@datahot.xiahongbin.comDataHot 今日精选 3/5｜事件驱动架构是产品分析的必要非充分条件
帮助数据从业者在架构选型和工具迁移阶段避免“买了事件架构就算产品分析”的误区，也点明了分析工具底层架构收敛带来的机会与边界。
阅读全文：https://datahot.xiahongbin.com/e/d08baffbd722.html?utm_source=bluesky&utm_content=card
#DataEngineering #BusinessIntelligence #数据
@datahot.xiahongbin.comDataHot 今日精选 2/5｜默认提示词正在拖累你的Agent留存率
对数据/AI Agent 产品团队有直接借鉴意义：激活指标应从首次消息转向第二次消息，并用数据说明默认提示词是影响留存的关键抓手。
阅读全文：https://datahot.xiahongbin.com/e/121742439778.html?utm_source=bluesky&utm_content=text
#DataEngineering #Analytics #数据
@checknumber.bsky.socialYour API error logs are often a better diagnostic for pipeline health than your dashboard. An unexpected response state isn't just a failure; it’s a signal about your data quality. Learn how to interpret these signals in our docs: https://docs.checknumber.ai/?utm_source=bsky #DataEngineering #API
@datahot.xiahongbin.comDataHot data pick 1/5｜Redefining GIS: Declarative Symbology and Collaborative Workflows in JupyterGIS
数据从业者可了解开源 Notebook 环境与 GIS 工作流的最新结合方式，特别是大规模遥感数据交互式分析与团队协作能力。
Read / 中文全文：https://datahot.xiahongbin.com/e/c09c159bcc53.html?utm_source=bluesky&utm_content=text
#DataEngineering #DataPlatform #数据
@rajeshdataai.bsky.socialFull Post: www.instagram.com/p/Dc6LgEDk1A...
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#SQL #interview #DataScience #DataAnalytics #ArtificialIntelligence #data #BusinessAnalyst #DataAnalyst #Database #DataEngineering #Tech #RajeshUmrao
@rajeshdataai.bsky.social
@nextgreatread.bsky.social“Note that the canonical representation of a DATETIME has the letter T separating the date part and the time part, whereas the representation of a TIMESTAMP uses a space.”
@datahot.xiahongbin.comDataHot data pick 5/5｜10.32 Release Notes (with behavior changes) (Preview)
PERIOD 数据类型为时间区间建模提供原生支持，有助于数据平台上的语义层和时序分析；行为变更包机制也直接影响平台运维评估。
Read / 中文全文：https://datahot.xiahongbin.com/e/009c95673c3b.html?utm_source=bluesky&utm_content=text
#DataEngineering #DataPlatform #数据
@powerbitips.bsky.social559 - No more clicking through Dataflows Gen 2 menus. Just describe the table you want to an agent and let it write the code, then verify the result.
@datahot.xiahongbin.comDataHot 今日精选 4/5｜当你无法信任自己的数据时会发生什么？
数据信任直接决定BI与数据平台能否产生价值，文章点出数据治理失效的典型循环与根因，能帮助企业避免工具投入打水漂。
阅读全文：https://datahot.xiahongbin.com/e/39da2eb43096.html?utm_source=bluesky&utm_content=text
#DataEngineering #DataProducts #数据
@powerbitips.bsky.social559 - Add four new gigs to thirty already optimized ones, and the old runtime rewrites all sixty four. The new runtime only touches the four that changed.
www.youtube.com/live/ODZbchQ...
#microsoftfabric #dataengineering #bigdata #optimization #techtalk
@lpi.orgExplore #opensource, #cloudarchitecture, #AI governance, #dataengineering, technical leadership, & more at TDC São Paulo 2026, Sept. 23–25, in person or online!
#LPI is a sponsor and participant. Visit the #LPI booth & get 20% off LPI exams.
More info: lpi.org/7d0u
@alextalksdatalakehouses.fyiJust got a copy of the Japanese Translation of O'Reilly’s “Apache Iceberg: The Definitive Guide”. Very cool to see!
Find this and all my other book projects at books.alexmerced.com
@datahot.xiahongbin.comDataHot 今日精选 5/5｜Snowflake自动数据分类：PII检测完整指南
数据从业者可了解Snowflake内置治理能力的自动化PII识别流程，以及分类结果如何与脱敏策略联动，是平台化数据治理的落地参考。
阅读全文：https://datahot.xiahongbin.com/e/4761ed6dc8dd.html?utm_source=bluesky&utm_content=card
#DataEngineering #DataPlatform #数据
@datahot.xiahongbin.comDataHot 今日精选 4/5｜Genie Agents扩展：深度分析与文件推理等新能力
数据从业者应关注，因为对话式数据Agent正从单轮问答走向可编程的多步深度分析，Genie Agents的Agent mode和API展示了ChatBI在企业业务场景中的落地形态。
阅读全文：https://datahot.xiahongbin.com/e/775f063ddfa3.html?utm_source=bluesky&utm_content=text
#DataEngineering #AIAgents #数据
@ai-bridge-tech.bsky.social高速データ処理ライブラリ「Polars」の次期メジャー版、2.0の先行リリースが登場。クエリエンジンの一新により、さらなるパフォーマンス向上とAPIの最適化が期待されます。データエンジニア必須のアップデートとなりそうです。 #Polars #DataEngineering
@northcoders.comReady to kickstart your tech career this month? 💪
Enrolment on our September bootcamps closes soon!
Don't miss the deadline ⚠️
Apply today: northcoders.com/our-courses/
#DataEngineering #SoftwareDevelopment
@datahot.xiahongbin.comDataHot data pick 3/5｜September 02, 2026
Looker 的更新将对话式分析验证、dbt 模型变更与 BI 查询可靠性打通，体现出 BI 工具与数据 Agent 在生产环境中的落地路径，值得数据平台团队关注。
Read / 中文全文：https://datahot.xiahongbin.com/e/7b6deb18642c.html?utm_source=bluesky&utm_content=text
#DataEngineering #BusinessIntelligence #数据
@datahot.xiahongbin.comDataHot 今日精选 2/5｜在Amazon SageMaker用Iceberg物化视图构建Medallion架构
该文展示如何用Iceberg物化视图将湖仓分层管道的调度、ETL与增量处理收敛为声明式SQL，对数据平台工程化有直接参考价值。
阅读全文：https://datahot.xiahongbin.com/e/52613ad8696c.html?utm_source=bluesky&utm_content=text
#DataEngineering #DataPlatform #数据
@checknumber.bsky.socialMyth: File-based data ingestion is just a transfer problem. Reality: API-first pipelines prevent schema drift and ensure consistency that manual batch processes struggle to maintain. Build for stability by integrating directly. https://docs.checknumber.ai/?utm_source=bsky #DataEngineering #API