Core Insights - The article presents a practical guide developed by Volcano Engine in collaboration with the China Academy of Information and Communications Technology, focusing on the end-to-end process of data intelligence implementation [1] - It breaks down the technical aspects into a core architecture of "data collection - processing - modeling - application," detailing the collaborative logic of modules such as multimodal data fusion and real-time inference engines [1] - The application scenarios cover vertical fields including manufacturing data monitoring, financial risk control, and government data governance, providing standards for scenario adaptation [1] - The implementation path is divided into three phases: "small-scale pilot - medium-scale expansion - large-scale deployment," offering resource allocation and evaluation metrics for enterprises of different sizes [1] - The guide addresses core pain points such as cross-system integration and privacy compliance, providing a standardized framework for data departments and digital transformation leaders [1] Section Summaries Section 1: Cognitive Reconstruction - The section discusses the current state of the industry, highlighting deep-seated challenges beneath the surface of apparent prosperity [3] - It identifies three common misconceptions about the essence of AI and emphasizes a paradigm shift from tool thinking to system thinking [3] Section 2: System Construction - This section defines the concept of data intelligence agents as "enterprise-level data experts" and introduces a six-dimensional capability model [4] - It also presents a maturity model for data intelligence agents, categorizing them into four levels (L1-L4) [4] Section 3: Value Realization - The section categorizes application scenarios and provides in-depth analysis of typical use cases, along with a value assessment system [4] - It outlines strategies for phased implementation and enterprise readiness evaluation [4] Section 4: Industry Outlook - This section discusses technological evolution trends and industry opportunities, including the evolution of industry patterns and key success factors [4] - It also suggests standards for capability maturity assessment and industry development recommendations [4]