Analytics Engineering with SQL and Dbt: Building Meaningful Data Models at Scale
暫譯: 使用 SQL 和 Dbt 的分析工程：構建可擴展的有意義數據模型
Machado, Rui, Russa, Helder
相關主題
商品描述
With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. DBT (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL.
Authors Rui Machado from Monstarlab and Helder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence.
With this book, you'll learn:
- What DBT is and how a DBT project is structured
- How DBT fits into the data engineering and analytics worlds
- How to collaborate on building data models
- The main tools and architectures for building useful, functional data models
- How to fit DBT into data warehousing and laking architecture
- How to build tests for data transformations
商品描述(中文翻譯)
隨著從資料倉儲轉向資料湖，資料現在在轉換之前就已經進入儲存庫，使工程師能夠將原始資料建模為乾淨且明確定義的資料集。DBT（data build tool）幫助您進一步處理資料。本書實用地向資料分析師、資料工程師、商業智慧（BI）開發人員和資料科學家展示如何通過使用動態 SQL 創建真正的自助式轉換平台。
作者 Rui Machado 來自 Monstarlab 和 Helder Russa 來自 Jumia 向您展示如何專注於價值交付而非架構和工程方面，快速交付新的資料產品。如果您對自己的業務非常了解，並具備將原始資料建模為乾淨且明確定義的資料集的技術技能，您將學會如何設計和交付資料模型，而不受任何技術影響。
通過本書，您將學到：
- DBT 是什麼以及 DBT 專案的結構
- DBT 如何融入資料工程和分析領域
- 如何協作建立資料模型
- 建立有用且功能性資料模型的主要工具和架構
- 如何將 DBT 融入資料倉儲和資料湖架構
- 如何為資料轉換建立測試
