Create powerful, interactive dashboards and visualizations with the open-source Apache Superset BI platform

What you'll learn

Set up connections to databases like PostgreSQL, MySQL, Snowflake, BigQuery, etc., and understand dataset management.

Design and build dynamic dashboards with cross-filtering, tabs, custom layouts, and filters for business storytelling.

Leverage SQL Lab to write, save, and reuse SQL queries for more advanced data analysis.

Build a complete, interactive dashboard project that simulates a real business scenario in sales, marketing, or finance.

Step-by-step instructions to install Superset using Docker and alternative methods, with full configuration walkthroughs.

Requirements

Familiarity with tables, rows, columns, and basic SQL concepts

Description

Mastering Apache Superset: Build Modern BI DashboardsAre you looking for a fast, modern, and open-source alternative to expensive BI tools like Tableau or Power BI?Welcome to "Mastering Apache Superset" — your complete guide to building beautiful, interactive dashboards and unlocking insights with data, using one of the most popular open-source business intelligence platforms available today.Whether you're a data analyst, developer, data engineer, or just someone passionate about working with data, this course will help you turn raw data into meaningful, visual stories—without needing to be a coding expert.What This Course Covers:Module 1: Getting StartedWhat is Apache Superset and why it's gaining popularity in data teams globallyHow it fits into a modern data stackInstalling Superset using Docker (and alternatives if needed)Module 2: Connecting to Your DataSetting up connections to PostgreSQL, MySQL, DuckDB, etc.Creating and managing datasetsWriting SQL queries and building virtual datasetsModule 3: Visualizing Your DataExplore 30+ built-in chart typesConfigure filters, tooltips, custom metrics, and drilldownsBest practices for building clean and effective visualizationsModule 4: Dashboards That Tell a StoryCombine multiple charts into dynamic dashboardsCross-filtering, interactivity, and layout customizationSharing, exporting, and embedding dashboards in other platformsModule 5: SQL Lab for AnalystsUse SQL Lab to write, save, and reuse queriesAnalyze large datasets directly in the browserIntegrate SQL Lab outputs into dashboardsModule 6: User Access & SecurityRole-based access control (RBAC)Implementing row-level security (RLS)Managing users, permissions, and team collaborationModule 7: Superset AdministrationUnderstanding Superset's architectureConfiguring performance and cachingDeployment options for production environmentsBy the End of This Course, You'll Be Able To:Confidently install, configure, and use Apache Superset for business intelligenceCreate visually compelling dashboards that tell clear, actionable storiesWork with real databases and datasets in a highly interactive environmentShare your insights with decision-makers or clients through intuitive visuals

Overview

Section 1: Introduction

Lecture 1 Introduction to Apache Superset

Lecture 2 What is Apache Superset?

Lecture 3 Key Features and Capabilities

Lecture 4 Superset vs Other BI Tools

Section 2: Installation and Setup

Lecture 5 Installing Superset using Docker (Recommended)

Lecture 6 Installing Superset using Python

Lecture 7 Understanding Superset Architecture

Section 3: Superset UI Walkthrough

Lecture 8 Navigating the Superset Interface

Lecture 9 Understanding Roles and Permissions

Section 4: Data Connection and Dataset Creation

Lecture 10 Connecting to Databases (PostgreSQL)

Lecture 11 Connecting to Databases (DuckDB)

Lecture 12 Connecting to Databases (MySQL)

Lecture 13 Base Table Introduction

Lecture 14 Course Materials

Section 5: SQL Basics

Lecture 15 Installation on Mac

Lecture 16 Installation on Windows

Lecture 17 Database & Schema

Lecture 18 Create Base Tables

Lecture 19 Insert into Tables

Lecture 20 Create and Drop Tables

Lecture 21 Select Columns

Lecture 22 Experiments: Select (Without Tables)

Lecture 23 Experiments: Mathematical Expression

Lecture 24 Distinct

Lecture 25 Experiments: Distinct

Lecture 26 Aggregate Functions

Lecture 27 String Functions

Lecture 28 Sub-Strings

Lecture 29 Concat

Lecture 30 Limit & Offset

Lecture 31 Alias

Lecture 32 Filters with Numeric

Lecture 33 Filters with String

Lecture 34 Filters with Date

Lecture 35 IN Clause

Lecture 36 Cast: Decimal & Integers

Lecture 37 Like

Lecture 38 Default Values

Lecture 39 Inner Queries

Lecture 40 Inner Queries: Any & ALL

Lecture 41 Union

Lecture 42 Union All

Lecture 43 Intersect

Lecture 44 Group By

Lecture 45 Group By with Having

Lecture 46 Group By with Filters

Lecture 47 Order By

Lecture 48 Order By with Filters

Section 6: SQL Lab

Lecture 49 Writing and Saving SQL Queries

Lecture 50 Creating Datasets

Lecture 51 Save Custom Datasets

Section 7: Exploring and Visualizing Data

Lecture 52 Charts Architecture

Lecture 53 Charts GUI walk through

Lecture 54 First Chart on Big Number

Lecture 55 Create Table using Charts

Lecture 56 Active Products using Big Number

Lecture 57 Applying Ordering on Chart

Lecture 58 Customization on Charts

Lecture 59 Create Virtual Dataset

Lecture 60 Line Line Chart with Virtual Dataset

Section 8: Applying Filters & Conditions

Lecture 61 Filter Introduction Screen

Lecture 62 Applying Filters on Integer

Lecture 63 Appying Filters on String Fields

Lecture 64 Like Filtering on String Fields

Lecture 65 IN Clause Filtering

Lecture 66 Between Clause Filtering

Lecture 67 Chart Customization and Formatting

Lecture 68 Number Formatting on Charts

Section 9: Dashboards

Lecture 69 Adding Filters, Tabs, and Layouts

Lecture 70 Cross-filtering Between Charts

Lecture 71 Filters with Dividers on Dashboard

Lecture 72 Pagination in Table using Dashboard

Lecture 73 Human Readable Column Names

Lecture 74 Assign Permissions to new User

Section 10: Advanced Features

Lecture 75 Row-level Security (RLS)

Lecture 76 Row-level Security (RLS)

Section 11: Superset Administration

Lecture 77 Config File and Environment Variables

Lecture 78 Installation of Production Environment

Lecture 79 Performance Optimization

Lecture 80 Backup and Restore

Lecture 81 Logging and Monitoring

Data Analysts and Business Intelligence Professionals,Data Engineers and Developers,Anyone Exploring Alternatives to Tableau, Power BI, or Looker