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].