While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
在本課程中,您將實際操作 Looker 的 LookML。您將學習如何編寫 LookML 程式碼,建立新的維度和測量指標、建立衍生資料表並彙整至探索、篩選探索,以及在 LookML 中定義快取政策。
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.