Databricks Fundamentals Accreditation - Mandarin Chinese

本课程专为希望从根本上了解 Databricks 及 Databricks 数据智能平台的所有人而设计。在整个课程中，您将了解作为该平台一部分所提供的各种功能和产品，以及为什么这些功能和产品对所有希望利用其数据和 AI 资产的力量来加速业务发展的企业都具有价值。

这些视频按建议的顺序提供，但您也可以按自己喜欢的任意顺序观看。此外，我们建议您在尝试 Databricks 基础知识认证评估之前，先观看所有可用的视频内容。

请注意，我们假定您此前没有关于 Databricks 或数据管理平台的技术知识。

Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français

This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.

The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Declarative Automation Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Declarative Automation Bundles for multiple environments with different configurations using the Databricks CLI.

Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Declarative Automation Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Declarative Automation Bundles.

By the end of this course, you will be equipped to automate Databricks project deployments with Declarative Automation Bundles, improving efficiency through DevOps practices.

Note: 

1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!

2. This course is the fourth in the 'Advanced Data Engineering with Databricks' series.

Languages Available: English | 日本語 | 한국어

This course provides a comprehensive, hands-on overview of Databricks' modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. Working end-to-end with a fictional retailer (Vintage Audio Co.), you will explore the workspace, query governed Unity Catalog tables, keep Delta tables fast for analytical reads, load data incrementally with Auto Loader, model a star schema, and deliver consistent insights through Unity Catalog metric views — all from a single, governed environment, with AI-driven features (Predictive Optimization, Genie Code) built in throughout.