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

That's a wrap! We figured out how to allow new users to register on the Superset web app with their Google account. The OAuth configuration can be extended to provide users with Facebook, Twitter, or GitHub accounts to also register and sign in easily. We explored many security tools available to the administrator, such as activity logs and User Statistics. Our current setup will support user management for collaborators who will need Alpha roles and SQL Lab access, so that they can add or alter data sources, make new charts, and dashboards, or work in SQL Lab. Using the gamma role and data source access permissions, supports use cases for users who will only need to interpret charts and dashboards on specific data sources. For example, people in the finance team may only need the ability to view charts on finance-related data sources, while data analysts may need...