Overview
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.
Prerequisites
Participants should have:
- A working knowledge of SQL for data analysis. Learners should have attended QATSQL or have equivalent knowledge.
- Familiarity with data formats such as CSV, JSON, TXT, and Parquet
- Understanding of how data is created, stored, and managed
- Prior experience or familiarity with the Databricks Workspace UI
- A basic understanding of dashboard use in business intelligence
Target audience
This course is ideal for:
- Data analysts and BI professionals looking to use Databricks for SQL-based analytics
- Business professionals seeking to convert raw data into actionable insights
- Teams responsible for producing dashboards, reporting tools, and automated alerts
- Organisations adopting Databricks to scale data intelligence and self-service analytics
Delegates will learn how to
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.
Outline
SQL Analytics on Databricks
Data Discovery
- Using Unity Catalog as a Data Discovery Tool
- Understanding Data Object Ownership
- Use Unity Catalog to Locate and Inspect Datasets
Data Importing
- Ingesting Data into Databricks
- Uploading Data to Databricks Using the UI
- Programmatic Exploration and Data Ingestion to Unity Catalog
- Import Data into Databricks
SQL Execution
- Databricks SQL and Databricks SQL Warehouses
- The Unified SQL Editor
- Manipulate and Transform Data with Databricks SQL
- Creating Views with Databricks SQL
- Manipulate and Analyze a Table
Query Analysis
- Databricks Photon and Optimization in Databricks
- Query Insights
- Best Practices for SQL Analytics
AI/BI for Data Analysts
- Dashboards and Visualizations in Databricks
- AI/BI Dashboards
- Just enough SQL
- Designing Datasets for Dashboards
- Creating Visualizations and adding Summary Statistics to Dashboards
- AI Enhanced Features
- Filters
- Sharing Dashboards with Stakeholders and Others
- Managing Dashboards in Production
- Dashboard and Visualization Lab Activity
AI/BI Genie
- AI/BI Genie
- Developing Genie Spaces
- Sharing Genie Spaces
- AI/BI Genie Development Activity Lab

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