Business Intelligence 2.0: IoT Stream Processing, Analytics, and Data Management Services Image

Business Intelligence 2.0: IoT Stream Processing, Analytics, and Data Management Services

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Actionable Benefits

  • Compare the products and services, and IoT data management technology offering of 19 IoT vendors.
  • Identify the strength and weaknesses of IoT vendors and leverage the competitive differentiation for the sales/strategy teams.
  • Analyze the strategy, position, differentiation, and competitive outlook of the leading data management vendors for the IoT.
  • Identify market leaders, first followers, and important players for the edge and cloud real-time streaming technology vendors.
  • Select the vendors with the most relevant offering for enterprises, to ensure partnership, optimize commercial cooperation, and avoid vendor lock-in.
  • Identify current and future trends in IoT data management for the IoT, with revenue forecasts from 2018 until 2026 for integration, stream processing, storage, core analytics, visualization, and professional services.

Critical Questions Answered

  • How IoT data management vendors are positioned in the IoT-data enabled value chain?
  • What are the disruptive and future trends in real-time streaming analytics, ingestion, and data processing engine analytics for IoT?
  • Who is dominating edge centric & cloud centric IoT data management solutions?

Research Highlights

  • A detailed breakdown of IoT analytics value chain components.
  • Comprehensive analysis of IoT analytics strategies of ScaleOut Software, Clearblade, Informatica, Striim, TIBCO, Confluent, IBM, AWS, Azure, Oracle, Cisco, Cloudera and others.
  • Detailed technical and commercial overview of IoT streaming and data management technologies and comparison of overall IoT-data enabled capabilities.

Who Should Read This?

  • IoT Big Data 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 data management offerings, strengths and avoid vendors lock-in.
  • S-Suita and strategic advisors within the data-enabled industry who are responsible for strategy formation, business development and innovative solutions planning.

Table of Contents

Table of Contents

1. EXECUTIVE SUMMARY

2. IOT DATA STREAMING AND DATA MANAGEMENT MARKETS

2.1. Introduction
2.2. Brief Overview of the Analytics Value Chain
2.3. Detailed Outlook Edge-to-the-Cloud Streaming Analytics Value Chain
2.4. Computing at the Edge: Streaming Technology
2.5. Cloud Computing: Streaming Technology

3. THE BI PARADIGM

3.1. From Traditional Business Model to BI 2.0
3.2. Three Paradigms of Stream Processing

4. THE ROLE OF OPEN SOURCE IN STREAMING ANALYTICS

5. KEY TRENDS AND OBSERVATIONS

6. IOT STREAM PROCESSING ECOSYSTEM

6.1. Competitive Landscape
6.2. Vendor Overview

7. MARKET FORECASTS

7.1. Methodology

8. RECOMMENDATIONS