This article explores Kuaishou E‑Commerce’s journey in constructing a comprehensive data metric system, detailing its business context, the necessity of metrics, challenges across data production, querying and usage, practical implementation steps, management practices, and a concluding Q&A.
This article presents NetEase Yanxuan's end‑to‑end approach for automatically detecting and diagnosing metric anomalies in e‑commerce, covering background motivations, statistical detection methods (absolute, volatility, trend), contribution‑decomposition diagnosis, optimization techniques for dimensional explosion, and a Q&A on practical implementation.
This article presents a comprehensive overview of applying causal inference to Alibaba’s Business Intelligence platform, detailing fundamental concepts, the merchant intelligent diagnosis system architecture, key technologies such as hybrid causal network discovery (HCM) and deep attribution, and showcases the resulting operational impact.
This article explains ByteDance’s data lake technology, its Apache Hudi‑based features, near‑real‑time architecture, and practical e‑commerce use cases such as marketing promotion, traffic diagnosis, logistics monitoring, risk governance, and operational monitoring, while outlining future challenges and plans.
The article explains how JD’s Activity Cockpit tackles mega‑sale challenges by monitoring the consumer golden‑link, applying Optimize Table, BitMap, and materialized view techniques to reduce data volume, accelerate queries, and enable precise real‑time marketing for brands.
This article details how NetEase Yanxuan designed and implemented a comprehensive traffic system—including event‑tagging methods, a top‑down management framework, data‑quality controls, testing strategies, and attribution models—to turn fragmented user behavior into actionable e‑commerce insights.
