Summary

Actionable Benefits

• Compare the tools and services, and IoT technology stacks of the leading cloud vendors for IoT analytics.
• Analyze the strategy, position, differentiation and competitive outlook of the leading cloud vendors for IoT analytics.
• Identify market leaders, first followers, and important players in the IoT analytics market.
• Select the vendors with most relevant offering for enterprises, to ensure partnership, optimize commercial cooperation, and avoid vendor lock-in.
• Identify current and future trends in cloud analytics for the IoT, with revenue forecasts from 2019 until 2026 for: integration, storage, analytics, presentation, and professional services.

Critical Questions Answered

• How cloud vendors are positioned in the IoT analytics market?
• What are the disruptive and future trends in analytics, advanced analytics and streaming analytics for IoT?
• Who is dominating cloud-native IoT analytics solutions?

Research Highlights

• A detailed breakdown of IoT analytics value chain components.
• Comprehensive analysis of IoT analytics strategies of: AWS, Azure, Oracle, Cisco, Huawei, SAP, Google, PTC, Cloudera and others.
• Detailed technical and commercial overview of IoT analytics technologies and comparison of overall IoT technology stacks of cloud vendors.

Who Should Read This?

• Cloud vendors and software developers for IoT analytics, who needs to understand the market dynamics and identify differentiation point among competitors.
• Industrial players, who intend/ongoing the IoT digital transformation, to understand cloud-vendor offerings, strengths and avoid vendors lock-in.
• S-Suita and strategic advisors within the cloud industry who are responsible for strategy formation, business development and innovative solutions planning.

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Table of Contents

1. EXECUTIVE SUMMARY

2. IOT AND ANALYTICS MARKET

2.1. Introduction

2.2. Brief Overview of Analytics Value Chain

2.3. IoT Data Analytics Value Chain

2.4. Cloud Computing Service Models

3. BUSINESS APPLICATION FOR IOT DATA ANALYTICS

3.1. Traditional Business Model for Enterprises

3.2. BI 2.0: IoT Data Analytics

3.3. Key Trends and Observations from 2019

3.4. Challenges in IoT Data Analytics Domain

4. IOT ANALYTICS ECOSYSTEM

4.1. Competitive Landscape

4.2. Cloud Service Provider IoT Platform

4.3. Specialized Cloud-Based Industrial Platforms

4.4. Open-Source Cloud-Based IoT Platforms

5. FORECASTS

5.1. Methodology

6. CONCLUSION: COMPARATIVE OUTLOOK

6.1. Competitive Landscape of 2019