Advanced Data Engineering with Databricks
This course serves as an appropriate entry point to learn Advanced Data Engineering with Databricks.
Below, we describe each of the four, four-hour modules included in this course.
Databricks Streaming and Delta Live Tables
This course provides a comprehensive understanding of Spark Structured Streaming and Delta Lake, including computation models, configuration for streaming read, and maintaining data quality in a streaming environment.
Databricks Data Privacy
This content is intended for the learner persona of data engineers or for customers, partners, and employees who complete data engineering tasks with Databricks. It aims to provide them with the necessary knowledge and skills to execute these activities effectively on the Databricks platform.
Databricks Performance Optimization
In this course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, photons, and more.
Automated Deployment with Databricks Asset Bundles
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 Databricks Asset 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 Databricks Asset 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 Databricks Asset 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 Databricks Asset Bundles.
By the end of this course, you will be equipped to automate Databricks project deployments with Databricks Asset Bundles, improving efficiency through DevOps practices.
Languages Available: English | 日本語 | Português BR | 한국어
Prerequisites
- Ability to perform basic code development tasks using the Databricks Data Engineering and 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 Delta Live Tables (DLT) UI
- Beginner experience defining Delta Live Tables pipelines using PySpark
- Ingest and process data using Auto Loader and PySpark syntax
- Process Change Data Capture feeds with APPLY CHANGES INTO syntax
- Review pipeline event logs and results to troubleshoot DLT syntax
- Strong knowledge of the Databricks platform, including experience with Databricks Workspaces, Apache Spark, Delta Lake, the Medallion Architecture, Unity Catalog, Delta Live Tables, and Workflows. In particular, knowledge of leveraging Expectations with DLTs.
- Experience in data ingestion and transformation, with proficiency in PySpark for data processing and DataFrame manipulation. Candidates should also have experience writing intermediate-level SQL queries for data analysis and transformation.
- Proficiency in Python programming, including the ability to design and implement functions and classes, and experience with creating, importing, and utilizing Python packages.
- Familiarity with DevOps practices, particularly continuous integration and continuous delivery/deployment (CI/CD) principles.
- A basic understanding of Git version control.
- Prerequisite course DevOps Essentials for Data Engineering Course
Outline
Databricks Streaming and Delta Live Tables
Streaming Data Concepts
Introduction to Structured Streaming
Demo: Reading from a Streaming Query
Streaming from Delta Lake
Lab: Streaming Query Lab
Aggregation, Time Windows, Watermarks
Event Time + Aggregatios over Time Windows
Lab: Stream Aggregation Lab
Demo: Windowed Aggregation with Watermark
Data Ingestion Pattern
Demo: Auto Load to Bronze
Demo: Stream from Multiplex Bronze
Quality Enforcement Pattern
Demo: Quality Enforcement
Lab: Streaming ETL Lab
Databricks Data Privacy
Regulatory Compliance
Data Privacy
Key Concepts and Components
Audit Your Data
Data Isolation
Demo: Securing Data in Unity Catalog
Pseudonymization & Anonymization
Summary & Best Practices
Demo: PII Data Security
Capturing Changed Data
Deleting Data in Databricks
Demo: Processing Records from CDF and Propagating Changes
Lab: Propagating Changes with CDF Lab
Databricks Performance Optimization
DevOps Spark UI Introduction
Introduction to Designing Foundation
Demo: File Explosion
Data Skipping and Liquid Clustering
Lab: Data Skipping and Liquid Clustering
Skew
Shuffles
Demo: Shuffle
Spill
Lab: Exploding Join
Serialization
Demo: User-Defined Functions
Fine-Tuning: Choosing the Right Cluster
Pick the Best Instance Types
Automated Deployment with Databricks Asset Bundles
DevOps Review
Continuous Integration and Continuous Deployment/Delivery (CI/CD) Review
Demo: Course Setup and Authentication
Deploying Databricks Projects
Introduction to Databricks Asset Bundles (DABs)
Demo: Deploying a Simple DAB
Lab: Deploying a Simple DAB
Variable Substitutions in DABs
Demo: Deploying a DAB to Multiple Environments
Lab: Deploy a DAB to Multiple Environments
DAB Project Templates Overview
Lab: Use a Databricks Default DAB Template
CI/CD Project Overview with DABs
Demo: Continuous Integration and Continuous Deployment with DABs
Lab: Adding ML to Engineering Workflows with DABs
Developing Locally with Visual Studio Code (VSCode)
Demo: Using VSCode with Databricks
CI/CD Best Practices for Data Engineering
Next Steps: Automated Deployment with GitHub Actions
Upcoming Public Classes
Date | Time | Language | Price |
|---|---|---|---|
May 12 - 13 | 09 AM - 05 PM (Europe/London) | English | $1500.00 |
May 19 - 22 | 11 AM - 03 PM (Asia/Singapore) | English | $1500.00 |
May 19 - 22 | 02 PM - 06 PM (Europe/Paris) | English | $1500.00 |
May 19 - 20 | 09 AM - 05 PM (America/New_York) | English | $1500.00 |
May 26 - 27 | 09 AM - 05 PM (Australia/Sydney) | English | $1500.00 |
May 26 - 29 | 02 PM - 06 PM (America/New_York) | English | $1500.00 |
Jun 16 - 19 | 11 AM - 03 PM (Asia/Singapore) | English | $1500.00 |
Jun 16 - 17 | 09 AM - 05 PM (America/New_York) | English | $1500.00 |
Jun 23 - 24 | 09 AM - 05 PM (Australia/Sydney) | English | $1500.00 |
Jun 23 - 24 | 09 AM - 05 PM (Europe/Paris) | English | $1500.00 |
Jun 23 - 26 | 02 PM - 06 PM (America/New_York) | English | $1500.00 |
Jul 07 - 08 | 09 AM - 05 PM (Australia/Sydney) | English | $1500.00 |
Jul 07 - 08 | 09 AM - 05 PM (Europe/London) | English | $1500.00 |
Jul 14 - 17 | 02 PM - 06 PM (Europe/Paris) | English | $1500.00 |
Jul 14 - 15 | 09 AM - 05 PM (America/New_York) | English | $1500.00 |
Jul 21 - 24 | 11 AM - 03 PM (Asia/Singapore) | English | $1500.00 |
Jul 21 - 24 | 02 PM - 06 PM (America/New_York) | English | $1500.00 |
Aug 04 - 05 | 09 AM - 05 PM (Australia/Sydney) | English | $1500.00 |
Aug 04 - 05 | 09 AM - 05 PM (Europe/Paris) | English | $1500.00 |
Aug 04 - 05 | 09 AM - 05 PM (America/Los_Angeles) | English | $1500.00 |
Aug 18 - 19 | 09 AM - 05 PM (Europe/London) | English | $1500.00 |
Aug 25 - 28 | 11 AM - 03 PM (Asia/Singapore) | English | $1500.00 |
Aug 25 - 28 | 02 PM - 06 PM (Europe/Paris) | English | $1500.00 |
Aug 25 - 28 | 02 PM - 06 PM (America/New_York) | English | $1500.00 |
Sep 01 - 02 | 09 AM - 05 PM (Europe/Paris) | English | $1500.00 |
Sep 02 - 03 | 09 AM - 05 PM (America/Los_Angeles) | English | $1500.00 |
Sep 15 - 16 | 09 AM - 05 PM (Europe/London) | English | $1500.00 |
Sep 15 - 16 | 09 AM - 05 PM (America/New_York) | English | $1500.00 |
Sep 22 - 25 | 11 AM - 03 PM (Asia/Singapore) | English | $1500.00 |
Sep 22 - 25 | 02 PM - 06 PM (America/New_York) | English | $1500.00 |
Oct 13 - 14 | 09 AM - 05 PM (Europe/London) | English | $1500.00 |
Oct 13 - 14 | 09 AM - 05 PM (America/New_York) | English | $1500.00 |
Oct 20 - 23 | 11 AM - 03 PM (Asia/Singapore) | English | $1500.00 |
Oct 27 - 30 | 02 PM - 06 PM (Europe/Paris) | English | $1500.00 |
Oct 27 - 30 | 02 PM - 06 PM (America/New_York) | English | $1500.00 |
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