Monitoring and Optimizing Apache Spark Workloads on Databricks

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.

Note: This course is part of the 'Advanced Data Engineering with Databricks' course series.

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

This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and configure alerts. This course will prepare you to take the Databricks Certified Data Analyst Associate exam.

This course consists of two four-hour modules. 

SQL Analytics on Databricks

In this course, you'll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights. 

You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL. 

Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.

AI/BI for Data Analysts

In this course, you’ll learn how to use the features Databricks provides for business intelligence needs: AI/BI Dashboards and AI/BI Genie. As a Databricks Data Analyst, you will be tasked with creating AI/BI Dashboards and AI/BI Genie Spaces within the platform, managing the access to these assets by stakeholders and necessary parties, and maintaining these assets as they are edited, refreshed, or decommissioned over the course of their lifespan. This course intends to instruct participants on how to design dashboards for business insights, share those with collaborators and stakeholders, and maintain those assets within the platform. Participants will also learn how to utilize AI/BI Genie Spaces to support self-service analytics through the creation and maintenance of these environments powered by the Databricks Data Intelligence Engine.

This course is designed for data professionals who want to explore the data warehousing capabilities of Databricks. Assuming no prior knowledge of Databricks, it provides an introduction to leveraging Databricks as a modern cloud-based data warehousing solution. Learners will explore how use the Databricks Data Intelligence Platform to ingest, transform, govern, and analyze data efficiently using the industry-standard TCP-DI dataset as a reference. Learners will also explore Genie, an innovative Databricks feature that simplifies data exploration through natural language queries. By the end of this course, participants will be equipped with the foundational skills to implement and optimize a data warehouse using Databricks.

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