Data Analysis with Databricks

This content provides a comprehensive introduction to Databricks SQL. It is designed to support individuals seeking the Associate Data Analysis of Databricks SQL certification. Participants will learn about ingesting data, writing queries, producing visualizations and dashboards, and connecting Databricks SQL to additional tools using Partner Connect. This course contains a lab exercise to provide you with hands-on experience in data visualization and dashboards.

Skill Level

Associate

Duration

Prerequisites

At a minimum, you should be familiar with the following before attempting to take this content:

General SQL fundamentals (e.g. write basic SELECT from statements)

Courses you should consider taking before taking this content include:

Databricks Lakehouse Fundamentals

Outline

Databricks SQL Services and Capabilities

Get Started with Databricks SQL
Setting Up a Catalog and Schema
Data Importing
A Quick Query and Visualization

Unity Catalog in Databricks SQL
Lakehouse Architecture

Integrations

Data Management in Databricks SQL

Databricks SQL Warehouses
Delta Lake in Databricks SQL

Data Security

Data Visualization and Dashboarding

Data Visualizations and Dashboards

Lab: Data Visualizations and Dashboards
Create Interactive Dashboards
Databricks SQL in Production

Self-Paced

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

See all our registration options

Registration options

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

Instructor-Led

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

Blended Learning

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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Skills@Scale

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

Machine Learning Practitioner

Machine Learning Operations

This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.

Note: This is the fourth course in the 'Machine Learning with Databricks’ series.

Build Data Pipelines with Delta Live Tables

In this course, you’ll learn how to define and schedule data pipelines that incrementally ingest and process data through multiple tables in the lakehouse using Delta Live Tables (DLT) in Spark SQL and Python. The course covers how to get started with DLT, how DLT tracks data dependencies in data pipelines, how to configure and run data pipelines using the Delta Live Tables UI, how to use Python or Spark SQL to define data pipelines that ingest and process data through multiple tables in the lakehouse using Auto Loader and DLT, how to use APPLY CHANGES INTO syntax to process Change Data Capture feeds, and how to review event logs and data artifacts created by pipelines and troubleshoot DLT syntax.

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

Paid & Subscription

Lab

Associate

Machine Learning Practitioner

Data Preparation for Machine Learning

This course focuses on the fundamentals of preparing data for machine learning using Databricks. Participants will learn essential skills for exploring, cleaning, and organizing data tailored for traditional machine learning applications. Key topics include data visualization, feature engineering, and optimal feature storage strategies. Through practical exercises, participants will gain hands-on experience in efficiently preparing data sets for machine learning within the Databricks. This course is designed for associate-level data scientists and machine learning practitioners. and individuals seeking to enhance their proficiency in data preparation, ensuring a solid foundation for successful machine learning model deployment.

Note: This is the first course in the 'Machine Learning with Databricks’ series.

Paid & Subscription

Lab

Associate