2023年2月1日 · We have a new logo, a new website, and a new vision. Our new logo is a retro-futuristic play on data and space: a celestial body coupled with elements of a functional chart.

Y42's Turnkey Data Orchestration Platform gives you a unified space to build, monitor and maintain a robust flow of data to power your business

Find the Y42 style guide with brand assets such as logos, colors, fonts, and more.

Y42 is the first fully managed Modern DataOps Cloud. It is purpose-built to help companies easily design production-ready data pipelines on top of their Google BigQuery or Snowflake cloud data...

Y42's Turnkey Data Orchestration Platform gives you a unified space to build, monitor and maintain a robust flow of data to power your business

2021年3月3日 · Have you ever wondered why we’re named Y42? 🤔 Well, if The Hitchhiker's Guide to the Galaxy movie poster isn’t enough of a clue, let’s just say that 42 is the answer to “the …

商標資訊 資料來源：經濟部智慧財產局公開資料 商標權人 數據智能公司 DATOS-INTELLIGENCE GMBH 登記地址 德國 商標權人 數據智能公司 DATOS-INTELLIGENCE GMBH 登記地址 德國 商標名稱 y42 商標樣態 平面 商標種類 商標 圖樣顏色 墨色 申請案號 110063686 申請日期 2021-09-02 註冊編號 02267332 註冊日期 2022-12-01 註冊 ...

Y42 is a data pipeline management platform with a focus on enabling efficient engineering processes, robust governance and smooth collaboration. With Y42, you can build and manage the entire lifecycle of your data warehouse activities: Integrate data from a myriad of sources with minimal setup (E xtract & L oad)

2020年12月1日 · Y42 is the one platform for all your data needs. Integrate and transform all your data, analyze it at rocket speed, and align your entire organization. Watch the following video for a quick overview of what you can do with Y42! What can you do with Y42? Y42 allows you to easily import your data sources and integrate them with other applications.

2021年10月25日 · Founded in 2020 and based in Berlin, Y42 is the full-stack data platform that anyone can run. Founder Hung Dang set up the company following experiences working in start-ups and data consulting where he encountered organisations suffering from the same data pain points time and again.