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This article presents Ximalaya's practical exploration of a large‑model‑driven BI system called ChatBI, detailing the background challenges, product architecture, implementation workflow, model‑optimization techniques, launch results, and future directions for data‑intelligent operations.
This article reviews the China Academy of Information and Communications Technology's advancements in large‑model‑driven data intelligence, covering development trends, key deployment technologies such as prompt engineering, fine‑tuning and RAG, emerging application paradigms, challenges, and a series of newly drafted standards to guide industry adoption.
This article presents the China Information and Communications Research Institute’s research on the Enterprise Digital Intelligence Capability Maturity Model (EDMM), detailing the concepts of data, intelligent, and knowledge middle platforms, the model’s four‑layer framework, its development stages, value propositions, long‑term mechanisms, and upcoming work plans.
This presentation explains how data intelligence—through Customer Intelligence, Business Intelligence, and Artificial Intelligence—addresses key data challenges, enhances user profiling, automates analytical insights, and enables conversational data consumption to drive efficient, data‑driven business growth.
This article presents a comprehensive overview of data intelligence as a catalyst for business growth, detailing the roles of Customer Intelligence (CI), Business Intelligence (BI), and Artificial Intelligence (AI) in enhancing data analysis, decision‑making, and user‑centric product development across various organizational functions.
The 23rd CCF C³ Forum, organized by Alibaba’s Alimama and the CCF CTO Club, examined how large‑model AI is reshaping intelligent business technology, from data‑driven to knowledge‑driven approaches, enhancing e‑commerce with smarter search, personalized recommendations, content creation, and guiding merchants on future AI‑native strategies.
In a Shanghai launch event for Altair RapidMiner, Prof. Xiao Yanghua explained why data is a strategic resource, outlined the challenges of data value realization, introduced the concept of data intelligence driven by both data‑driven and knowledge‑driven systems, and discussed emerging trends such as low‑code platforms, large‑model integration, and the shift of AI applications from consumer to industrial domains.
This article explains how Alibaba combines frontend development with data intelligence—covering massive internet data, market demands, three integration modes, key technologies like WhaleM, DataCook and PipCook, practical workflows, a k‑means clustering case study, and future directions such as WebNN, WebGPU and WASM—to enhance user experience and drive business growth.
The article explains how user profiling—labeling users' habits, behaviors, and attributes—serves as the foundation for big‑data‑driven personalized recommendation, advertising, and intelligent marketing, and outlines a step‑by‑step development workflow from tag design to service deployment.
The paper proposes a containerized, machine‑learning framework that fuses rule‑based and XGBoost‑driven anomaly detection to monitor daily active users on a cloud music platform, achieving 89 % recall, 81 % precision and up to 74 % recall improvement over traditional threshold methods, while outlining future model refinement and broader metric applicability.
The 3rd Youzan Big Data Technology Salon, held online for over 200 participants, showcased Apache Kylin 4’s performance boost, GeTui’s five‑step AI method, Kwai’s sustainable data‑governance system, and Youzan’s intelligent copy algorithms, highlighting data governance’s evolution into a core business priority and the shift toward intelligent discovery.
This article details how the 58 Group applied data‑driven methods—user segmentation, interest description, clustering, and predictive modeling—to forecast and identify traffic in the used‑car scenario, illustrating the end‑to‑end pipeline, experimental results, and practical impact on downstream business processes.
The article describes Ant Financial's open computing architecture that unifies storage, security, and programming models to support real‑time data intelligence, AI engines, and large‑scale graph computing, illustrating how these technologies enable flexible, high‑availability financial services.
At QCon2014, Baidu Research’s Shen Zhiyong showcased the company’s massive big‑data engine—20,000 PB storage and daily processing of up to 100 PB—highlighting open platforms like Baidu Brain and real‑world prediction projects for tourism, the World Cup, disease outbreaks, and UN collaborations, while urging industry‑wide data‑driven transformation.