A real‑world incident where an ADS table stopped updating triggered a three‑second root‑cause discovery and a three‑hour data‑warehouse rebuild using a Claude‑based Skill that eliminated about 70% of the manual, repetitive steps traditionally required in data development, testing, deployment, and operations.
The article analyzes how AI coding has moved from assistance to partial automation, outlines production‑ready AI capabilities for data development, discusses rapidly advancing areas like cross‑table understanding and agent auto‑debugging, and examines the resulting blurring of job roles and the heightened importance of AI skills in interviews.
Facing siloed, tool‑fragmented, and low‑quality data pipelines, China Everbright Bank built an AI‑driven, end‑to‑end data integration platform that unifies heterogeneous databases, automates workflow checkpoints, and adds intelligent code quality checks, delivering faster, higher‑quality data services for the financial sector.
This article describes how a data‑engineering team built a suite of AI agents to automate requirement assessment, model review, code review, style enforcement, and problem diagnosis, turning tedious, error‑prone manual processes into fast, reliable, and scalable workflows that boost overall development efficiency.
The article discusses how large language model tools such as Cursor, DeepSeek, and Doubao are increasingly assisting code writing, SQL translation, job‑failure analysis, and documentation in data‑development workflows, while also reshaping job requirements and creating new opportunities for skilled developers.
The TDS platform, central to Baidu MEG’s Turing 3.0 ecosystem, unifies data development, warehouse management, monitoring, and resource control through Spark‑based TDE, a visual studio, and AI‑enhanced tools like Smart Diagnosis and Text2SQL, enabling standardized workflows, scalable scheduling, and handling over 30 k daily tasks.
The article walks through a detailed, real‑world scenario where a business analyst leverages a data middle platform—covering metric analysis, exploratory queries, data development, visualization, and productization—to diagnose a 30% sales decline and implement data‑driven remediation, illustrating core concepts such as OneData and OneService.
The 2022 Meituan Technical Salon recap details six online sessions—testing, algorithm strategies, data development, foundational technology, system development, and frontend development—listing each talk’s title, speaker, date, and offering video and PPT links, serving as a comprehensive learning resource on Meituan’s engineering practices.
This article presents an in‑depth overview of Youzan's data platform, introduces the DP data development platform with its key features and workflow, details the core module architecture—including service, scheduling, and component layers—and explains the migration from Airflow to DolphinScheduler to improve performance, stability, and scalability.
