Databricks Data Privacy

This content provides a comprehensive guide to managing data privacy within Databricks. It covers key topics like Delta Lake architecture, regional data isolation, GDPR/CCPA compliance, and Change Data Feed (CDF) usage. Through practical demos and hands-on labs, participants learn to use Unity Catalog features for securing sensitive data and ensuring compliance, empowering them to safeguard data integrity effectively.

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 second in the 'Advanced Data Engineering with Databricks' series.

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

Skill Level

Professional

Duration

Prerequisites

In this course, the content was developed for participants with these skills/knowledge/abilities:

• Ability to perform basic code development tasks using the Databricks Data Engineering & Data Science workspace (create clusters, run code in notebooks, use basic notebook operations, import repos from git, etc)

• Intermediate programming experience with PySpark

• Extract data from a variety of file formats and data sources

• Apply a number of common transformations to clean data

• Reshape and manipulate complex data using advanced built-in functions

• Intermediate programming experience with Delta Lake (create tables, perform complete and incremental updates, compact files, restore previous versions etc.)

• Beginner experience configuring and scheduling data pipelines using the Lakeflow Pipelines Editor

• Beginner experience defining Apache Spark™ Declarative Pipelines using PySpark

• Ingest and process data using Auto Loader and PySpark syntax

• Process Change Data Capture feeds with APPLY CHANGES INTO syntax

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Databricks has a delivery method for wherever you are on your learning journey

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Public and private courses taught by expert instructors across half-day to two-day courses

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Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Platform Administrator

Data Governance Fundamentals

In this course, you will explore the fundamentals of data governance and Unity Catalog. You will learn about the evolution and purpose of data catalogs, the architecture and components of Unity Catalog, and the importance of data quality, security, compliance, lineage, and auditing in governance.

Languages Available: English | 日本語 | 한국어

Free

Introductory

Data Engineer

Automated Deployment with Declarative Automation Bundles - Mandarin Chinese

本课程全面介绍了 DevOps 原则及其在 Databricks 项目中的应用。课程首先概述了核心 DevOps、DataOps、持续集成（CI）、持续部署（CD）和测试的基本概念，并探讨了如何将这些原则应用于数据工程管道。

课程随后聚焦于 CI/CD 流程中的持续部署，介绍用于项目部署的工具，包括 Databricks REST API、SDK 和 CLI。您将了解声明式自动化包（DAB）及其在 CI/CD 流程中的作用，深入学习其关键组件、文件夹结构，以及它们如何简化在 Databricks 中跨各种目标环境的部署流程。您还将学习如何使用 Databricks CLI 为多个具有不同配置的环境添加变量、修改、验证、部署和执行声明式自动化包。

最后，课程介绍如何将 Visual Studio Code 作为交互式开发环境（IDE），用于在本地构建、测试和部署声明式自动化包，从而优化开发流程。课程最后介绍如何使用 GitHub Actions 自动化部署管道，以增强声明式自动化包的 CI/CD 工作流。

完成本课程后，您将具备使用声明式自动化包自动化 Databricks 项目部署的能力，并能够通过 DevOps 实践提升工作效率。

注意：

Databricks Academy 正在将所有自定进度课程从视频讲座转为更简洁的 PDF 格式，其中包含幻灯片和讲义。请注意，演示视频仍将以原始格式提供。我们非常希望听到您对这一变化的看法，因此请通过课程末尾的课程调查分享您的反馈。感谢您成为我们学习社区的一员！本课程是 ‘Advanced Data Engineering with Databricks’ 系列的第四门课程。

Languages Available: English | 日本語 | 한국어

Free

Professional

Building RAG Agents with Agent Bricks

This course provides hands-on training for building retrieval agents on Databricks. Participants will learn to create Genie Agents for unstructured data, perform information retrieval with Lakebase Search, parse and transform unstructured documents into structured data using AI Functions, chunk text for semantic retrieval, and build AI Search indexes with multiple search modes.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.

Free

Associate