Chan Ye Xin Xi Wang·2025-12-30 01:32Core Insights - The industrial big data industry is a key enabling sector that leverages data as a core production factor, facilitating the release of data and information value in industrial economic activities. It encompasses the entire process from data collection, storage, processing, analysis to application, and is crucial for emerging fields like industrial internet and smart manufacturing [1][12]. Market Overview - The market size of China's industrial big data industry is projected to grow from 40 billion yuan in 2018 to 137.3 billion yuan by 2024, with a compound annual growth rate (CAGR) of 22.82%. By 2025, it is expected to reach 154.3 billion yuan [1][12]. - The growth is driven by the increasing demand for industrial big data in manufacturing, energy, and transportation sectors, alongside advancements in technologies such as big data, AI, edge computing, and real-time analysis [1][12]. Industry Policies - The government has implemented various policies to promote the development of industrial big data, including the "Digital Transformation Implementation Plan for the Electronic Information Manufacturing Industry" issued in May 2025, which emphasizes the integration of advanced computing, intelligent control, and big data technologies [5][6]. Industry Chain - The industrial big data industry chain consists of three segments: upstream (data visualization, data centers, cloud computing), midstream (industrial big data services), and downstream (application fields such as aerospace, medical devices, and new energy vehicles) [7][8]. Data Center Market - The data center market in China is expected to grow from 87.8 billion yuan in 2019 to 304.8 billion yuan by 2024, with a CAGR of 28.26%. This growth is supported by national policies promoting new infrastructure and digital transformation [9][10]. Industry Development Trends - The evolution of industrial big data will transition from descriptive analysis to decision-making intelligence, integrating edge computing and AI for real-time data processing and autonomous optimization [16]. - There will be a shift from data silos to value network integration, enabling trusted data sharing across the entire supply chain through technologies like privacy computing and blockchain [17]. - The focus will move from process optimization to the digitalization and reuse of industrial knowledge, creating standardized knowledge components that can be rapidly deployed across different production lines [18].