Book Image

Apache Superset Quick Start Guide

By : Shashank Shekhar
Book Image

Apache Superset Quick Start Guide

By: Shashank Shekhar

Overview of this book

Apache Superset is a modern, open source, enterprise-ready business intelligence (BI) web application. With the help of this book, you will see how Superset integrates with popular databases like Postgres, Google BigQuery, Snowflake, and MySQL. You will learn to create real time data visualizations and dashboards on modern web browsers for your organization using Superset. First, we look at the fundamentals of Superset, and then get it up and running. You'll go through the requisite installation, configuration, and deployment. Then, we will discuss different columnar data types, analytics, and the visualizations available. You'll also see the security tools available to the administrator to keep your data safe. You will learn how to visualize relationships as graphs instead of coordinates on plain orthogonal axes. This will help you when you upload your own entity relationship dataset and analyze the dataset in new, different ways. You will also see how to analyze geographical regions by working with location data. Finally, we cover a set of tutorials on dashboard designs frequently used by analysts, business intelligence professionals, and developers.
Table of Contents (10 chapters)

Summary

We made a lot of charts in this chapter! Those were just some approaches to visualizing and analyzing a dataset with entities and a value quantifying a type of relationship. The Superset chart, called a partition diagram, is similar to a TreeMap, but it only generates a single level of partitioning. So, I chose to use a TreeMap instead of that, because it provided a more efficient and powerful way to visualize data.

Hopefully, you are now comfortable with using these chart examples for inspiration to upload your own entity-relationship dataset and analyze it in new and different ways.

In the next chapter, we will continue the trend of analyzing geographical regions by working with location data.