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

Transcription

1 Brochure More information from M2M/IoT, Cloud, Big Data and Analytics: Market Dynamics and Opportunities Description: 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 this report 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: - 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 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 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 Contents: EXECUTIVE SUMMARY 1.0 INTRODUCTION 2.0 ASPECTS OF M2M APPLICATION 2.1 Wireless Connectivity 2.2 Big Data 2.3 The Cloud 3.0 BIG DATA

2 3.1 CXOs' take on Big Data 4.0 USING DATA AS A POWERFUL TOOL 4.1 Social Sensor Cloud (SSC) 4.2 Virtual Sensors 5.0 BUSINESSES IMPACT OF BIG DATA AND ANALYTICS 5.1 Big Data: The Road to Decision-making not the Destination 5.2 Correlation of Data from Different Sources 5.3 Big Data Myth-busters for Management 6.0 M2M AND BIG DATA APPLICATIONS 6.1 Wireless Carriers 6.2 Smart Cars 6.3 Auto Insurance 6.4 Insurance 6.5 Smart Homes 6.6 Healthcare 6.7 Utility 6.8 Energy Management 6.9 Robotics 6.10 Logistics 6.11 Asset Tracking 6.12 Manufacturing 6.13 Supply Chain for Auto Manufacturers 6.14 Security and Surveillance 6.15 Enterprise in any Sector 7.0 CHALLENGES OF M2M AND BIG DATA 7.1 Privacy and Data Ownership 7.2 Authenticity and Security 7.3 Specialized Skill-set Required 7.4 Change in approach 8.0 BIG DATA STRATEGIES 8.1 Do-it-Yourself (DIY) Model 8.2 Database as a service (DBaaS) 8.3 Managed Service Providers (MSP) 8.4 One-button-Deploy Technology 9.0 BIG DATA SECURITY AND PRIVACY 9.1 Security Updates 9.2 Data Encryption 9.3 Choosing the Right Encryption Solution 9.4 Big Data to Detect Malicious Behavior 10.0 CLOUD 11.0 CLOUD COMPUTING MODEL 11.1 Services IaaS PaaS SaaS MaaS CaaS XaaS 11.2 Characteristics On-demand Self-service Broad Network Access Resource Pooling Rapid Elasticity Measured Service 11.3 Deployment Modes

3 Private Cloud Public Cloud Community Cloud Hybrid Cloud 11.4 Benefits of Cloud Computing 11.5 Strategic fit for Cloud Adoption 11.6 M2M and Cloud Integration 11.7 Analysis 12.0 BARRIERS AND CHALLENGES TO CLOUD ADOPTION 12.1 Reluctance to Change 12.2 Outsourcing Data Security Loss of Control 12.3 Security Concerns 12.4 Cyber Attacks Severe Budget Restrictions of SMEs Prolific use of Internet 12.5 Unclear SLAs Unclear SLA Terms for Downtime Secondary CSPs Entitlement to Credit for Downtime Calculating Up-time Different Cloud Services have Different SLAs 12.6 Complexity restricts Adoption Inherent Complexity in the Cloud Computing Environment Integration of Processes is a Complex Task Integration Problems with SAAS Deployment API Management Determine the Best way to Integrate Data 12.7 Cloud Interoperability Option of cloud interoperability Moving Applications between Clouds 12.8 Audit of Service Provider Industry Best Practices are still Developing Resistance to Audit Signals Caution Resistance of CSPs to allow Elaborate Tests Audits build Confidence among Reluctant SMEs 12.9 Viability of Third-party Providers Acceptance Issues Cost Considerations Lack of Integration Features in the Public Cloud 13.0 DATA ANALYTICS 13.1 Factors Driving M2M Analytics Opportunity M2M Data Growth New Analytical Technologies Enhanced Business Models through Data Analysis 13.2 Important Factors for success in M2M Analytics Market 13.3 Competitive Vendor Analysis Device Manufacturers SI and Professional Services Management Platform Providers Software and Application Developers Communication Service Providers 14.0 ADVANCED ANALYTICS TOOLS 15.0 ADVANCED ANALYTICS CASE STUDIES 15.1 Case One: Using analytics to Identify Interdependencies among different Process Parameters The Challenge The Solution The Result 15.2 Case Two: Use of Neural Networks Tools

4 The Challenge The Solution The Result 15.3 Case Three: Use Production Data to identify Gaps The Challenge The Solution The Result 16.0 CONCLUSIONS 17.0 APPENDIX LIST OF FIGURES Figure 1: Aspects of M2M Application Figure 2: Five Factors of Big Data Figure 3: New Interest over Time: Big Data vs. Cloud Computing Figure 4: Adoption Index Figure 5: Risk of Forest Fires Figure 6: Google's Self-driving Car Figure 7: Snapshot device by Progressive Insurance Figure 8: Model of Smart City Sangdo Figure 9: Data Reliability/Security Diminishing over Time Figure 10: The M2M Cloud Figure 11: IaaS Figure 12: PaaS Figure 13: SaaS Figure 14: Cloud Computing Service by Deployment Mode Figure 15: Cloud Application and Services Priorities Figure 16: Barriers and Challenges to Cloud Adoption Figure 17: Factors Driving M2M Analytics Opportunity Figure 18: Value Creation Mechanisms through M2M Analytics Figure 19: Competitive Vendor Analysis Figure 20: Example of Histogram Figure 21: Examples of Correlation Analysis Figure 22: Examples of Significance Testing Figure 23: Example of Artificial Neural Network Ordering: Order Online - Order by Fax - using the form below Order by Post - print the order form below and send to Research and Markets, Guinness Centre, Taylors Lane, Dublin 8, Ireland.

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