M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities

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Overview: Technology and market advances in four separate, yet related, areas are poised to cause disintermediation as well as many market opportunities for companies across a broad spectrum within telecom and digital technologies. Machine-to-Machine (M2M) has already made a big impact on wireless communications as network operators seek to leverage revenue opportunities beyond human interaction reliant services. The evolution of automated processes due to the Internet of Things (IoT) will accelerate this impact. The Cloud supports storage of huge amount of data gathered by M2M applications and also ensures real-time availability of data for further processing and analysis. Without the processing power and number crunching ability of Big Data and Analytics, the full potential of M2M and IoT would never be realized. These four factors working in alignment will enable new business opportunities and provide additional benefits to enterprise, which in turn will be passed on to end-consumers. This research evaluates each of these individually as well as in conjunction with each. This report uniquely focuses on the mutual and conjoint benefits of M2M, Cloud, Big Data and Analytics. 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. Report Benefits:Case StudiesCXO positions on Big DataBig Data Security and PrivacyChallenges of M2M and Big DataApplications of M2M and Big DataFactors Driving M2M Analytics OpportunityBarriers and Challenges to Cloud AdoptionBusinesses Impact of Big Data and AnalyticsTarget Audience:Network operatorsM2M / IoT platform providersM2M infrastructure providersM2M / IoT application developersCloud and telecom security companiesAnalytics and Data reporting companiesTelecommunications infrastructure providersM2M equipment and service providers of all typesCloud infrastructure and support service providersData aggregators, storage and management providersBig Data solution (Infrastructure, Software, Service) vendors

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M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities

  1. 1. ReportLinker Find Industry reports, Company profiles and Market Statistics >> Get this Report Now by email! M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities Published on July 2014 Report Summary Overview: Technology and market advances in four separate, yet related, areas are poised to cause disintermediation as well as many market opportunities for companies across a broad spectrum within telecom and digital technologies. Machine-to-Machine (M2M) has already made a big impact on wireless communications as network operators seek to leverage revenue opportunities beyond human interaction reliant services. The evolution of automated processes due to the Internet of Things (IoT) will accelerate this impact. The Cloud supports storage of huge amount of data gathered by M2M applications and also ensures real-time availability of data for further processing and analysis. Without the processing power and number crunching ability of Big Data and Analytics, the full potential of M2M and IoT would never be realized. These four factors working in alignment will enable new business opportunities and provide additional benefits to enterprise, which in turn will be passed on to end-consumers. This research evaluates each of these individually as well as in conjunction with each. This report uniquely focuses on the mutual and conjoint benefits of M2M, Cloud, Big Data and Analytics. 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. Report Benefits: Case Studies CXO positions on Big Data Big Data Security and Privacy Challenges of M2M and Big Data Applications of M2M and Big Data Factors Driving M2M Analytics Opportunity Barriers and Challenges to Cloud Adoption Businesses Impact of Big Data and Analytics Target Audience: Network operators M2M / IoT platform providers M2M infrastructure providers M2M / IoT application developers Cloud and telecom security companies Analytics and Data reporting companies Telecommunications infrastructure providers M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities (From Slideshare) Page 1/7
  2. 2. ReportLinker Find Industry reports, Company profiles and Market Statistics >> Get this Report Now by email! M2M equipment and service providers of all types Cloud infrastructure and support service providers Data aggregators, storage and management providers Big Data solution (Infrastructure, Software, Service) vendors Table of Content EXECUTIVE SUMMARY 1.0 INTRODUCTION 1 2.0 ASPECTS OF M2M APPLICATION 2 2.1 Wireless Connectivity 2 2.2 Big Data 2 2.3 The Cloud 2 3.0 BIG DATA 3 3.1 CXOs' take on Big Data 4 4.0 USING DATA AS A POWERFUL TOOL 9 4.1 Social Sensor Cloud (SSC) 9 4.2 Virtual Sensors 10 5.0 BUSINESSES IMPACT OF BIG DATA AND ANALYTICS 12 5.1 Big Data: The Road to Decision-making not the Destination 12 5.2 Correlation of Data from Different Sources 12 5.3 Big Data Myth-busters for Management 13 6.0 M2M AND BIG DATA APPLICATIONS 16 6.1 Wireless Carriers 16 6.2 Smart Cars 16 6.3 Auto Insurance 17 6.4 Insurance 18 6.5 Smart Homes 18 6.6 Healthcare 19 6.7 Utility 20 6.8 Energy Management 20 6.9 Robotics 21 6.10 Logistics 21 6.11 Asset Tracking 21 6.12 Manufacturing 22 6.13 Supply Chain for Auto Manufacturers 22 6.14 Security and Surveillance 22 6.15 Enterprise in any Sector 22 7.0 CHALLENGES OF M2M AND BIG DATA 24 7.1 Privacy and Data Ownership 24 7.2 Authenticity and Security 24 7.3 Specialized Skill-set Required 25 7.4 Change in approach 25 8.0 BIG DATA STRATEGIES 26 8.1 Do-it-Yourself (DIY) Model 26 8.2 Database as a service (DBaaS) 26 M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities (From Slideshare) Page 2/7
  3. 3. ReportLinker Find Industry reports, Company profiles and Market Statistics >> Get this Report Now by email! 8.3 Managed Service Providers (MSP) 27 8.4 One-button-Deploy Technology 27 9.0 BIG DATA SECURITY AND PRIVACY 28 9.1 Security Updates 28 9.2 Data Encryption 28 9.3 Choosing the Right Encryption Solution 29 9.4 Big Data to Detect Malicious Behavior 30 10.0 CLOUD 31 11.0 CLOUD COMPUTING MODEL 32 11.1 Services 32 11.1.1 IaaS 33 11.1.2 PaaS 34 11.1.3 SaaS 35 11.1.4 MaaS 36 11.1.5 CaaS 36 11.1.6 XaaS 36 11.2 Characteristics 37 11.2.1 On-demand Self-service 38 11.2.2 Broad Network Access 38 11.2.3 Resource Pooling 38 11.2.4 Rapid Elasticity 38 11.2.5 Measured Service 38 11.3 Deployment Modes 39 11.3.1 Private Cloud 39 11.3.2 Public Cloud 39 11.3.3 Community Cloud 39 11.3.4 Hybrid Cloud 39 11.4 Benefits of Cloud Computing 40 11.5 Strategic fit for Cloud Adoption 41 11.6 M2M and Cloud Integration 42 11.7 Analysis 44 12.0 BARRIERS AND CHALLENGES TO CLOUD ADOPTION 45 12.1 Reluctance to Change 45 12.2 Outsourcing Data Security 45 12.2.1 Loss of Control 45 12.3 Security Concerns 46 12.4 Cyber Attacks 46 12.4.1 Severe Budget Restrictions of SMEs 46 12.4.2 Prolific use of Internet 46 12.5 Unclear SLAs 47 12.5.1 Unclear SLA Terms for Downtime 47 12.5.2 Secondary CSPs 47 12.5.3 Entitlement to Credit for Downtime 47 12.5.4 Calculating Up-time 47 12.5.5 Different Cloud Services have Different SLAs 48 12.6 Complexity restricts Adoption 48 12.6.1 Inherent Complexity in the Cloud Computing Environment 48 12.6.2 Integration of Processes is a Complex Task 48 M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities (From Slideshare) Page 3/7
  4. 4. ReportLinker Find Industry reports, Company profiles and Market Statistics >> Get this Report Now by email! 12.6.3 Integration Problems with SAAS Deployment 48 12.6.4 API Management 48 12.6.5 Determine the Best way to Integrate Data 49 12.7 Cloud Interoperability 49 12.7.1 Option of cloud interoperability 49 12.7.2 Moving Applications between Clouds 49 12.8 Audit of Service Provider 49 12.8.1 Industry Best Practices are still Developing 49 12.8.2 Resistance to Audit Signals Caution 49 12.8.3 Resistance of CSPs to allow Elaborate Tests 50 12.8.4 Audits build Confidence among Reluctant SMEs 50 12.9 Viability of Third-party Providers 50 12.10 Acceptance Issues 50 12.11 Cost Considerations 51 12.12 Lack of Integration Features in the Public Cloud 51 13.0 DATA ANALYTICS 52 13.1 Factors Driving M2M Analytics Opportunity 52 13.1.1 M2M Data Growth 52 13.1.2 New Analytical Technologies 53 13.1.3 Enhanced Business Models through Data Analysis 53 13.2 Important Factors for success in M2M Analytics Market 54 13.3 Competitive Vendor Analysis 55 13.3.1 Device Manufacturers 55 13.3.2 SI and Professional Services 56 13.3.3 Management Platform Providers 56 13.3.4 Software and Application Developers 56 13.3.5 Communication Service Providers 56 14.0 ADVANCED ANALYTICS TOOLS 57 15.0 ADVANCED ANALYTICS CASE STUDIES 60 15.1 Case One: Using analytics to Identify Interdependencies among different Process Parameters 60 15.1.1 The Challenge 60 15.1.2 The Solution 60 15.1.3 The Result 60 15.2 Case Two: Use of Neural Networks Tools 60 15.2.1 The Challenge 60 15.2.2 The Solution 61 15.2.3 The Result 61 15.3 Case Three: Use Production Data to identify Gaps 61 15.3.1 The Challenge 61 15.3.2 The Solution 62 15.3.3 The Result 62 16.0 CONCLUSIONS 63 17.0 APPENDIX 64 LIST OF FIGURES Figure 1: Aspects of M2M Application 2 Figure 2: Five Factors of Big Data 3 M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities (From Slideshare) Page 4/7
  5. 5. ReportLinker Find Industry reports, Company profiles and Market Statistics >> Get this Report Now by email! Figure 3: New Interest over Time: Big Data vs. Cloud Computing 4 Figure 4: Adoption Index 7 Figure 5: Risk of Forest Fires 11 Figure 6: Google's Self-driving Car 17 Figure 7: Snapshot device by Progressive Insurance 18 Figure 8: Model of Smart City Sangdo 19 Figure 9: Data Reliability/Security Diminishing over Time 24 Figure 10: The M2M Cloud 32 Figure 11: IaaS 33 Figure 12: PaaS 35 Figure 13: SaaS 36 Figure 14: Cloud Computing Service by Deployment Mode 40 Figure 15: Cloud Application and Services Priorities 43 Figure 16: Barriers and Challenges to Cloud Adoption 45 Figure 17: Factors Driving M2M Analytics Opportunity 52 Figure 18: Value Creation Mechanisms through M2M Analytics 54 Figure 19: Competitive Vendor Analysis 55 Figure 20: Example of Histogram 57 Figure 21: Examples of Correlation Analysis 58 Figure 22: Examples of Significance Testing 58 Figure 23: Example of Artificial Neural Network 59 M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities (From Slideshare) Page 5/7
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