Apache Superset - Explore, Visualize ,Analyze - From Scratch

Learn about installing Apache Superset on your local (with Docker), Learn about the complete working of Apache Superset

What you'll learn

The core concepts of Data Engineering i.e. Difference between Data Exploration vs Data Visualization vs Data Analytics. With focus on Data Exploration

What is Apache Superset and how it is different from the paid BI tools like Tableau, Power BI and Looker

Understanding the Apache Superset Architecture in detail, focusing on the end to end flow between the components

Exploring Apache Superset in Detail understanding what is Dashboard, Charts, DataSets,SQLLabs,

Requirements

No programing experience needed. You will learn everything you need to know

Description

This course starts with the basics of Data Analytics world i.e. what is Data Exploration, Data Visualization and Data Analytics , how these 3 are closely related and what is the thin line between them. We explain what is Business Intelligence because Superset is widely used for Business Intelligence. Then it shows how to install the superset with the help of Docker Desktop . We learn Docker Desktop installation steps as well.We load the already available Examples in Superset, by following simple commands.Once we are in Superset this course walks through each and every UI element in detail , explaining the end to end flow as well i.e. how Dashboarding <>Charting<>Dataset<>SQL work in tandemWe Learn the different charts in detail (first learning the categorization of charts)We also learn how to connect to other Databases like Postgres and MySQLWe also upload our own dataset in form of ExcelWe learn what is semantic layer and what are custom metrics and calculated columns. We learn the Role Based Access System in Detail (with the local setup of Superset)We learn how to setup some config settings, especially around how to enable the MapBox API and also how to setup the Max Row Limit.

Overview

Section 1: Introduction

Lecture 1 Introduction to Data Exploration, Data Visualization and Data Analytics

Lecture 2 Data Exploration vs Data Visualization vs Data Analytics

Lecture 3 What is Business Intelligence

Lecture 4 What is Apache Superset and its prominent features

Lecture 5 The history of Apache Superset

Section 2: Apache Superset - Features ,Architecture and the E2E flow of Data in Superset

Lecture 6 Glimpse of Superset

Lecture 7 Apache Superset the Most Valued Features

Lecture 8 Apache Superset Architecture - In Detail

Section 3: Apache Superset Setup

Lecture 9 Setting up Superset on Docker (covers Docker Basic and setup)

Section 4: Walkthrough of the Apache Superset which we have just setup

Lecture 10 UI Layout of the Superset -> Home Section

Lecture 11 UI Layout of the Superset -> The 4 tabs > Dashboards | Charts | Datasets | SQL

Lecture 12 UI Layout of the Superset -> The "+" icon

Lecture 13 UI Layout of the Superset - > The Settings Section

Section 5: In Detail understanding of Dashboards | Charts | Datasets | SQL

Lecture 14 Working with Dashboards

Lecture 15 Working with Charts (1 chart will be made in this lecture, others covered later)

Lecture 16 Working with Datasets

Lecture 17 Working with SQL (SQL Lab, Saved Queries and Queries History)

Lecture 18 How Dashboards, Charts, Datasets and SQL work End to End

Section 6: Making Different Charts

Lecture 19 Understanding the Categories of Charting

Lecture 20 Making Evolution Charts in Superset - Bar Chart (Line Chart already covered)

Lecture 21 Making Correlation Charts in Superset (Heatmap)

Lecture 22 Making Map charts in Superset (deck.gl charts)

Lecture 23 How to make any chart of any category by just watching this video

Section 7: Connecting Apache Superset to Different Databases

Lecture 24 MySQL setup on Docker - Get image, Run Container, Make DB on mysql using CLI

Lecture 25 Connecting Superset to MySQL which we have just setup on Docker

Lecture 26 Connecting to Postgres (includes Postgres setup on Docker)

Lecture 27 Uploading the Dataset through CSV (includes creating the csv file)

Section 8: Making your own Custom Metrics, Calculated Columns and Custom Queries

Lecture 28 Making your own Custom Metrics (The first computed data of Superset Semantic Lay

Lecture 29 Making your own Calculated Columns (The 2nd computed data of the Semantic Layer)

Lecture 30 Notes

Section 9: Advanced Analytics in Superset

Lecture 31 Advanced Analytics > Rolling Mean

Lecture 32 Advanced Analytics > Time Comparison

Lecture 33 Advanced Analytics > Resampling the Data

Lecture 34 Adding the Annotation Layers

Section 10: RBAC - Role Based Access Control in Superset

Lecture 35 Role Based Access Control (RBAC) and how to achieve that in Superset

Lecture 36 Notes and Links for RBAC

Section 11: Working with Configurations

Lecture 37 Configurations - Config.py - Mapbox API and Row Limit Setup

Data Enthusiasts, Freshers, Data Engineers, Data Scientists, Data Analysts, Business Analysts, Software Developers, Project Managers, Test Managers, Scrum Masters,Accountants, Share brokers, Anybody who wants to learn a new subject