
Set up Apache Superset in an Ubuntu Linux environment for a hands-on learning experience, install and configure it, connect to databases, upload data, and build interactive charts and dashboards.
Core concepts, open-source advantages, and the modern BI landscape.
Explore business intelligence, a suite of software applications that analyze an organization's raw data using data mining, online analytics processing, and business reporting. For example, Tableau demonstrates these BI capabilities.
Comparing Superset against Power BI, Tableau, Looker, and Metabase
Explore Apache Superset's no-code and SQL-based data exploration with drag-and-drop interfaces, versatile visualizations, and secure, scalable data connectivity for BI, data engineering, and product analytics.
Compare Apache Superset with Power BI, Tableau, and Looker to highlight open source freedom, self-hosted deployment, cost efficiency, SQL-based exploration, data visualization, diverse data connections, and RBAC.
Deep dive into Superset components, web servers, SQLAlchemy, and metadata database operations.
System prerequisites, image architectures, and local development standards.
Step-by-step setup on Windows, macOS, and Linux.
Initializing configuration, secret key generation, database URIs, and environment variables.
Initializing the metadata database, creating admin credentials, and managing start, stop, and restart routines.
Install apache superset on ubuntu 24.04 with python 3.10, setting up dependencies, a virtual environment, upgrading the database, creating an admin, loading examples, and running the server.
Enhance your course taking experience by adjusting playback speed and video quality, using captions and auto-generated transcripts, and considering leaving a review to help others.
Driver installation patterns, connection strings, and protocol handling.
Connecting PostgreSQL and MySQL instances.
Connecting Snowflake, Google BigQuery, and Databricks.
Uploading and configuring CSV and Excel files into database tables.
Multi-database query interface, schema navigation, and query history.
Working with CTEs, aggregate operations, window functions, and subqueries.
Managing timeouts, query sharing, exporting query results, and caching queries.
Begin a hands-on HR analytics dashboard project in Apache Superset, exploring local versus cloud setup, logging in with Gmail, and initial design steps in a guided environment.
Develop an HR analytics dashboard in Apache Superset, generating graphs for attrition, age distribution by gender, job satisfaction, and income by gender; include department counts and average income by department.
Learn to build an HR analytics dashboard by connecting Google Sheets data, creating a database, and running SQL queries on employee attrition datasets for a practical data engineering workflow.
Build and customize an HR analytics dashboard in Apache Superset by creating charts, such as a gender distribution and an attrition by group chart, and save the first dashboard.
Build an hr analytics dashboard by creating charts for job satisfaction across industries and police, then add and save a monthly income by gender chart.
Create charts in Apache Superset to analyze HR analytics: show monthly income by gender, average salary by gender, and employed by department, with gender breakdowns and generation-based insights.
Part 6 of the hr analytics dashboard project builds an apache superset visualization of education level and degree types, attrition, department breakdowns, and income, using pie charts and graphs.
Builds an HR analytics dashboard in Apache Superset by creating three charts, including a pie chart for job satisfaction, median salary by job, and an attrition breakdown.
Develop HR analytics dashboards by adding charts for job growth, attrition, and job satisfaction, using a current manager and environmental satisfaction matrix to compare averages.
Use Apache Superset to build an HR analytics dashboard, charting work-life balance by department and analyzing attrition and business travel trends.
Build and customize an HR analytics dashboard in Apache Superset by creating charts for attrition by distance from home, grouping by job role, and applying color and filter options.
Build an Olympic analytics dashboard in Apache Superset using a free online instance, log in, access workspace, and name the dashboard olympic analytics.
Create a quick analytics dashboard to visualize Olympic medals by country with a world map and analyze age distribution and gender trends in gold medalists over time.
Upload the lead_events file (not CSV) to Google Sheets, then connect the sheet as a database in Superset and import the data into the Olympic Analytics Dashboard.
Load the Olympic dataset into Apache Superset in a preset cloud environment, use the SQL editor to select the Olympic table, and verify data availability and medal data.
Create charts from Olympic dataset by selecting medals and country, add a Google Sheet dataset, and save charts to the Olympic analytics dashboard showing gold, silver, and bronze by country.
Build and customize charts in Apache Superset using the Olympic dataset to visualize gold medals by age, athletes over 50 by sport, and female medals in summer games.
Build an olympic analytics dashboard in Apache Superset, featuring a bar chart of top five gold medal countries and a table of USA golds by event.
Create and customize bar charts of male and female athletes' participation over time in the Olympics using filters for sex and season, adjust sorting, and add to the analytics dashboard.
Visualize how the age of Olympic athletes varies over time by building bar charts for minimum, maximum, and average ages, filtered by sex and labeled by year.
Build charts showing variation of weight for male and female Olympic athletes over time, computing minimum, maximum, and average weights by year, and save the analytics dashboard with color customization.
Create and customize charts to show height variation for male and female athletes over time, then save and add these charts to the Olympic analytics dashboard for quick insights.
Are you a data engineer, analyst, or business intelligence professional looking for a powerful, open-source alternative to Power BI, Tableau, or Looker? Do you want to learn how to install, configure, and build interactive dashboards with Apache Superset, one of the most popular open-source BI platforms in the world?
This hands-on course will take you from the fundamentals of business intelligence to building advanced dashboards and visualizations using Apache Superset. With step-by-step installations, real-world projects, and practical exercises, you’ll learn everything you need to effectively use Superset in your data engineering and analytics workflows.
Apache Superset is a modern data exploration and visualization platform. Apache Superset is a modern, enterprise-ready business intelligence web application. It is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple pie charts to highly detailed geospatial charts.
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Superset! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Apache Superset!
The primary objective of this course is to equip learners with the knowledge and hands-on skills required to effectively use Apache Superset for data exploration, visualization, and dashboard creation in real-world data engineering and analytics environments.
By the end of this course, you will be able to:
Understand the Role of Apache Superset in Modern Data Stacks
Learn how Superset fits into the broader Business Intelligence (BI) and Data Engineering ecosystem.
Compare Superset with other BI tools such as Tableau, Power BI, and Looker, and understand its advantages as an open-source, cost-effective solution.
Install and Configure Apache Superset Across Multiple Platforms
Gain practical experience installing Superset on Linux (Ubuntu 20.04 & 24.04), Windows (Docker Desktop), and Docker Compose environments.
Learn best practices for configuration, environment setup, and dependency management to ensure smooth deployments.
Connect Superset to Various Data Sources
Integrate Superset with MySQL, PostgreSQL, Hive, Drill, and CSV files.
Understand how to manage connections, schemas, and tables to prepare datasets for analysis.
Develop Interactive Visualizations and Dashboards
Explore Superset’s wide range of visualization options (line charts, bar charts, heatmaps, maps, pivot tables, histograms, pie charts, word clouds, etc.).
Build interactive dashboards with filters, drill-downs, and real-time insights.
Learn to apply best practices for effective dashboard design.
Work on Real-World Business Projects
Build an HR Analytics Dashboard to monitor workforce metrics such as employee demographics, performance, and retention.
Develop an Olympic Analytics Dashboard to explore medal tallies, trends, and country-wise performance over time.
Apply data storytelling techniques to turn raw data into actionable insights.
Master Advanced Superset Features & FAQs
Handle large datasets, query performance issues, schema changes, timed refreshes, and dynamic filters.
Learn common troubleshooting techniques and best practices for production environments.
Gain Confidence for Professional Use
Acquire the skills to use Superset in professional projects, data engineering workflows, and enterprise reporting solutions.
Be prepared to deploy Superset in production environments and collaborate with data teams to deliver impactful analytics solutions.
Take your data visualization and analytics skills to the next level with Apache Superset, the open-source powerhouse for interactive dashboards and business intelligence. In today’s data-driven world, organizations rely on quick, insightful, and visually compelling reports to make critical decisions. Superset makes this possible—turning raw data into actionable insights with stunning visualizations that are easy to build and share.
This course is your ultimate guide to mastering Apache Superset, whether you’re a beginner or an experienced data professional. Through a hands-on, project-based approach, you’ll learn to create dynamic dashboards, connect to various data sources, and customize visualizations that deliver impactful stories to stakeholders.
What You'll Gain:
Seamless Visualization Skills: Master the tools to design and deploy professional-grade dashboards that bring data to life.
Time-to-Insight Advantage: Learn to connect Superset with databases and quickly uncover insights that drive business growth.
Hands-On Projects: Work on real-world scenarios to build your confidence in delivering powerful, data-driven solutions.
Who Should Enroll:
This course is perfect for:
Data Analysts & Business Intelligence Professionals looking to enhance their reporting and visualization capabilities.
Data Engineers & Developers who want to simplify data exploration and create impactful dashboards.
Entrepreneurs & Managers aiming to make data-driven decisions and share insights effortlessly across teams.
Don’t miss the opportunity to transform the way you work with data. Enroll now to master Apache Superset and become a trusted expert in data visualization and analytics!