行业点评报告 · 通信行业 足星移动通信牌照,卫星通信进程加速 2025 年 09 月 10 日 核心观点 除了面向大众的 To C 直连服务外,卫星运营还包括 To B 模式,即以太空算 力和"星缆计划"为代表的企业级专属服务,更侧重算力调度与数据传输等高 附加值需求。以之江实验室的三体计算星座为例,我们将其商业模式总结为三 大方向:1) 太空算力租赁服务:算力星座可作为"太空数据中心",通过星 间激光链路快速接入,为其他应用卫星提供边缘计算能力,实现太空数据"就 近处理",解决应用卫星"有星无算"的长期痛点。2)太空通信与星缆计划: 通过专属地面站与星间链路,构建"太空光纤"通道,形成低时延、高安全性 的跨域传输网络。该模式类比地面政企专线,面向云计算厂商、大型互联网等 客户,帮助其实现跨境数据传输、算力调度。其核心优势在于低延迟(星间激 光通信的传输路径更接近直线,数据传输速度更快）、安全性(规避跨境地区 安全风险）、以及经济性(使东部高需求地区能够实时调用西部低电价算力资 源),有效补足地面骨干网的短板。 3)智能数据资产变现:可将收集积累的 数据应用于农业、气象、能源、城市治理、低空积极等行业,形成 ...

Core Viewpoint - The financial market data landscape is undergoing significant changes due to the increasing volume and variety of data, as well as the rising demand for real-time insights [1][3]. Group 1: Challenges in Financial Market Data Management - Traditional data management methods are often isolated, inefficient, and costly, leading to slow transmission, high costs, and poor flexibility [4]. - Current industry characteristics include an explosion of data sources, requiring integration from numerous vendors alongside proprietary and third-party data [5]. - The diversity of data types is increasing, necessitating the handling of structured, unstructured, and semi-structured data, including ESG data and private market data [5]. Group 2: Adoption of DaaS - The adoption of Data as a Service (DaaS) is driven by the need for greater flexibility, scalability, and cost-effectiveness in data management [6]. - DaaS simplifies data pipelines by connecting services and integrating third-party and proprietary data sources, ensuring data integrity and relevance [7]. Group 3: Benefits of DaaS for Financial Market Participants - DaaS supports the pursuit of real-time insights, enabling faster decision-making through the fusion of different data types [11]. - Technological advancements such as cloud computing, APIs, and AI are reshaping data access, processing, and analysis [11]. - DaaS enhances compliance by helping companies meet increasingly complex data regulatory requirements [11]. Group 4: Action Framework for Implementing DaaS - Step 1: Define objectives by identifying specific problems and expected outcomes related to data, technology, and application scenarios [12]. - Step 2: Assess existing infrastructure to evaluate strengths, limitations, and costs, determining readiness for DaaS integration [13]. - Step 3: Identify DaaS requirements through detailed evaluation to ensure alignment with specific company needs [14]. - Step 4: Design and implement a phased approach starting with proof of concept to demonstrate DaaS advantages [15]. - Step 5: Optimize and evaluate the DaaS system continuously to maximize its value and ensure transparency in data usage and costs [18]. Group 5: Future of Financial Market Data Management - DaaS is a key driver for building data pipelines, playing an increasingly important role in modernizing data architecture, improving efficiency, and fostering innovation [19].