工業數據趨勢與技術

本報告探討了工業資料管理趨勢，總結了價值鏈中領先供應商和解決方案的競爭優勢和差異化因素、製造資料架構的收入預測以及應用障礙。

實際收益：

• 識別並優先考慮客戶在工業資料管理方面的需求。
• 了解按產業、使用案例和部署模式劃分的關鍵成長機會。
• 評估工業資料管理解決方案供應商的競爭優勢和差異化因素。

解答關鍵問題：

• 工業資料管理的哪些領域創新最多？
• 市場上的領先解決方案提供者有哪些？他們在哪些方面提供了差異化機會？
• 哪些因素阻礙了客戶採用工業資料管理解決方案？

研究亮點：

• 數據價值鏈領先供應商解決方案評估
• 按應用程式劃分的製造資料架構收入預測
• 基於優勢的解決方案提供者區隔

目錄

第一章：主要發現

第二章：主要預測

第三章：工業資料價值鏈

• 資料攝取與邊緣處理
• 情境化與存儲
• 編排
• 分析

第四章：主要參與者與生態系

• 雲端解決方案供應商
• 邊緣與資料營運軟體
• 製造軟體供應商
• 工業分析與智能

第五章：採用障礙

Actionable Benefits:

• Identify and prioritize customer needs in industrial data management.
• Recognize key growth opportunities across industries, use cases, and deployment models.
• Assess competitive positioning and points of differentiation among industrial data management suppliers.

Critical Questions Answered:

• What areas of industrial data management are experiencing the most innovation?
• Who are the key solution providers in the market, and where are there opportunities to differentiate?
• What is preventing customers from adopting industrial data management solutions?

Research Highlights:

• Table of major suppliers with ratings on their solutions along the data value chain.
• Manufacturing data fabric revenue forecast by specific application.
• Segmentation of solution providers based on their strengths.

Who Should Read This?

• Technology suppliers in product management, marketing, and corporate strategy.
• Industrial data platform providers in market intelligence.
• Systems integrators and value-added resellers.
• Manufacturing and industrial end users, including digital transformation managers and operations executives.

TABLE OF CONTENTS

1 KEY FINDINGS

2 KEY FORECASTS

3 INDUSTRIAL DATA VALUE CHAIN

• 3.1. INGESTION AND EDGE PROCESSING
• 3.2. CONTEXTUALIZATION AND STORAGE
• 3.3. ORCHESTRATION
• 3.4. ANALYTICS

4 KEY COMPANIES AND ECOSYSTEMS

• 4.1. CLOUD SOLUTION PROVIDERS
• 4.2. EDGE AND DATAOPS SOFTWARE
• 4.3. MANUFACTURING SOFTWARE PROVIDERS
• 4.4. INDUSTRIAL ANALYTICS AND INTELLIGENCE

5 BARRIERS TO ADOPTION