Databricks SQL for Data Analysts

Course Curriculum

Chapter 1: Set Up and Overview of Databricks

Lecture 1: Course Overview

Lecture 2: Introduction to Big Data (Optional)

Lecture 3: Apache Spark Ecosystem (Optional)

Lecture 4: Overview of Databricks

Lecture 5: Note for Students using their Organisational Azure Tenant

Lecture 6: Azure Account Set Up

Lecture 7: Azure Portal Overview

Lecture 8: Cost Management and Billing

Lecture 9: Creating a Databricks Premium Workspace

Lecture 10: Databricks Workspace User Interface

Lecture 11: Unity Catalog Overview

Lecture 12: Enabling Unity Catalog – Overview

Lecture 13: ADLS Overview and Storage Creation

Lecture 14: Access Connector for Databricks

Lecture 15: Global Administrator Pre-requisite Check

Lecture 16: Enabling Unity Catalog

Lecture 17: Creating a SQL Warehouse

Chapter 2: Introduction to Queries

Lecture 1: Your First Query

Lecture 2: Switching Catalogs and Schemas

Lecture 3: Scheduling Queries

Lecture 4: Adding Comments to Queries

Lecture 5: Course Resources – SQL Code Download

Chapter 3: Catalogs, Schemas, Tables and Views

Lecture 1: Creating Catalogs

Lecture 2: Creating Schemas

Lecture 3: Data Types in Databricks SQL

Lecture 4: Overview of Tables in Databricks

Lecture 5: Creating Managed Tables with SQL

Lecture 6: Creating Managed Tables in Hive Metastore

Lecture 7: Creating Managed Tables using the Data Explorer

Lecture 8: Creating an External Storage Location

Lecture 9: Creating External Tables

Lecture 10: Overriding Unity Catalog’s Default Managed Table Storage Location

Lecture 11: Truncate Table

Lecture 12: Alter Table

Lecture 13: Drop Tables, Schemas and Catalogs

Chapter 4: Data Analysis with SQL

Lecture 1: Select Statement Recap

Lecture 2: Select Distinct

Lecture 3: Note on the JC_BIKE_DATA_22 Table

Lecture 4: Filtering Records with the WHERE Clause

Lecture 5: Filtering Records Based on Multiple Conditions

Lecture 6: Filtering Records with the IN and LIKE Operators

Lecture 7: Deleting Records

Lecture 8: Databricks SQL Built In Functions Overview

Lecture 9: String Functions

Lecture 10: Numerical Functions

Lecture 11: Date and Timestamp Functions

Lecture 12: Converting Strings to Dates/Timestamps

Lecture 13: Conditional Functions

Lecture 14: Aggregate Functions

Lecture 15: Group By Clause

Lecture 16: Filtering Aggregated Tables with the Having Clause

Lecture 17: Joining Tables Overview

Lecture 18: Joining Tables Demo

Lecture 19: Order By and Limit Clauses

Lecture 20: SQL Order of Execution

Lecture 21: Subqueries

Lecture 22: Views

Lecture 23: Set Operators

Lecture 24: SQL Challenge 1

Lecture 25: SQL Challenge 2

Lecture 26: SQL Challenge 3

Lecture 27: SQL Challenge 4

Lecture 28: SQL Challenge 5

Lecture 29: Schema Clean Up

Chapter 5: Delta Lake

Lecture 1: Medallion Architecture and Last Mile ETL

Lecture 2: Medallion Architecture Demo

Lecture 3: Benefits of Delta File Format

Lecture 4: Upsert / Merge Into

Lecture 5: Table Audit History and Time Travel

Chapter 6: Query Alerts and Monitoring

Lecture 1: Query History and Profile

Lecture 2: Query Caching in Databricks SQL

Lecture 3: Query Alerts

Chapter 7: Visualizations and Dashboards in Databricks SQL

Lecture 1: Visualizations and Dashboards Overview

Lecture 2: Our First Chart in Databricks SQL

Lecture 3: Line and Area Charts

Lecture 4: Combo Chart

Lecture 5: Pie Chart

Lecture 6: Scatter and Bubble Plots

Lecture 7: Histograms

Lecture 8: Box Plots

Lecture 9: Heatmaps

Lecture 10: Sankey Charts

Lecture 11: Tables

Lecture 12: Pivot Tables

Lecture 13: Counters

Lecture 14: Additional Guidance on Charts in Databricks SQL

Lecture 15: Exploratory Data Analysis Challenge

Lecture 16: Adding Missing Data to the JC_BIKE_DATA_22 Table

Lecture 17: Creating a View to Simplify Upcoming Demos

Lecture 18: Query Filters

Lecture 19: Query Parameters

Lecture 20: Query Parameters (Dates)

Lecture 21: Dashboards in Databricks