMENT AGENCY
5.4 WORKPLACE ENVIRONMENT
5.5 ROLE OF MNOS
6.0 BYOD IN CLOUD ENVIRONMENT
6.1 CLOUD BYOD ADOPTION
6.2 ENTERPRISE MIGRATION TO CLOUD
6.3 ENTERPRISE BENEFITS OF CLOUD SERVICE
6.4 CLOUD GROWTH DRIVERS
6.5 DATA SECURITY IN CLOUD
6.6 CLOUD APP SECURITY CHALLENGE
6.7 PROTECTING CORPORATE ASSETS
6.8 CASE STUDY
6.8.1 DOMINO’S PIZZA
6.8.2 LONDON AIRPORT
7.0 ENTERPRISE MDM
7.1 MDM OR EMM
7.1.1 DEVICE MANAGEMENT
7.1.2 APPLICATION MANAGEMENT
7.1.3 NETWORK MANAGEMENT
7.1.4 DATA MANAGEMENT
7.2 RECOMMENDED FEATURES FOR MDM
7.3 MDM PROJECTIONS AND TREND 2015 – 2020
7.3.1 ENTERPRISE PERCEPTION ON BYOD IN WORKPLACE
7.3.2 ENTERPRISE BELIEF OVER MOBILE WORKFORCE
7.3.3 WORKPLACE MOBILITY TREND OF PROFESSIONALS 2015 - 2020
7.3.4 EMPLOYEE RATIO OF PERSONAL DEVICES 2015 - 2020
7.3.5 WHAT EMPLOYEE FEELINGS ABOUT USING PERSONAL DEVICES FOR WORK
7.3.6 COMPANIES ON MOBILE WORKFORCE ADOPTION 2015 - 2020
7.3.7 COMPANY CONCERN OVER ALLOWING PERSONAL DEVICES IN WORKPLACE
7.3.8 MOBILE WORKFORCE ADOPTION SCENARIO
7.3.9 PERSONAL MOBILE DEVICES IN TODAY’S WORKPLACE
7.3.10 MOBILE MALWARE THREAT & MOBILE WORKFORCE DILEMMA
7.3.11 HOW COMPANIES MANAGE MOBILITY WITH SOLID STRATEGY
7.4 VENDOR ANALYSIS
8.0 MOBILE VIRTUALIZATION
9.0 BYOD TREND IN SMAC CONVERGENCE
10.0 GAMIFICATION AND BYOD
11.0 ENTERPRISE CHALLENGES
11.1 POLICY VS. REGULATORY
11.1.1 DEFINE WHAT WILL BE ALLOWED AND WHAT IS NOT
11.1.2 SET CLEAR AND WRITTEN POLICIES
11.1.3 DETERMINE WHOSE DATA IS?
11.1.4 WHO OWNS THE HARDWARE?
11.2 SECURITY VS. INFRASTRUCTURE
11.3 COST VS. REVENUE
11.4 WORKING CULTURE CHALLENGES
11.5 SECURITY RISK OF BYOD DEPLOYMENT
11.6 REASONS OF SECURITY RISKS
11.6.1 OUTDATED SOFTWARE
11.6.2 INABILITY TO PREVENT INSTALLATION OF SPECIFIC MOBILE APPS
11.6.3 CONSUMERIZATION OF CLOUD STORAGE
12.0 BYOD IMPLEMENTATION
12.1 IDENTIFYING RIGHT APPROACH
12.2 EVALUATING BYOD DEPLOYMENT FACTORS
12.3 EVALUATING HYBRID BYOD
12.4 MINIMIZING MOBILE SECURITY RISKS
12.5 EVALUATING MOBILE DEVICE OWNERSHIP
12.6 COBIT 5 FRAMEWORK
13.0 BYOD PROJECT MANAGEMENT
13.1 PROJECT TEAM
13.2 BYOD ROADMAP
13.3 POLICY GUIDELINE
13.4 RIGHT INFRASTRUCTURE
13.5 DATA OWNERSHIP
13.6 ACCESS POLICY
13.7 ROBUST SUPPORT
13.8 FINANCIAL ELEMENTS
14.0 BYOD IMPLICATION FOR CIO AND IT DEPARTMENT
14.1 BROKER OF CHOICE
14.2 COST SAVER
14.3 SECURITY ENABLER
15.0 BYOD MARKET PROJECTIONS
15.1 GLOBAL CONNECTED DEVICE PROJECTION 2015 – 2020
15.2 M2M VS. PERSONAL HANDHELD CONNECTION 2015 – 2020
15.3 CONNECTED DEVICE IN REGIONS 2015 – 2020
15.4 GLOBAL MOBILE DATA TRAFFIC 2015 – 2019
15.5 MOBILE DATA TRAFFIC BY REGION 2015 – 2019
15.6 GLOBAL BYOD DEVICES IN WORKPLACE 2015 – 2020
15.7 BYOD DEVICES BY MOBILE OS 2015 - 2020
15.7.1 WHY APPLE IS STILL NUMBER ONE
15.8 WORKPLACE BYOD BY TYPES OF DEVICES 2015 – 2020
15.9 BYOD ADOPTION IN ENTERPRISE 2015 - 2020
15.10 GLOBAL CONNECTED DEVICES BY NETWORK 2015 – 2029
15.11 GLOBAL CONNECTED TRAFFIC SOURCE 2015 - 2019
15.12 GLOBAL CONNECTED CLOUD TRAFFIC 2015 - 2019
15.13 GLOBAL CELLULAR VS. OFFLOAD TRAFFIC 2015 - 2019
15.14 ENTERPRISE SUPPORT PLAN FOR BYOD
15.15 DURATION OF BYOD POLICY IN ENTERPRISE
15.16 PERCENT OF MOBILE BUDGET SPENT ON BYOD BY COUNTRY
15.17 DESKTOP VIRTUALIZATION STRATEGY IMPLEMENTATION
16.0 BYOD BY REGION
16.1 GROWTH MARKET VS. MATURE MARKET
16.1.1 LACK OF BYOD MANAGEMENT
16.1.2 AVERAGE OF NUMBER OF BYOD DEVICE 2014
16.1.3 BYOD BENEFITS 2014
16.2 EUROPE ANALYSIS
16.2.1 UNITED KINGDOM
16.2.2 FRANCE
16.2.3 GERMANY
16.2.4 RUSSIA
16.3 APAC ANALYSIS
16.3.1 CHINA
16.3.2 INDIA
16.4 LATIN AMERICA
16.4.1 BRAZIL
16.4.2 MEXICO
17.0 BYOD VENDOR ANALYSIS
17.1 HP
17.1.1 SWOT ANALYSIS
17.2 DELL
17.2.1 MOBILE ACCESS SOLUTION SET
17.2.2 CLOUD EXPERIENCE SOLUTION SET
17.2.3 NETWORK OPTIMIZATION SOLUTION SET
17.2.4 APPLICATION MODERNIZATION AND DEVELOPMENT SOLUTION SET
17.2.5 SWOT ANALYSIS
17.3 HUAWEI
17.3.1 SWOT ANALYSIS
17.4 RUCKS AND AEROHIVE
17.4.1 SWOT ANALYSIS
17.5 ARUBA 105
17.5.1 SWOT ANALYSIS
17.6 CISCO
17.6.1 CISCO MERAKI
17.6.2 SWOT ANALYSIS
17.7 CITRIX 110
17.7.1 SWOT ANALYSIS
17.8 ENTERASYS: MOBILE IDENTITY ACCESS MANAGEMENT
17.8.1 SWOT ANALYSIS
17.9 ARMOR5
17.9.1 COMPANY DESCRIPTION
17.9.2 CLOUD BASED SOLUTION
17.9.3 ZERO TOUCH DEPLOYMENT MODEL
17.9.4 BEST SECURITY: REDUCE ATTACK SURFACE
17.9.5 SWOT ANALYSIS
17.10 DOMO
17.10.1 COMPANY DESCRIPTION
17.10.2 BUSINESS INTELLIGENCE (BI) VS. BIG DATA & ANALYTICS
17.10.3 BI DASHBOARD AND EXECUTIVE MANAGEMENT PLATFORM
17.10.4 SWOT ANALYSIS
17.11 DIVIDE BY ENTERPROID
17.11.1 COMPANY DESCRIPTION
17.11.2 DIVIDE PLATFORM
17.11.3 VIRTUALIZATION & DEVICE MANAGEMENT
17.11.4 WORK-LIFE BALANCE & DIVIDE PLATFORM
17.11.5 SWOT ANALYSIS
17.12 MOBILESPACES
17.12.1 COMPANY DESCRIPTION
17.12.2 ENTERPRISE APP SORE, EMPLOYEE PRIVACY AND BYOD SOLUTION
17.12.3 SWOT ANALYSIS
17.13 MOCANA
17.13.1 COMPANY DESCRIPTION
17.13.2 SOLUTION APPROACH
17.13.3 PRODUCT & SERVICE PARADIGM
17.13.4 INDUSTRY SERVICE HORIZON
17.13.5 SOLUTION FRAMEWORK
17.13.6 MOBILE APP PROTECTION & BYOD
17.13.7 APP WRAPPING SOLUTION AND MOCANA PARTNERSHIP WITH APPERIAN
17.13.8 SWOT ANALYSIS FOR MAP
17.14 APPERIAN
17.14.1 COMPANY DESCRIPTION
17.14.2 MAM PLATFORM AND EASE
17.14.3 SWOT ANALYSIS
17.15 ROAMBI
17.15.1 COMPANY DESCRIPTION
17.15.2 ROAMBI FLOW
18.0 MDM VENDOR ANALYSIS
18.1 AIRWATCH
18.2 APPLE PROFILE MANAGER
18.3 BOXTONE
18.4 CENTRIFY
18.5 GOOD TECHNOLOGY
18.6 IBM
18.7 LANDESK
18.8 MICROSOFT
18.9 MOBILEIRON
18.10 SAP
18.11 SYMANTEC
18.12 ZENPRISE/CITRIX
18.13 FIBERLINK
18.14 MOTOROLA SOLUTIONS
18.15 BLACKBERRY
18.16 TREND MICRO
18.17 SOTI
18.18 ABSOLUTE SOFTWARE
18.19 ANTENNA SOFTWARE
18.20 KONY
18.21 MCAFEE
18.22 SMITH MICRO SOFTWARE
18.23 SOPHOS
18.24 TANGOE
18.25 WAVELINK
18.26 JUNIPER NETWORKS
18.27 CSC
19.0 CASE ANALYSIS
19.1 MICROSOFT AZURE ACTIVE DIRECTORY CASE
19.1.1 BENEFITS ACHIEVED BY COMPANIES
19.2 IBM
19.3 DIGID
19.4 DIMENSION DATA
20.0 CONCLUSIONS AND RECOMMENDATIONS
20.1 RECOMMENDED CHECKLIST TO SELECT BYOD SOLUTION PROVIDER

Figures

Figure 1: Driving Forces of Mobility Adoption of Enterprises
Figure 2: BYOD Opportunities Allocation 2015 – 2017
Figure 3: Activity cycle of Enterprise Mobility
Figure 4: Deployment Difficulties of Enterprise Mobility
Figure 5: Steps for Implementing BYOD in SMBs
Figure 6: Growth Predictions of Government Agencies Using BYOD 2015 – 2018
Figure 7: Percent of Workers not willing to Work from Home
Figure 8: Strategic Consideration of BYOD Organization
Figure 9: Decision Making Factor for Cloud BYOD Adoption
Figure 10: BYOD Applications Available via Cloud 2015 – 2018
Figure 11: Enterprise Function Migration to Cloud Services
Figure 12: Enterprise Benefits Derived from Cloud Adoption
Figure 13: Personal Devices in Workplace as Corporate Security Risk 2015
Figure 14: Professionals use 2 Devices vs. 3 or More Devices 2015 – 2020
Figure 15: Employee Personal Devices vs. Ownership Status 2015 - 2020
Figure 16: Right vs. Want to Break Company Rule vs. Dislike MDM on Device 2015
Figure 17: Company Allow Personal Devices vs. MDM 2015 - 2020
Figure 18: Company Device Policy Breakdown 2015
Figure 19: Companies Who Allow Personal Devices in Workplace 2015
Figure 20: Personal Mobile Devices in Workplace 2015
Figure 21: Companies Managing Mobility in Different Ways 2015
Figure 22: VMware's Horizon Mobile and Horizon Mobile Manager
Figure 23: Employees using BYOD Devices 2015
Figure 24 Obstacles for BYOD Adoption 2015
Figure 25: Security Issues and Impact on BYOD Decision Making 2015
Figure 26: Mobile Security Options for BYOD and HYOD
Figure 27: Connected Device by Region 2015 – 2020
Figure 28: Global Mobile Data Traffic Exabytes per Month 2015 – 2019
Figure 29: Mobile Data Traffic Exabytes per Month by Region 2015 – 2019
Figure 30: Global BYOD Devices 2015 – 2020
Figure 31: Percentage of OS Used in BYOD Environment 2015 - 2020
Figure 32: Workplace BYOD (Smartphone vs. Tablet & Wearable) 2015 – 2020
Figure 33: BYOD Adoption (Large vs. Medium &. Small Enterprise) 2015 - 2020
Figure 34: Global Connected Device by Technology 2015 – 2019
Figure 35: Global Connected Traffic Source 2015 – 2019
Figure 36: Global Connected Traffic by Cloud vs. Non-Cloud 2015 – 2019
Figure 37: Global Connected Traffic by Cellular Source vs. Offload 2015 – 2019
Figure 38: Percent of Enterprise Support Plan for BYOD Adoption
Figure 39: Length of Time BYOD Policy in Enterprise by Percent of Enterprise
Figure 40: Percent of Mobile Budget spent on BYOD by Country
Figure 41: Desktop Virtualization Strategy Implementation by Region
Figure 42: BYOD in Developed vs. Developing Markets
Figure 43: Lack of BYOD Management Issues
Figure 44: Average Number of Connected Devices per Knowledge Worker
Figure 45: BYOD Benefits to the Company by Country
Figure 46: IMC BYOD Solution of HP
Figure 47: SWOT Analysis for Dell BYOD Solution
Figure 48: Different Phase for BYOD
Figure 49: Huawei BYOD Solution Component
Figure 50: Secure and Productive BYOD for the Enterprise
Figure 51: Main Components for BYOD Solutions
Figure 52: Cisco BYOD Solution Framework
Figure 53: Cisco BYOD Device Projections 2015 - 2017
Figure 54: Zero Touch Model
Figure 55: CloudSpace Architecture
Figure 56: Web Virtualization Engine (WVE) Architecture
Figure 57: Interactive Dashboard for Enterprise
Figure 58: Cross-Platform view of BI Dashboard
Figure 59: Divide Screenshot
Figure 60: Work-life Separation Interface of Divide
Figure 61: Native Apps Screenshot on Smartphone
Figure 62: Product & Service
Figure 63: Industry Coverage
Figure 64: Mocana Solution Framework
Figure 65: MAP Framework
Figure 66: EASE Admin Portal
Figure 67: Roambi Flow

Tables

Table 1: Comparative Analysis of 5 MDM Vendors - Part 1
Table 2: Comparative Analysis of 5 MDM Vendors - Part 2
Table 3: Global Connected Device 2015 – 2020
Table 4: M2M and Personal Handheld Connections 2015 – 2020
Table 5: SWOT Analysis for Huawei BYOD Solution
Table 6: SWOT Analysis for Aerohive BYOD Solution
Table 7: SWOT Analysis for Aruba BYOD Solution
Table 8: SWOT Analysis for Citrix BYOD Solution
Table 9: SWOT Analysis for Enterasys BYOD Solution
Table 10: Three Years Cost vs. Saving of Transactiv with Windows Azure
Table 11: Success Story of IBM using BYOD
Table 12: Questions to Answer before Finalizing BYOD Solution Provider

Cloud Application Marketplace 2015 – 2020

1.0 EXECUTIVE SUMMARY
2.0 OVERVIEW OF CLOUD COMPUTING
2.1 UNDERSTANDING CLOUD COMPUTING
2.1.1 CLOUD COMPUTING SERVICES
2.2 CLOUD FOUNDATIONS
2.2.1 CATEGORIES OF CLOUD COMPUTING DEPLOYMENT MODEL
2.2.2 GRID COMPUTING
2.2.3 GRID COMPUTING MARKET SEGMENTATION
2.3 CLOUD TECHNOLOGIES AND ARCHITECTURE
2.3.1 SOFTWARE DEFINED NETWORKING (SDN)
2.3.2 SDN DEPLOYMENT MODELS
2.3.3 VIRTUALIZATION (SERVER VS. HARDWARE VS. DESKTOP VS. STORAGE)
2.4 CLOUD COMPUTING AND VIRTUALIZATION
2.5 MOVING BEYOND CLOUD COMPUTING
2.5.1 A 'GLOCAL' CLOUD
2.6 RISE OF THE CLOUD-BASED NETWORKED ENTERPRISE
2.7 GENERAL CLOUD SERVICE ENABLERS
2.7.1 WIRELESS BROADBAND CONNECTIVITY
2.7.2 SECURITY SOLUTIONS
2.7.3 PRESENCE AND LOCATION
2.8 PERSONAL CLOUD SERVICE ENABLERS
2.8.1 IDENTITY MANAGEMENT
2.8.2 PREFERENCE MANAGEMENT
3.0 CLOUD SERVICE ANALYSIS
3.1 CLOUD SERVICE SEGMENTATION
3.1.1 BUSINESS TO BUSINESS (B2B)
3.1.2 BUSINESS TO CONSUMER (B2C)
3.2 CORE CLOUD SERVICES
3.2.1 INFRASTRUCTURE AS A SERVICE (IAAS)
3.2.2 PLATFORM AS A SERVICE (PAAS)
3.2.3 SOFTWARE AS A SERVICE (SAAS)
3.2.4 DIFFERENCES BETWEEN IAAS, SAAS, AND PAAS
3.3 EMERGING MODELS: XAAS (EVERYTHING AS A SERVICE)
3.3.1 BUSINESS PROCESS AS A SERVICE (BPAAS)
3.3.2 COMMUNICATION AS A SERVICE (CAAS)
3.3.3 MONITORING AS A SERVICE (MAAS)
3.3.4 NETWORK-AS-A-SERVICE (NAAS)
3.3.5 STORAGE AS A SERVICE (SAAS)
3.3.6 DATA AS A SERVICE (DAAS)
3.4 DATA AS A SERVICE ECOSYSTEM
3.4.1 THE DRIVERS OF DATA-AS-A-SERVICE
3.4.2 BUSINESS INTELLIGENCE AND DAAS INTEGRATION
3.4.3 THE CLOUD ENABLER DAAS
3.4.4 XAAS DRIVES DAAS
3.4.5 THE DAAS ECOSYSTEM
3.4.6 DAAS ELEMENTS
3.4.7 THE ROLE OF DATA MARTS
3.4.8 BEST PRACTICES IN DAAS
3.4.9 BENEFITS OF DAAS
3.4.10 CHALLENGES OF DATA AS A SERVICE
3.4.11 APIS AND DATABASE
3.4.12 THE NEED FOR FEDERATED DATABASE MODEL
3.5 ENTERPRISE RESOURCE PLANNING IN THE CLOUD
3.6 SUPPLY CHAIN MANAGEMENT IN THE CLOUD
4.0 INDUSTRY VERTICALS IN THE CLOUD
4.1 FINANCE AND BANKING IN THE CLOUD
4.1.1 AGILITY, EFFICIENCY, AND SIMPLIFIED DELIVERY
4.1.2 PRIORITIZING THE CLOUD
4.2 RETAIL IN THE CLOUD
4.3 HEALTHCARE IN THE CLOUD
4.3.1 KEY BENEFITS OF CLOUD TECHNOLOGY
4.4 TELECOMMUNICATIONS IN THE CLOUD
4.4.1 OPPORTUNITIES AND CHALLENGES
4.4.2 SOLUTIONS
4.5 GOVERNMENT AND DEFENSE IN THE CLOUD
4.5.1 PROS AND CONS OF THE FEDERAL CLOUD
4.6 WORKFORCE IN THE CLOUD
4.6.1 HUMAN CAPITAL MANAGEMENT IN THE CLOUD
4.6.2 TRAINING AND EDUCATION IN THE CLOUD
4.6.3 COLLABORATION IN THE CLOUD
4.6.4 OFFICE AUTOMATION IN THE CLOUD
4.7 CUSTOMERS IN THE CLOUD
4.7.1 CUSTOMER RELATIONSHIP IN THE CLOUD
4.7.2 COMMERCE AND PAYMENTS IN THE CLOUD
4.8 EMERGING CLOUD BASED APPLICATIONS
4.8.1 B2B APPLICATIONS
4.8.2 BIG DATA AS A SERVICE (BDAAS)
4.8.3 B2C APPLICATIONS
4.8.4 ENTERTAINMENT IN THE CLOUD: TV, VIDEO, GAMING AND MORE
4.9 THE FUTURE OF CLOUD SERVICES
4.9.1 EVERYTHING AS A SERVICE
4.9.2 HOW XAAS DECREASES COSTS AND MAKES EVERYTHING FIT TOGETHER
4.10 DATA CENTER PROVIDERS
4.11 VIRTUALIZATION: ROLE AND IMPACT
4.11.1 TYPES OF VIRTUALIZATION
4.11.2 HOW VIRTUALIZATION AFFECTS COST STRUCTURES
5.0 CLOUD APPLICATION SERVICE MARKET FORECAST
5.1 CLOUD SERVICE MARKET REVENUE FORECAST 2015 - 2020
5.2 CLOUD SERVICE MARKET REVENUE BY TPES 2015 - 2020
5.3 CLOUD SERVICE MARKET REVENUE BY CORE SEGMENTS OR MODELS 2015 - 2020
5.4 CLOUD SAAS MARKET REVENUE BY SEGMENTS 2015 - 2020
5.5 CLOUD PAAS MARKET REVENUE BY SEGMENTS 2015 - 2020
5.5.1 CLOUD PAAS MARKET REVENUE BY SUB-SEGMENTS 2015 - 2020
5.6 CLOUD IAAS MARKET REVENUE BY SEGMENTS 2015 - 2020
5.7 PUBLIC CLOUD SERVICES MARKET REVENUE BY SEGMENTS 2015 - 2020
5.7.1 PUBLIC CLOUD MANAGEMENT & SECURITY SERVICES MARKET REVENUE BY SEGMENTS 2015 - 2020
5.7.2 PUBLIC CLOUD BPAAS SERVICES MARKET REVENUE BY SEGMENTS 2015 - 2020
5.8 CLOUD SERVICE MARKET REVENUE BY GEOGRAPHIC REGION 2015 - 2020
5.9 CLOUD APPLICATION SERVICE REVENUE BY INDUSTRY VERTICAL 2015 - 2020
5.10 CLOUD APPLICATION ADOPTION TREND AMONG PERCENT OF ORGANIZATIONS BY DEPLOYMENT MODELS 2015 - 2020
5.11 CLOUD APPLICATION ADOPTION TREND AMONG PERCENT OF ORGANIZATIONS BY INDUSTRY VERTICALS 2015 - 2020
5.12 CLOUD INVESTMENT PERCENT TO INDUSTRY APPLICATIONS 2015
5.13 BENEFITS OF CLOUD APPLICATION SERVICE ADOPTION OVER IN-HOUSE IT SERVICES
5.14 PRIVATE CLOUD STORAGE SUBSCRIPTION FORECAST 2015 - 2020
6.0 CLOUD APPLICATION SERVICE VENDOR ANALYSIS
6.1 OFFICE AUTOMATION APPLICATION
6.1.1 ZOHO
6.1.2 TECHINLINE
6.1.3 WINDOWS LIVE MESH
6.1.4 DROPBOX
6.1.5 LOGMEIN
6.1.6 MICROSOFT OFFICE 365
6.1.7 NOODLE
6.2 CRM APPLICATIONS
6.2.1 ADDRESSTWO
6.2.2 ALLCLIENTS
6.2.3 MAXIMIZER
6.2.4 SALESCLOUD FROM SALESFORCE
6.2.5 SALESNEXUS
6.3 DATA CENTER APPLICATIONS
6.3.1 GOOGLE
6.3.2 MICROSOFT
6.3.3 SWITCH SUPER NAP
6.3.4 RANGE INTERNATIONAL INFORMATION HUB
6.4 CORE CLOUD SERVICE PROVIDERS
6.4.1 AMAZON
6.4.2 VERIZON
6.4.3 IBM
6.4.4 SALESFORCE.COM
6.4.5 CSC
6.4.6 CENTURYLINK
6.4.7 SAVVIS
6.4.8 JOYENT
6.4.9 MICROSOFT
6.4.10 RACKSPACE
6.4.11 FUJITSU
6.4.12 HP
6.5 CLOUD NETWORK OPERATORS
6.5.1 CHINA MOBILE LIMITED
6.5.2 VODAFONE GROUP
6.5.3 TELENOR GROUP
6.5.4 AMERICA MOVIL
6.6 ENTERPRISE CLOUD APPLICATION
6.6.1 SALESFORCE.COM
6.6.2 BOX
6.6.3 CRASHPLAN
6.6.4 AMAZON WEB SERVICES
6.6.5 EASY VISTA
7.0 CARRIER CLOUD OPPORTUNITY
7.1 CLOUD INFRASTRUCTURE AND SERVICES IN TELECOMMUNICATIONS
7.1.1 CLOUD RAN
7.2 MOBILE CONSUMER CLOUD SERVICES
7.2.1 CONSUMER MOBILITY AND THE CLOUD: STATISTICS AND FORECASTS
7.3 COMMERCIAL CONSIDERATIONS
7.3.1 WHAT CONSUMERS WILL STORE IN AND ACCESS FROM THE CLOUD
7.3.2 WHAT DEVICES CONSUMERS WILL USE TO ACCESS THE CLOUD
7.3.3 WHERE AND HOW CONSUMERS WILL ACCESS THE CLOUD
7.3.4 WHAT COMPANIES DO CONSUMERS IDENTIFY WITH CLOUD SERVICES
7.3.5 CONSUMER WILLINGNESS TO PAY FOR PERSONAL CLOUD SERVICES
7.4 KEY CONCERNS AND SOLUTIONS FOR PERSONAL CLOUD SERVICES
7.4.1 LTE AND ANYWHERE, ANYTIME, ANY DEVICE ACCESS
7.4.2 LTE DRIVES CLOUD GROW ACCELERATION VIA USER GENERATED CONTENT (UGC)
7.4.3 DIGITAL RIGHTS MANAGEMENT (DRM)
7.4.4 NETWORK AND DEVICE OPTIMIZATION
7.4.5 CLOUD DATA SECURITY
7.4.6 IDENTITY MANAGEMENT FOR CLOUD SERVICES
7.4.7 CLOUD SERVICES BROKERING AND CLOUD MEDIATION
7.5 MOBILE NETWORK OPERATOR VAS APPLICATION VS. OTT APPLICATIONS
7.6 TELECOM APIS AND THE CLOUD
7.6.1 ROLE OF API'S IN THE CLOUD
7.6.2 ENTERPRISE API PROVIDERS AND CLOUD SERVICES
7.6.3 TELECOM API'S AND THE CLOUD
7.7 GREATER MOBILE CLOUD COMPUTING
7.7.1 BYOC (BRING YOUR OWN CLOUD) AND INCREASED SECURITY
7.8 CARRIER CLOUD SERVICE STRATEGY
7.8.1 CONSUMER CLOUD SERVICES KEY TO GROWTH IN CARRIER DATA SERVICES
7.8.2 CARRIER CLOUD SERVICES TO DRIVE VALUE-ADDED SERVICES GROWTH
7.8.3 PERSONAL CLOUD SERVICES TO IMPROVE CARRIER TOP LINE REVENUE AND PROFITS
7.9 TELECOM BENEFITS OF OFFERING CLOUD SERVICES
7.9.1 VALUE PROPOSITION FOR TELECOM
7.9.2 WEB-BASED APPLICATIONS PROMOTE IT INDEPENDENCE
7.9.3 CLOUD-BASED MANAGED SERVICES PRODUCES REVENUE
7.9.4 INCREASE DATA CENTER EFFICIENCY AND OPERATIONS
7.9.5 DIFFERENTIATING SERVICE PROVIDERS
7.10 CARRIER ADVANTAGES IN CLOUD ECOSYSTEM
7.10.1 SERVICE-ORIENTATION
7.10.2 PERFORMANCE
7.10.3 SECURITY
7.11 CARRIER CHALLENGES
7.11.1 BUSINESS-CLASS SERVICES
7.11.2 STANDARDIZATION
7.11.3 PORTABILITY
7.12 CLOUD BACK UP SERVICES FOR TELECOM
7.12.1 CTERA AND TELECOM ITALIA
7.12.2 HUAWEI AND CHINA TELECOM
7.12.3 HUAWEI PUBLIC CLOUD AND TELKOMSIGMA
7.12.4 HUAWEI PUBLIC CLOUD AND CHINACOMM
7.12.5 HUAWEI DATA CENTER AND VERT BRAZIL
7.12.6 ACRONIS
7.12.7 VODAFONE
7.12.8 OPENSTACK
7.12.9 HP AND NOKIA
7.12.10 ATOS
7.12.11 VOX TELECOM
7.12.12 ZAJIL TELECOM
7.12.13 OSSTELCO
7.13 CLOUD BACKUP SERVICE PROVIDER COMPEITION
7.14 IMPACT OF ICLOUD
8.0 CONCLUSIONS AND RECOMMENDATIONS
8.1 RECOMMENDATIONS
8.1.1 CONTENT DELIVERY NETWORKS (CDN)
8.1.2 MOBILE PERSONAL CLOUD SERVICES
8.1.3 TELECOM OPERATOR

Figures

Figure 1: Cloud Computing Concept
Figure 2: Cloud Service Models
Figure 3: Benefit Chart of Cloud Computing
Figure 4: How Grid Computing Works
Figure 5: Cloud Computing Architecture
Figure 6: Server Virtualization Architecture
Figure 7: Mixed IT Environment
Figure 8: Cloud Professional B2B Service Provider Matrix
Figure 9: Cloud Computing Stack
Figure 10: Deployment Ratio of by Categories of SaaS Application
Figure 11: Difference between IaaS, PaaS, and SaaS
Figure 12: DaaS Ecosystem
Figure 13: Data Value Chain in DaaS Ecosystem
Figure 14: Data Value Chain with Value-added Enrichment
Figure 15 DaaS Elements
Figure 16 DaaS Benefits
Figure 17: Cloud Services and APIs
Figure 18 Cloud ERP vs. On-premise ERP
Figure 19: SCM Cloud Structure
Figure 20: Financial Services in the Cloud
Figure 21: Retail in the Cloud
Figure 22: Telecom Cloud Focus
Figure 23: Cloud Computing in Government and Defense
Figure 24: Office Automation in the Cloud
Figure 25: Cloud Burst of Big Data
Figure 26: Top Themes in the Cloud
Figure 27 Cloud Service Market Revenue 2015 - 2020
Figure 28: Private Cloud Storage Subscription Forecast 2015 - 2020
Figure 29: Datacenter Infrastructure
Figure 30: Virtualization of the Mobile Network
Figure 31: DevOps (Development Operations)
Figure 32: Cloud Radio Access Network (C-RAN)
Figure 33: How People User their Mobile Phone
Figure 34: Personal Content on Home Computer and Mobile Device
Figure 35: IDS1000 AIO 137 Figure 36: IDS1000 cluster

Tables

Table 1: Private Cloud B2C Service Provider Matrix
Table 2: Cloud Service Market Revenue by Private and Public Cloud 2015 - 2020
Table 3: Total Revenue Share by Private vs. Public Cloud Service 2015 - 2020
Table 4: Cloud Service Market Revenue by Core Segments or Models 2015 - 2020
Table 5: Total Revenue Share by SaaS vs. PaaS vs. IaaS 2015 - 2020
Table 6: Cloud Market Revenue by SaaS Segments 2015 - 2020
Table 7: Cloud SaaS Revenue Share by Segments during 2015 - 2020
Table 8: Cloud PaaS Market Revenue by Segments 2015 - 2020
Table 9: Percent of Cloud PaaS Revenue Share by Segments during 2015 - 2020
Table 10 Cloud PaaS Market Revenue by Sub-Segments 2015 - 2020
Table 11: Cloud PaaS Revenue Share by Sub-Segments during 2015 - 2020
Table 12: Cloud IaaS Market Revenue by Segments 2015 - 2020
Table 13: IaaS Cloud Service Market Revenue by Segments during 2015 - 2020
Table 14: Public Cloud Services Market Revenue by Segments 2015 - 2020
Table 15: Public Cloud Service Revenue by Segments during 2015 - 2020
Table 16: Public Cloud Mgt & Security Services Mkt Rev by Segments 2015 - 2020
Table 17: Public Cloud Mgt & Security Services Rev by Segment 2015 - 2020
Table 18: Public Cloud BPaaS Services Market Revenue by Segments 2015 - 2020
Table 19: Public Cloud BPaaS Services Rev by Segment 2015 - 2020
Table 20 Cloud Service Market Revenue by Region 2015 - 2020
Table 21: Cloud Service Market Revenue Share by Region 2015 - 2020
Table 22: Cloud Application Service Revenue by Industry Vertical 2015 - 2020
Table 23: Cloud Application Service Revenue by Industry Verticals 2015 - 2020
Table 24: Cloud Application Adoption Trend by Deployment Models 2015 - 2020
Table 25: Cloud Application Adoption Trend by Industry Verticals 2015 - 2020
Table 26: Cloud Investment in Industry Applications 2015
Table 27: Benefits of Cloud App Service Adoption over In-House IT Services
Table 28: Basic Features or Functionality of Mobile Personal Cloud Services

Social Business Services in the Cloud: Market Analysis and Forecast 2015 – 2020

1.0 EXECUTIVE SUMMARY
2.0 OVERVIEW
2.1 WHAT IS SOCIAL BUSINESS?
2.2 SOCIAL BUSINESS SERVICES AND SAAS SOLUTION
2.3 CLOUD CONVERGENCE WITH SOCIAL TECHNOLOGIES
2.4 CLOUD SOLUTION DEVELOPMENT FOR SOCIAL BUSINESS
2.5 MOBILE, WEARABLE AND ANALYTICS
2.6 SECURITY COMPLIANCE AND NEW STAKEHOLDERS
2.7 SOCIAL CUSTOMER
2.8 ENTERPRISE SOCIAL ADOPTION
2.9 CLOUD SOCIAL COLLABORATION
2.10 SUCCESS PRINCIPLES OF SOCIAL BUSINESS
2.10.1 RECOGNIZE SOCIAL TECHNOLOGY
2.10.2 BUILDING SUCCESS ARCHITECTURE
2.10.3 MULTISTEP APPROACH
2.10.4 TREAT USERS FIRST
2.10.5 STRATEGIC THOUGHT APPROACH
2.11 SOCIAL ENTERPRISE DEPLOYMENT AND CHALLENGES TO ADDRESS
2.12 BUILDING BLOCK TECHNIQUES
2.13 IMPROVING ENTERPRISE SOCIAL CAPABILITIES
2.14 ASSESSING ENTERPRISE SOCIAL CAPABILITIES
2.15 EFFECTIVENESS OF SOCIAL BUSINESS CAPABILITIES
2.15.1 BUSINESS CHALLENGE
2.15.2 SOCIAL CAPABILITIES
2.15.3 BUSINESS OUTCOMES
2.15.4 INDUSTRY NUANCES
2.15.5 TECHNICAL CHALLENGES
2.16 SWOT ANALYSIS
2.16.1 STRENGTHS & OPPORTUNITIES
2.16.2 WEAKNESSES & THREATS
2.17 INDUSTRY VERTICAL
3.0 TECHNOLOGY, APPLICATION AND PROVIDER
3.1 MARKETING AUTOMATION
3.1.1 MARKETO
3.1.2 PARDOT
3.1.3 ELOQUA
3.1.4 CUSTOMER.IO
3.1.5 HUBSPOT
3.1.6 ADROLL
3.1.7 PICA9
3.1.8 CANTERRIS
3.1.9 BREMY
3.1.10 OUTMARKET
3.1.11 BUSSBUILDER PRO
3.1.12 SALESFUSION
3.1.13 GENOO
3.1.14 BIZIBLE
3.1.15 ETRIGUE
3.1.16 ALLOCADIA
3.1.17 SALES ENGINE INTERNATIONAL
3.1.18 ONTRAPORT
3.1.19 LEADSQUARED
3.1.20 MARCOMCENTRAL
3.1.21 AMBASSADOR
3.1.22 INTEGRATE
3.1.23 BRANDMAKER
3.1.24 BUZZPORTAL
3.1.25 ACTIVE CONVERSATION
3.1.26 COMMUNIGATOR
3.1.27 AGILLIC
3.1.28 APRIX SOLUTIONS
3.1.29 DISTRIBION
3.1.30 SALESFORMICS
3.1.31 ELATERAL
3.1.32 CASCADE
3.1.33 GRAVITY FACTOR
3.1.34 BRONTO
3.1.35 GREENROPE
3.1.36 IFBYPHONE
3.1.37 NEXTBEE
3.1.38 ZOHO
3.1.39 ACTIVECAMPAIGN
3.1.40 CONSTANTCONTACT
3.1.41 MAILCHIMP
3.1.42 ASANA
3.1.43 GLIFFY
3.1.44 JUMPLEAD
3.1.45 SIMPLYCAST
3.1.46 DRIP
3.1.47 KENTICO
3.1.48 LEADSIUS
3.1.49 KAHUNA
3.1.50 DEMANDBASE
3.2 SOCIAL MEDIA MANAGEMENT & MONITORING
3.2.1 SUGARCRM
3.2.2 MARKETO
3.2.3 PIPELINEDEALS
3.2.4 SALESFORCE.COM SERVICE CLOUD
3.2.5 SALESFORCE MARKETING CLOUD
3.2.6 ZIPWIRE
3.2.7 SALESOUTLOOK CRM
3.2.8 SMARTTOUCH
3.2.9 CALLIDUSCLOUD MARKETING AUTOMATION
3.2.10 PROPERTYBASE
3.3 ENTERPRISE COLLABORATION & SOCIAL
3.3.1 CO-OP
3.3.2 CYN.IN
3.3.3 CUBETREE
3.3.4 HASHWORK
3.3.5 JAIKU
3.3.6 OBAYOO
3.3.7 PRESENT.LY
3.3.8 QONTEXT
3.3.9 SHARETRONIX
3.3.10 SNIPIA
3.3.11 SOCIALCAST
3.3.12 SOCIALTEXT
3.3.13 SOCIALWOK
3.3.14 STATUS.NET
3.3.15 YAMMER
3.4 WEB EXPERIENCE MANAGEMENT
3.4.1 ADOBE EXPERIENCE MANAGER
3.4.2 ZENDESK
3.4.3 IBM TEALEAF
3.4.4 SATMETRIX
3.4.5 RESPONSETEK
3.4.6 CLICKTALE
3.4.7 KANA
3.4.8 CLARABRIDGE
3.4.9 SAS
3.4.10 GEMIUS
3.4.11 HUBSPOT
3.4.12 MEDALLIA
3.4.13 MAXYMISER
3.4.14 USERZOOM
3.4.15 UX360
3.4.16 USABILITYTOOLS
3.4.17 EKTRON
3.4.18 EZPUBLISH 5
3.4.19 HIPPO CMS 7.8
3.4.20 SDL
3.4.21 OPENTEXT
3.4.22 KENTICO
3.4.23 DRUPAL
3.4.24 COREMEDIA
3.4.25 SITECORE
3.5 INFORMATION GOVERNANCE
3.5.1 ACAVEO
3.5.2 OSTIA
3.5.3 RELTIO
3.6 DIGITAL COMMERCE
3.6.1 ABILITY COMMERCE
3.6.2 BIG COMMERCE
3.6.3 INTUIT ECOMMERCE
3.6.4 SHOPIFY
3.6.5 VENDIO
3.7 CRM & CUSTOMER SUPPORT
3.7.1 SUPPORTCENTER PLUS
3.7.2 ISUPPORT
3.7.3 BLAZEDESK
3.7.4 C-DESK
3.7.5 ACT!
3.7.6 NABD
3.7.7 FUZE SUITE
3.7.8 LIVECHAT
3.7.9 ESERVIZ
3.7.10 HAPPYFOX
3.7.11 MYTIPS
3.7.12 LIVEHELPNOW SUITE
3.7.13 MIGHTYCALL
3.7.14 CHATAROO
3.7.15 CUSTOMANSWERS CRM
3.7.16 ALWAYSUPPORT
3.7.17 CHAT INTERFACE FOR OPERATOR
3.7.18 NICKELLED
3.7.19 OXYGEN SERVICE DESK
3.7.20 ZOHO SURVEY
3.7.21 CUSTOMER SUPPORT SUITE
3.7.22 BOLDCHAT
3.7.23 ACHIEVER CRM
3.7.24 ACTIVATE
3.7.25 AGENDIZE
3.7.26 AGI SELF SERVICE
3.7.27 ALTITUDE UCI SUITE
3.7.28 ANY REQUEST
3.7.29 AURIC PROSPECTOR
3.7.30 BAMBOO CRICKET
3.7.31 BEETRACK
3.7.32 BRAND EMBASSY
3.7.33 CARECALL
3.7.34 CASENGO
3.7.35 CCS CUSTOMER SERVICE
3.7.36 CINCOM SYNCHRONY
3.7.37 CLICKDESK
3.7.38 CLOSE SUPPORT
3.7.39 CLOUD 9 SUPPORT
3.7.40 COGNITIVE VIRTUAL ASSISTANT
3.7.41 COMARCH NGSF
3.7.42 COMM100 HELP DESKVIEW PROFILE
3.7.43 COMMUNICATIONS CENTER
3.7.44 CONSUMER RELATIONSHIP SYSTEM
3.7.45 CONVERSOCIAL
3.7.46 COVEO FOR CUSTOMER SERVICE & CRM
3.7.47 CRM EXPRESS
3.7.48 CRMDESK
3.7.49 CRMUNLEASHED
3.7.50 CUSTOMER CENTRIC FRAMEWORK
3.7.51 CUSTOMER EXPERIENCE MANAGEMENT
3.7.52 CUSTOMER SERVICE HELP DESK
3.7.53 CUSTOMERFIRST
3.7.54 E-TRACK
3.7.55 ECOMMSOURCE
3.7.56 EGAIN SUITE
3.7.57 EPTICA ENTREPRISE SUITE
3.8 ECM & FILE SHARING
3.8.1 ACRONIS ACTIVECHO
3.8.2 CITRIX SHAREFILE
3.8.3 DRUVA INSYNC
3.8.4 EGNYTE BUSINESS FILE SHARING
3.8.5 EMC SYNCPLICITY
3.8.6 HYLAND SOFTWARE
3.8.7 IBM
3.8.8 MICROSOFT
3.8.9 OPENTEXT
3.8.10 PERCEPTIVE SOFTWARE
3.8.11 HUDDLE
3.8.12 OXYGEN CLOUD
3.9 WORKFORCE MANAGEMENT
3.9.1 CHETU
3.9.2 CERIDIAN
3.9.3 ORACLE
3.9.4 SAP/SUCCESSFACTORS
3.9.5 IBM / KENEXA
3.9.6 INFOR
3.9.7 ULTIMATE SOFTWARE
3.9.8 WORKDAY
3.9.9 PEOPLEFLUENT
3.9.10 ADP
3.9.11 SILKROAD
3.9.12 SABA
3.9.13 FINANCIALFORCE HCM
3.9.14 HRSOFT
3.9.15 LUMESSE
3.9.16 KRONOS
3.9.17 SUMTOTAL SYSTEMS
3.9.18 HALOGEN
3.9.19 CORNERSTONE ONDEMAND
3.9.20 BENEFITFOCUS EENROLLMENT
3.9.21 PAYCOM
3.9.22 PAYLOCITY
4.0 MARKET PROJECTIONS 2015 – 2020
4.1 GLOBAL SOCIAL CLOUD BUSINESS APPLICATION MARKET 2015 – 2020
4.2 SOCIAL CLOUD BUSINESS APPLICATION MARKET BY INDUSTRY SEGMENT 2015 - 2020
4.3 SOCIAL CLOUD BUSINESS APPLICATION MARKET BY DEVELOPMENT PLATFORM 2015 – 2020
4.4 SOCIAL CLOUD BUSINESS APPLICATION MARKET BY BUSINESS MODEL 2015 – 2020
4.5 SOCIAL CLOUD BUSINESS APPLICATION MARKET BY GEOGRAPHIC SEGMENT 2015 – 2020
4.6 ENTERPRISE ADOPTION RATE OF SOCIAL BUSINESS SERVICES 2015 - 2020
4.7 SOCIAL BUSINESS APPLICATION MAJOR VENDOR REVENUE FORECAST 2015 – 2020
5.0 ECOSYSTEM ANALYSIS
5.1 VENDOR
5.2 CLOUD SERVICE PROVIDERS
5.3 SOCIAL MEDIA NETWORK
5.4 END USER
5.5 SOFTWARE MANUFACTURER
5.6 GOVERNMENT
5.7 TELECOMMUNICATION
6.0 VENDOR ANALYSIS
6.1 IBM
6.1.1 IBM SMARTCLOUD
6.1.2 IBM SMARTCLOUD ORCHESTRATOR
6.1.3 IBM CONNECTIONS AND IBM NOTES AND DOMINO SOCIAL EDITION 9
6.1.4 SWOT ANALYSIS
6.2 SALESFORCE
6.2.1 CHATTER
6.2.2 SALESFORCE SOCIAL CRM
6.3 MICROSOFT
6.3.1 MICROSOFT OFFICE 365 AND CONNECTED EXPERIENCE
6.3.2 PUBLIC CLOUD - WINDOWS AZURE
6.3.3 PRIVATE CLOUD - WINDOWS SERVER AND SYSTEMS CENTER
6.3.4 MICROSOFT DYNAMICS CRM ONLINE
6.3.5 SHAREPOINT 2013
6.3.6 MICROSOFT SKYDRIVE
6.3.7 ORANGE AND MICROSOFT CLOUD PARTNERSHIP CASE
6.4 YAMMER
6.4.1 YAMMER AND OFFICE 365
6.4.2 YAMMER AND SHAREPOINT SERVER
6.4.3 SWOT ANALYSIS
6.5 NEWSGATOR
6.5.1 SUCCESS CASE WITH ACCENTURE
6.5.2 SUCCESS CASE WITH CME FEDERAL CREDIT UNION
6.5.3 SUCCESS CASE WITH AMERICAN FAMILY INSURANCE
6.6 JIVE
6.6.1 JIVE SOCIAL BUSINESS PLATFORM
6.6.2 SWOT ANALYSIS
6.6.3 SUCCESS CASE OF JIVE SOCIAL INTRANET WITH ALCATEL-LUCENT
6.6.4 SUCCESS CASE WITH LIVEPERSON
6.7 TELLIGENT
6.7.1 SUCCESS CASE WITH DELL
6.8 SOCIALTEXT
6.8.1 SWOT ANALYSIS
6.9 MZINGA
6.9.1 MZINGA OMNISOCIAL
6.10 COMMUNISPACE
6.10.1 FULL-SERVICE SOLUTION
6.10.2 BULLYING PREVENTION CAMPAIGN CASE
6.11 LITHIUM
6.11.1 LITHIUM SOCIAL WEB: THE SOCIAL CUSTOMER EXPERIENCE PLATFORM
6.11.2 SOCIAL SOLUTIONS FOR MARKETING, COMMERCE AND SUPPORT
6.12 SUCCESSFACTORS: AN SAP COMPANY
6.12.1 SUCCESSFACTORS BIZX SUITE
6.12.2 SUCCESS CASE WITH SIEMENS
6.13 CITRIX
6.13.1 GOTO CLOUD SERVICES
6.14 ORACLE SOCIAL SERVICES
6.15 SABA POOPLE CLOUD
6.16 CISCO WEBEX SOCIAL
6.16.1 SWOT ANALYSIS
6.17 POKESHOT///SMZ
6.17.1 PUBLIC SECTOR COMMUNITY
6.17.2 POKESHOT///SMARTERPATH
6.17.3 TRANSLATION MANAGER
6.17.4 SOCIAL CONNECTOR FOR CISCO, SAMETIME AND LOTUS NOTES
6.17.5 SECURITY EXTENSION
7.0 CASE STUDY ANALYSIS OF SUCCESS SCENARIOS
7.1 LINKEDIN ONLINE RECRUITMENT BUSINESS
7.2 FACEBOOK AND TWITTER CASE AS ENABLER
7.3 RESTAURANT BUSINESS CASE ON PT BAMBU DESA
7.4 SATEL OY AND FORD CASE
7.5 CLIMATE ASIA PACIFIC CASE
7.6 OXFAM CASE ON ADVOCACY THROUGH SOCIAL MEDIA
7.7 ASSIST CASE ON SOCIAL CAPACITY BUILDING
7.8 FERRING ITALY SPA IMPLEMENTATION CASE
8.0 CONCLUSIONS AND RECOMMENDATIONS
8.1 RECOMMENDATION FOR VENDORS
8.2 RECOMMENDATION FOR ORGANIZATIONS

Figures

Figure 1: Reasons of Cloud Computing Adoption to Social Businesses
Figure 2: Social Customer Conversion Ecosystem
Figure 3: Building Block Techniques for Social Business Capabilities
Figure 4: Social Collaboration Component and Business Activities Part 1
Figure 5: Social Collaboration Component and Business Activities Part 2
Figure 6: Social Collaboration Component and Business Activities Part 3
Figure 7: Parameters to Assess Social Business Capabilities
Figure 8: Sample List of Business Outcomes
Figure 9: Industry vs. Nuance
Figure 10: Major Obstacles of Cloud Based Social Business Services
Figure 11: Global Social Cloud Bus App Market by Enterprise Spend 2015 – 2020
Figure 12: Enterprise Social Business App at Least One 2015 – 2020
Figure 13: Vendor in Social Business Services in Cloud Ecosystem
Figure 14: Engagement Ratios by Internal, External, and Unified Social Network
Figure 15: Market Share of Major Social Networking Media
Figure 16: IBM’s Investment for Business Partner Growth
Figure 17: SaleForce Solution Dimensions for Social Business
Figure 18: Salesforce Chatter Dynamic Interface
Figure 19: Upcoming Enhanced Experience with Yammer Social & Office 365
Figure 20: Jive Social Business Platform
Figure 21: Full-Service Solution Sketch
Figure 22: Interface of Bullying Prevention Campaign Site
Figure 23: Lithium Social Customer Experience Platform

Tables

Table 1: Global Social Cloud Business App Market by Segment 2015 – 2020
Table 2: Social Cloud Business App Market by Major Functions 2015 – 2020
Table 3: Social Cloud Bus App Market by Desktop, Mobile & Platform 2015 – 2020
Table 4: Social Cloud Business App Market SaaS vs. PaaS Model 2015 – 2020
Table 5: Social Cloud Business App Market Region 2015 – 2020
Table 6: Social Business App Major Vendor Revenue Projection 2015 – 2020
Table 7: Government Cost Reduction due to Social Cloud Business 2015 – 2018

Big Data Market: Business Case, Market Analysis & Forecasts 2015 - 2020

1 Introduction 10
1.1 Executive Summary 10
1.2 Topics Covered 12
1.3 Key Findings 13
1.4 Target Audience 14
1.5 Companies Mentioned 15
2 Big Data Technology & Business Case 20
2.1 Defining Big Data 20
2.2 Key Characteristics of Big Data 21
2.2.1 Volume 21
2.2.2 Variety 22
2.2.3 Velocity 22
2.2.4 Variability 23
2.2.5 Complexity 23
2.3 Big Data Technology 24
2.3.1 Hadoop 24
2.3.2 Other Apache Projects 26
2.3.3 NoSQL 26
2.3.3.1 Hbase 27
2.3.3.2 Cassandra 27
2.3.3.3 Mongo DB 28
2.3.3.4 Riak 28
2.3.3.5 CouchDB 28
2.3.4 MPP Databases 28
2.3.5 Others and Emerging Technologies 29
2.3.5.1 Storm 29
2.3.5.2 Drill 29
2.3.5.3 Dremel 29
2.3.5.4 SAP HANA 29
2.3.5.5 Gremlin & Giraph 30
2.3.6 New Paradigms and Techniques 30
2.3.6.1 Streaming Analytics 30
2.3.6.2 Cloud Technology 30
2.3.6.3 Google Search 30
2.3.6.4 Customize Analytical Tools 31
2.3.6.5 Internet Keywords 31
2.3.6.6 Gamification 32
2.4 Big Data Roadmap 34
2.5 Market Drivers 36
2.5.1 Data Volume & Variety 36
2.5.2 Increasing Adoption of Big Data by Enterprises and Telecom 36
2.5.3 Maturation of Big Data Software 36
2.5.4 Continued Investments in Big Data by Web Giants 36
2.5.5 Business Drivers 37
2.6 Market Barriers 38
2.6.1 Privacy and Security: The ‘Big’ Barrier 38
2.6.2 Workforce Re-skilling and Organizational Resistance 38
2.6.3 Lack of Clear Big Data Strategies 39
2.6.4 Technical Challenges: Scalability & Maintenance 39
2.6.5 Big Data Development Expertise 39
3 Key Investment Sectors for Big Data 40
3.1 Industrial Internet and Machine-to-Machine 40
3.1.1 Big Data in M2M 40
3.1.2 Vertical Opportunities 40
3.2 Retail and Hospitality 40
3.2.1 Improving Accuracy of Forecasts & Stock Management 41
3.2.2 Determining Buying Patterns 41
3.2.3 Hospitality Use Cases 41
3.2.4 Personalized Marketing 42
3.3 Media 44
3.3.1 Social Media 44
3.3.2 Social Gaming Analytics 44
3.3.3 Usage of Social Media Analytics by Other Verticals 45
3.3.4 Internet Keyword Search 45
3.4 Utilities 47
3.4.1 Analysis of Operational Data 47
3.4.2 Application Areas for the Future 47
3.5 Financial Services 48
3.5.1 Fraud Analysis, Mitigation & Risk Profiling 48
3.5.2 Merchant-Funded Reward Programs 48
3.5.3 Customer Segmentation 48
3.5.4 Customer Retention & Personalized Product Offering 48
3.5.5 Insurance Companies 50
3.6 Healthcare and Pharmaceutical 50
3.6.1 Drug Development 50
3.6.2 Medical Data Analytics 50
3.6.3 Case Study: Identifying Heartbeat Patterns 50
3.7 Telecommunications 51
3.7.1 Telco Analytics: Customer/Usage Profiling and Service Optimization 51
3.7.2 Big Data Analytic Tools 51
3.7.3 Speech Analytics 52
3.7.4 New Products and Services 52
3.8 Government and Homeland Security 53
3.8.1 Big Data Research 53
3.8.2 Statistical Analysis 55
3.8.3 Language Translation 55
3.8.4 Developing New Applications for the Public 56
3.8.5 Tracking Crime 56
3.8.6 Intelligence Gathering 56
3.8.7 Fraud Detection & Revenue Generation 56
3.9 Other Sectors 58
3.9.1 Aviation 58
3.9.2 Transportation & Logistics: Optimizing Fleet Usage 58
3.9.3 Sports: Real-Time Processing of Statistics 59
3.9.4 Education 59
3.9.5 Manufacturing 60
4 The Big Data Value Chain 66
4.1 How Fragmented is the Big Data Value Chain? 66
4.2 Data Acquisitioning & Provisioning 67
4.3 Data Warehousing & Business Intelligence 67
4.4 Analytics & Virtualization 67
4.5 Actioning and Business Process Management 68
4.6 Data Governance 68
5 Big Data Analytics 69
5.1 What is Big Data Analytics? 69
5.2 The Importance of Big Data Analytics 70
5.3 Reactive vs. Proactive Analytics 71
5.4 Technology and Implementation Approaches 73
5.4.1 Grid Computing 73
5.4.2 In-Database processing 73
5.4.3 In-Memory Analytics 75
5.4.4 Data Mining 75
5.4.5 Predictive Analytics 77
5.4.6 Natural Language Processing 80
5.4.7 Text Analytics 84
5.4.8 Visual Analytics 85
5.4.9 Association rule learning 86
5.4.10 Classification tree analysis 87
5.4.11 Machine Learning 87
5.4.11.1 Neural networks 88
5.4.11.2 Multilayer Perceptron (MLP) 89
5.4.11.3 Radial Basis Functions 90
5.4.11.4 Support vector machines 90
5.4.11.5 Naïve Bayes 90
5.4.11.6 k-nearest neighbors 91
5.4.11.7 Geospatial predictive modelling 92
5.4.12 Regression Analysis 92
5.4.13 Social Network Analysis 93
6 Standardization and Regulatory Initiatives 94
6.1 Cloud Standards Customer Council – Big Data Working Group 94
6.2 National Institute of Standards and Technology – Big Data Working Group 95
6.3 OASIS 96
6.4 Open Data Foundation 98
6.5 Open Data Center Alliance 99
6.6 Cloud Security Alliance – Big Data Working Group 100
6.7 International Telecommunications Union 101
6.8 International Organization for Standardization 101
6.9 International Organization for Standardization) 101
7 Key Players in the Big Data Market 102
7.1 Vendor Assessment Matrix 102
7.2 1010Data 102
7.3 Actuate Corporation 103
7.4 Accenture 103
7.5 Amazon 103
7.6 Apache Software Foundation 104
7.7 APTEAN (Formerly CDC Software) 104
7.8 Booz Allen Hamilton 104
7.9 Cap Gemini 105
7.10 Cisco Systems 105
7.11 Cloudera 105
7.12 Computer Science Corporation 105
7.13 DataDirect Network 106
7.14 Dell 107
7.15 Deloitte 107
7.16 EMC 107
7.17 Facebook 107
7.18 Fujitsu 108
7.19 General Electric 109
7.20 GoodData Corporation 110
7.21 Google 110
7.22 Guavus 110
7.23 Hitachi Data Systems 111
7.24 Hortonworks 111
7.25 HP 111
7.26 IBM 112
7.27 Informatica 112
7.28 Intel 112
7.29 Jaspersoft 112
7.30 Juniper Networks 113
7.31 Marklogic 113
7.32 Microsoft 114
7.33 MongoDB (Formerly 10Gen) 114
7.34 MU Sigma 114
7.35 Netapp 115
7.36 NTT Data 115
7.37 Opera Solutions 116
7.38 Oracle 116
7.39 Pentaho 116
7.40 Platfora 116
7.41 Qliktech 117
7.42 Quantum 117
7.43 Rackspace 117
7.44 Revolution Analytics 117
7.45 Salesforce 118
7.46 SAP 118
7.47 SAS Institute 118
7.48 Sisense 119
7.49 Software AG/Terracotta 119
7.50 Splunk 119
7.51 Sqrrl 120
7.52 Supermicro 120
7.53 Tableau Software 120
7.54 Tata Consultancy Services 121
7.55 Teradata 121
7.56 Think Big Analytics 121
7.57 TIBCO 121
7.58 Tidemark Systems 122
7.59 VMware (Part of EMC) 122
7.60 Wipro 122
7.61 Zettics 123
8 Market Analysis 124
8.1 Big Data Revenue 2014 - 2020 124
8.2 Big Data Revenue by Functional Area 2014 - 2020 125
8.2.1 Supply Chain Management 126
8.2.2 Business Intelligence 127
8.2.3 Application Infrastructure & Middleware 128
8.2.4 Data Integration Tools & Data Quality Tools 129
8.2.5 Database Management Systems 130
8.2.6 Big Data Social & Content Analytics 131
8.2.7 Big Data Storage Management 132
8.2.8 Big Data Professional Services 133
8.3 Big Data Revenue by Region 2014 - 2020 134
8.3.1 Asia Pacific 135
8.3.2 Eastern Europe 136
8.3.3 Latin & Central America 137
8.3.4 Middle East & Africa 138
8.3.5 North America 139
8.3.6 Western Europe 140

Figures

Figure 1: NoSQL vs Legacy DB Performance Comparisons 27
Figure 2: 2014 Gartner Hype Cycle for Emerging Technologies 34
Figure 3: Roadmap Big Data Technologies 2014 - 2030 35
Figure 4: The Big Data Value Chain 66
Figure 5: Big Data Vendor Ranking Matrix 102
Figure 6: Big Data Revenue 2013 – 2020 124
Figure 7: Big Data Revenue by Functional Area 2013 – 2020 125
Figure 8: Big Data Supply Chain Management Revenue 2013 – 2020 126
Figure 9: Big Data Supply Business Intelligence Revenue 2013 – 2020 127
Figure 10: Big Data Application Infrastructure & Middleware Revenue 2013 – 2020 128
Figure 11: Big Data Integration and Quality Tools Revenue 2013 – 2020 129
Figure 12: Big Data DB Management Systems Revenue 2013 – 2020 130
Figure 13: Big Data Social & Content Analytics Revenue 2013 – 2020 131
Figure 14: Big Data Storage Management Revenue 2013 – 2020 132
Figure 15: Big Data Professional Services Revenue 2013 – 2020 133
Figure 16: Big Data Revenue by Region 2013 – 2020 134
Figure 17: Asia Pacific Big Data Revenue 2013 – 2020 135
Figure 18: Eastern Europe Big Data Revenue 2013 – 2020 136
Figure 19: Latin & Central America Big Data Revenue 2013 – 2020 137
Figure 20: Middle East & Africa Big Data Revenue 2013 – 2020 138
Figure 21: North America Big Data Revenue 2013 – 2020 139
Figure 22: Western Europe Big Data Revenue 2013 – 2020 140

Mobile Application Marketplace 2015: Market Analysis and Assessment of Future Evolution and Opportunities

1 Introduction 9
1.1 Executive Summary 9
1.2 Target Audience 12
1.3 Companies Mentioned 13
2 Mobile Applications Overview 16
2.1 Definition of a Mobile Applications 17
2.2 What Separates an App From a Bundled Device Feature? 18
2.3 Examples of Current Mobile Apps 18
3 Mobile Platforms (Operating Systems) 21
3.1 OHA Android (free and open source) 21
3.2 iOS from Apple 25
3.3 BlackBerry 10 from RIM 29
3.4 Windows Mobile from Microsoft 29
3.5 BlackBerry OS from RIM 31
3.6 BREW from Qualcomm 33
3.7 Symbian OS from Nokia and Accenture 33
3.8 Firefox OS from Mozilla Foundation 34
3.9 Sailfish OS from Jolla 34
3.10 TIZEN from the Linuz Foundation 36
3.11 Ubuntu from Canonical Ltd. 38
4 Mobile Programming 39
4.1 Widgets 39
4.2 Hardware Widgets 40
4.3 Hardware and Software Evolution 42
4.3.1 Hardware Evolution and Handset Manufacturers Market Share 42
4.3.2 The Smartphone Revolution 47
4.3.3 Development Platforms 48
4.3.4 HTML5 49
4.3.5 HTML and Mini Browsers 53
4.3.6 Adobe, Flash, and SilverLight 53
4.3.7 JavaScript 53
4.3.8 AJAX 54
4.3.9 Future Directions of Mobile Development 55
5 Application Development Platforms 57
5.1 J2ME Platform 58
5.2 Platform Specific 59
5.2.1 iOS SDK 60
5.2.2 Blackberry OS Development Tools 60
5.2.3 Nokia Development Tools 61
5.2.4 Motorola Development Tools 61
5.2.5 LG Development Tools 62
5.2.6 Samsung Development Tools 62
5.2.7 HTC Development Tools 62
5.2.8 Sony Ericsson Development Tools 63
5.2.9 Android Development Tools 63
6 Key Development Concepts 64
6.1 Mobile Development Trends 64
6.1.1 Platforms 65
6.1.2 Programming Techniques 65
6.1.3 Mobile Optimization 68
6.1.4 Software Development Methodology 69
6.2 Native Programming Techniques 69
6.2.1 Size Constraints 69
6.2.1.1 Compact Code 70
6.2.1.2 Compact File Space 70
6.2.2 Display Constraints 70
6.2.2.1 Display Sizes and Standards 71
6.2.2.2 Multiple Displays 71
6.2.3 Input and Controls 72
6.2.3.1 Input device types 72
6.2.3.2 Keyboard 73
6.2.3.3 Touch Screen 73
6.2.3.4 Thumb Sticks, Roller Balls, and Direction Pads. 75
6.2.3.5 Environmental Controls 75
6.2.3.6 Motion and Orientation Sensors 75
6.2.3.7 Light Sensors 75
6.2.3.8 Proximity Sensor 76
6.2.3.9 Gyroscope 76
6.2.3.10 Accelerometer 76
6.2.3.11 Peripheral Access 77
6.2.3.12 GPS Onboard and Off 77
6.2.3.13 Bluetooth 77
6.2.3.14 Near Field Communication and S Beam 78
6.2.3.15 Touch ID 79
6.2.3.16 Stylus Pen 80
6.3 Network Access 81
6.3.1 Connection Persistence 81
6.3.2 Dial on Demand 81
6.3.3 Always On 82
6.3.4 Connection Types and Limitations 82
6.3.5 Cellular Data 83
6.3.6 WiFi 83
6.3.7 Bluetooth 84
6.3.8 Bluetooth Low Energy (BLE) 84
6.3.9 Processing 88
6.3.10 Platforms and Speeds 88
7 Mobile Application Market 90
7.1 Mobile Advertising 92
7.2 Market Summary 93
8 Application Store Case Studies 100
8.1 Case Study Blackberry (RIM) 100
8.2 Case Study Apple 105
8.3 Case Study Android 110
8.4 Case Study: Amazon App Store 113
8.5 Case Study Windows App Store 115
9 Market Size 116
9.1 Mobile Application Overall Market 116
9.2 Mobile Sales Potential 117
9.3 Forecasted Smart Phone Sales 118
9.4 Growth Indicators 119
9.5 Market Analysis 122
9.6 Application Store Market Performance 124
9.6.1 Apple App Store 124
9.6.2 Android Marketplace Analysis 126
10 Mobile Gaming Analytics 131
10.1.1 Monetizing Micro Transaction in F2P Model: Creating a Need Approach is Key 137
10.1.2 Game Balancing Method in Micro Transaction Model 137
10.1.3 Potential Risk and Solution in F2P Virtual Economy 138
10.1.4 Pricing Decision Factors: ARPU vs. Average game price vs. Average Gamers 141
10.1.5 Product Life Cycle of Mobile Game: Adoption of Moore’s Lifecycle Model 142
10.1.6 Game Lifecycle KPI framework 144
10.1.7 Smartphones vs. Portable Game Players 145
11 Wearable Devices Apps and Future Apps 146
11.1 Fitness Apps 147
11.2 Wearable Devices Payment Apps 149
11.3 Future Wearables Apps 151
11.3.1 Military Applications 151
11.3.2 Industry and Enterprise Applications 152
11.3.3 A Day in the Life of a Celebrity App 153
11.3.4 In my Glass 154
12 Carrier and Vendor Adaptations 156
12.1 Topology and Network Changes 156
12.1.1 Policy Changes 156
12.1.2 Open Network Movements 157
12.1.3 Billing Plan Changes 157
12.1.4 Infrastructure Hardware Changes 158
12.1.5 Location Based Services 158
12.1.6 WiFi Localized Service Hosting 158
12.1.7 Handset Manufacturer Changes 159
12.1.8 Integrating New Handset Features 159
12.1.9 Evolving the Handset 160
12.1.10 Multiple Platform Mobile Operating Systems 160
13 App Publishers Analysis 161
13.1 Gameloft 161
13.2 GungHo Online 162
13.3 Electronic Arts 163
13.4 Zynga 164
13.5 DeNA 164
13.6 SEGA 165
13.7 King 166
14 Future of Mobile Applications 167
14.1 Communication Enabled Apps 167
14.1.1 Direct API Revenue 167
14.1.2 Data Monetization 168
14.1.3 Cost Savings 168
14.1.4 Higher Usage 168
14.1.5 Churn Reduction 169
14.2 Embedded Entertainment and Gamified Apps 169
14.2.1 Gamification 169
14.2.2 Wearable Gamification 170
14.2.3 Mobile Social Gamification 170
14.2.4 Cloud Gamification 171
14.3 Cross Platform Apps 171
14.3.1 Smartphones, Tablets, Wearable Tech and More 172
14.3.2 Mobile/Wireless Apps Everywhere 174
14.4 The Impact of SMAC 176
14.4.1 Social, Mobile, Analytics, and Cloud (SMAC) 176
14.4.2 SMAC Stack 177
14.4.3 SMAC and Enterprise Mobile Market and Apps 177

Tables

Table 1: Example of the Most Successful Apps 19
Table 2: Apps Revenues in Apple App and Google Play Stores 20
Table 3: Handsets Manufacturer Market Share 46
Table 4: Mobile/Tablet Browser Share 50
Table 5: Mobile Platform Market Share 2012 - 2020 97
Table 6: Smartphone Market SWOT 123
Table 7: Key Considerable Mobile Gaming Strategies 132
Table 8: Mobile Gaming Business Model Descriptions 133
Table 9 Game Balancing Methods in Virtual Economy 138
Table 10: Potential Risk & Solution in F2P Virtual Economy 139
Table 11: Revenue vs. Costs in Gaming App Business 140
Table 12: Gameloft most Successful Apps 161
Table 13: Gungho Online Entertainment, Inc most Successful Apps 162
Table 14: EA most Successful Apps 163
Table 15: Zynga most Successful Apps 164
Table 16: DeNa Most Successful Apps 165
Table 17: SEGA Most Successful App 165
Table 18: King Applications 166

Figures

Figure 1: iPhone 6 and iPhone 6 Plus 26
Figure 2: iOS 8 28
Figure 3: Windows Phone 8 from Nokia 30
Figure 4: BlackBerry Z10 32
Figure 5: First Mobile Widgets 40
Figure 6: Early Mobile Widgets and Hardware 41
Figure 7: The Rise of the Smartphones Era 48
Figure 8: Classic Web App vs. Ajax Web Application Model 55
Figure 9: Samsung Note Edge 72
Figure 10: Multi-touch Screen 74
Figure 11: Touch ID 80
Figure 12: Blackberry OS 10.1 102
Figure 13: Amazon App Store 114
Figure 14: Apple App Store vs. iTunes Music Sales 125
Figure 15: Mobile Gaming Business Models 136
Figure 16: Monetizing Micro-Transaction in F2P model 137
Figure 17: Adoption of Moore’s Lifecycle Model in Mobile Gaming 142
Figure 18: Sequential Steps of Mobile Game Analytic Approach 143
Figure 19: Mobile Game Lifecycle KPI Framework 144
Figure 20: Apple Watch Payments using NFC 151
Figure 21: A Day in a Life of a Celebrity 154
Figure 22: Mobile App Store Framework 175

Data as a Service (DaaS) Market and Forecasts 2015 – 2020

1 Introduction 8
1.1 Executive Summary 8
1.2 Topics Covered 10
1.3 Key Findings 11
1.4 Target Audience 12
2 DaaS Technologies 13
2.1 Cloud 13
2.2 Database Approaches and Solutions 14
2.2.1 Relational Database Management System (RDBS) 14
2.2.2 NoSQL 15
2.2.3 Hadoop 16
2.2.4 High Performance Computing Cluster (HPCC) 18
2.2.5 OpenStack 19
2.3 DaaS and the XaaS Ecosystem 19
2.4 Open Data Center Alliance 22
2.5 Market Sizing by Horizontal 23
3 DaaS Market 25
3.1 Market Overview 25
3.1.1 Data-as-a-Service: A movement 27
3.1.2 Data Structure 27
3.1.3 Specialization 28
3.1.4 Vendors 30
3.2 Vendor Analysis and Prospects 31
3.2.1 Large Vendors: BDaaS 31
3.2.2 Mid-sized Vendors 35
3.2.3 Small Vendors: DaaS and SaaS 37
3.2.4 Market Size: BDaaS vs. RDBMS 38
3.3 Market Drivers and Constraints 39
3.3.1 Drivers 39
3.3.1.1 Business Intelligence and DaaS Integration 42
3.3.1.2 The Cloud Enabler DaaS 44
3.3.1.3 XaaS Drives DaaS 44
3.3.2 Constraints 44
3.3.2.1 Issues Relating to Data-as-a-Service Integration 47
3.4 Barriers and Challenges to DaaS Adoption 48
3.4.1 Enterprises Reluctance to Change 48
3.4.2 Responsibility of Data Security Externalized 49
3.4.3 Security Concerns are Real 49
3.4.4 Cyber Attacks 50
3.4.5 Unclear Agreements 51
3.4.6 Complexity is a Deterrent 53
3.4.7 Lack of Cloud Interoperability 54
3.4.8 Service Provider Resistance to Audits 55
3.4.9 Viability of Third-party Providers 56
3.4.10 No Move of Systems and Data is without Cost 57
3.4.11 Lack of Integration Features in the Public Cloud results in Reduced Functionality 58
3.5 Market Share and Geographic Influence 58
3.6 Vendors 61
3.6.1 1010data 62
3.6.2 Amazon 62
3.6.3 Clickfox 65
3.6.4 Datameer 66
3.6.5 Google 66
3.6.6 Hewlett-Packard 68
3.6.7 IBM 69
3.6.8 Infosys 70
3.6.9 Microsoft 71
3.6.10 Oracle 71
3.6.11 Rackspace 72
3.6.12 Salesforce 73
3.6.13 Splunk 74
3.6.14 Teradata 74
3.6.15 Tresata 76
4 DaaS Strategies 77
4.1 General Strategies 77
4.1.1 Tiered Data Focus 77
4.1.2 Value-based Pricing 79
4.1.3 Open Development Environment 80
4.2 Specific Strategies 81
4.2.1 Service Ecosystem and Platforms 81
4.2.2 Bringing to Together Multiple Sources for Mash-ups 82
4.2.3 Developing Value-added Services (VAS) as Proof Points 83
4.2.4 Open Access to all Entities including Competitors 83
4.2.5 Prepare for Big Opportunities with the Internet of Things (IoT) 84
4.3 Service Provider Strategies 88
4.3.1 Telecom Network Operators 88
4.3.2 Data Center Providers 96
4.3.3 Managed Service Providers 97
4.4 Infrastructure Provider Strategies 98
4.4.1 Enable New Business Models 98
4.5 Application Developer Strategies 99
5 DaaS based Applications 100
5.1 Business Intelligence 100
5.2 Development Environments 103
5.3 Verification and Authorization 104
5.4 Reporting and Analytics 105
5.5 DaaS in Healthcare 106
5.6 DaaS and Wearable technology 107
5.7 DaaS in the Government Sector 107
5.8 DaaS for Media and Entertainment 108
5.9 DaaS for Telecoms 109
5.10 DaaS for Insurance 110
5.11 DaaS for Utilities and Energy Sector 110
5.12 DaaS for Pharmaceuticals 111
5.13 DaaS for Financial Services 111
6 Market Outlook and Future of DaaS 113
6.1 Recent Security Concerns 113
6.2 Cloud Trends 116
6.2.1 Hybrid Computing 117
6.2.2 Multi-Cloud 118
6.2.3 Cloud Bursting 119
6.3 General Data Trends 121
6.4 Enterprise Leverages own Data and Telecom 123
6.4.1 Web APIs 123
6.4.2 SOA and Enterprise APIs 125
6.4.3 Cloud APIs 127
6.4.4 Telecom APIs 128
6.5 Data Federation Emerges for DaaS 130
7 Conclusions 138
8 Appendix 141
8.1 Structured vs. Unstructured Data 141
8.1.1 Structured Database Services in Telecom 141
8.1.2 Unstructured Database Services in Telecom and Enterprise 143
8.1.3 Emerging Hybrid (Structured/Unstructured) Database Services 143
8.2 Data Architecture and Functionality 146
8.2.1 Data Architecture 146
8.2.1.1 Data Models and Modelling 147
8.2.1.2 DaaS Architecture 148
8.2.2 Data Mart vs. Data Warehouse 150
8.2.3 Data Gateway 151
8.2.4 Data Mediation 151
8.3 Master Data Management (MDM) 155
8.3.1 Understanding MDM 156
8.3.1.1 Transactional vs. Non-transactional Data 157
8.3.1.2 Reference vs. Analytics Data 157
8.3.2 MDM and DaaS 157
8.3.2.1 Data Acquisition and Provisioning 158
8.3.2.2 Data Warehousing and Business Intelligence 159
8.3.2.3 Analytics and Virtualization 160
8.3.2.4 Data Governance 160
8.4 Data Mining 161
8.4.1 Data Capture 163
8.4.1.1 Event Detection 165
8.4.1.2 Capture Methods 165
8.4.2 Data Mining Tools 168

Figures

Figure 2: Cloud Computing Service Model Stack and Principle Consumers 20
Figure 3: DaaS across Horizontal and Vertical Segments 22
Figure 8: Different Data Types and Functions in DaaS 78
Figure 9: Ecosystem and Platform Model 81
Figure 10: Ecosystem and Platform Model 85
Figure 11: DaaS and IoT Mediation for Smartgrid 87
Figure 12: Internet of Things (IoT) and DaaS 88
Figure 13: Telecom API Value Chain for DaaS 95
Figure 14: DaaS, Verification and Authorization 104
Figure 15: Web APIs 124
Figure 16: Services Oriented Architecture 126
Figure 17: Cloud Services, DaaS, and APIs 128
Figure 18: Telecom APIs 129
Figure 19: Federated Data vs. Non-Federated Models 131
Figure 20: Federated Data at Functional Level 133
Figure 21: Federated Data at City Level 134
Figure 22: Federated Data at Global Level 135
Figure 23: Federation Requires Mediation Data 136
Figure 24: Mediation Data Synchronization 137
Figure 25: Hybrid Data in Next Generation Applications 145
Figure 26: Traditional Data Architecture 146
Figure 27: Data Architecture Modeling 147
Figure 28: DaaS Data Architecture 149
Figure 29: Location Data Mediation 152
Figure 30: Data Mediation in IoT 153
Figure 31: Data Mediation for Smartgrids 155
Figure 32: Enterprise Data Types 156
Figure 33: Data Governance 161
Figure 34: Data Flow 163
Figure 35: Processing Streaming Data 164


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