Get Started with Databricks for Data Warehousing

This course provides a comprehensive 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. You’ll learn about the AI-driven features that enhance data transformation and analysis on the Databricks Data Intelligence Platform. Designed for data warehousing practitioners, this course provides you with the foundational information needed to begin building and managing high-performant, AI-powered data warehouses on Databricks.

This course is designed for those starting out in data warehousing and those who would like to execute data warehousing workloads on Databricks. Participants may also include data warehousing practitioners who are familiar with traditional data warehousing techniques and concepts and are looking to expand their understanding of how data warehousing workloads are executed on Databricks.

Skill Level

Onboarding

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

A basic understanding of data warehousing principles and topics such as database administration, SQL, data manipulation, and storage.

Outline

Databricks Overview

Databricks Infrastructure
Databricks Data Intelligence Platform
Unity Catalog Overview
Databricks Workspace Walkthrough

Using Databricks for Data Warehousing

Introduction to Data Warehousing with Databricks
Databricks SQL Warehouses
Delta Lake Overview
Using Delta Lake features with Databricks SQL

Data Ingestion and Transformation

Delta Lake UniForm
Data Ingestion Techniques Overview
Data Ingestion Techniques
Data Transformation
Exploring Data Transformation in Databricks

Data Orchestration and Querying Capabilities

Orchestration in Databricks
Setting up and Managing Serverless Workflows
Databricks Querying Capabilities

Data Presentation

Introduction to AI/BI
Creating a Dashboard in Databricks
Creating Genie Spaces

Data Warehousing Comprehensive Lab

Upcoming Public Classes

Date	Time	Language	Price
Date	Time	Language	Price	Apr 09	09 AM - 11 AM (America/Los_Angeles)	English	Free
Apr 15	12 PM - 02 PM (Asia/Singapore)	English	Free
May 07	12 PM - 02 PM (Asia/Kolkata)	English	Free
May 07	03 PM - 05 PM (Europe/London)	English	Free
May 14	02 PM - 04 PM (Asia/Kolkata)	English	Free
May 16	09 AM - 11 AM (America/Los_Angeles)	English	Free
May 26	12 PM - 02 PM (Asia/Singapore)	English	Free
Jun 04	03 PM - 05 PM (Europe/London)	English	Free
Jun 18	12 PM - 02 PM (Asia/Singapore)	English	Free
Jun 20	09 AM - 11 AM (America/Los_Angeles)	English	Free

Public Class Registration

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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

Data Engineer

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 to secure sensitive data and ensure compliance, empowering them to safeguard data integrity effectively.

Note: This course is the second in the 'Advanced Data Engineering with Databricks' series.

Free

Professional

Data Architect

Data Modeling Strategies

This course offers a deep dive into designing data models within the Databricks Lakehouse environment, and understanding the data products lifecycle. Participants will learn to align business requirements with data organization and model design leveraging Delta Lake and Unity Catalog for defining data architectures, and techniques for data integration and sharing.

Free

Associate

Data Engineer

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.

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

Free

Professional