人人都是产品经理发布于 08/25 10:43
AI数据分析SOP（ChatBI，数据Agent，SKill通用版）
AI工具泛滥的时代，数据分析如何真正创造价值？陈老师总结的AI版SOP，从业务需求出发，强调数据成果的实用性与包装，教你摆脱人肉SQL机的命运，用数据驱动决策，让每一次分析都成为升职加薪的跳板。
AWS Machine Learning Blog发布于 08/22 01:06
Agentic Data Operations Platform (ADOP): Data engineering into hours
（翻译）智能体数据运维平台（ADOP）：数小时完成数据工程
The Agentic Data Operations Platform (ADOP) is a reference architecture on Amazon Bedrock that uses specialized AI agents to automate the full Bronze-to-Silver-to-Gold data pipeline lifecycle, compressing new-source onboarding from weeks to hours while keeping data governance and compliance controls
AWS Machine Learning Blog发布于 08/21 05:23
Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment
（翻译）使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码机器学习工作流——第1部分：设置Snowflake环境
Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your AWS account and Snowflake environment for a no-code ML workflow with Amazon SageMaker Canvas, laying the foundation for
AWS Machine Learning Blog发布于 08/21 05:23
Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 3: Visualizing insights with Amazon Quick Sight
（翻译）使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码ML工作流——第3部分：使用Amazon Quick Sight可视化洞察
In Part 3 of this no-code ML series, you bring fraud detection predictions to life. Import your Amazon SageMaker Canvas predictions into Amazon Quick Sight, build interactive dashboards, use generative BI to answer questions in natural language, and publish AI-generated executive summaries for stake
InfoQ 中文发布于 08/26 18:10
Grab 借助 AI 代理将机械性分析的工作量从 44% 降至 30%
Grab 正在利用 AI 代理实现分析工作流的自动化，从而减少分析师处理常规工作的占比，并缩短解答业务问题所需的时间。
人人都是产品经理发布于 08/26 10:00
AI+数据指标体系，这是我见过最完整的攻略
AI工具虽能快速生成指标框架，但脱离业务场景的体系注定水土不服。本文以销售运营为例，拆解如何从业务目标、流程、动作到数据记录四步构建真正可落地的指标体系，拒绝空谈理论。
