Preface

Apache Superset is a modern, open source, enterprise-ready Business Intelligence (BI) web application. Connecting it to a SQL database allows you to create real-time data visualizations and BI dashboards. This book gets you started with making the best use of Superset for your organization.

Who this book is for

This book is for data analysts, BI professionals, and developers who want to learn Apache Superset. If you want to create interactive dashboards from SQL databases, this book is what you need.

What this book covers

Chapter 1, Getting Started with Data Exploration, teaches you how to install Superset, add a database, create a dashboard, and share a dashboard with users. We will train ourselves to be ready to add additional databases and tables, as well as to create new visualizations and dashboards.

Chapter 2, Configuring Superset and Using SQL Lab, shows you how to configure a Superset web server for your runtime environment needs using the superset_config.py file. We will look at the configuration parameters that can make Superset secure and scalable to match optimal trade-offs. We will replace SQLite metadata with a PostgreSQL database and configure a web app to use it as the database.

Chapter 3, User Authentication and Permissions, looks at how to allow new users to register on the Superset web app with their Google accounts. We will explore the security tools available to the administrator, such as activity logs and user statistics.

Chapter 4, Visualizing Data in a Column, helps you understand columnar data through distribution plots, point-wise comparison with a reference columns, and charts.

Chapter 5, Comparing Feature Values, involves two datasets that you will use to compare prices of food commodities. We will make use of five chart types that will help in giving us a better understanding of how we can correlate between the two sets of data.

Chapter 6, Drawing Connections between Entity Columns, looks at visualizing relationships as graphs instead of coordinates on
orthogonal axes. We will learn about the approaches for visualizing and analyzing dataset with entities and a value quantifying some type of relationship.

Chapter 7, Mapping Data That Has Location Information, continues the trend of analyzing geographical regions by working with location data. We will visualize location data as scatter plots on maps and then we will plot arcs and lines on a map.

Chapter 8, Building Dashboards, is where we will make some beautiful dashboards and complete our Superset quick start journey. We will try to organize the charts such that the dashboard is effective at coherently communicating those answers.

To get the most out of this book

This book will make a great choice for collaborative data analysis work within a cross-functional team of data analysts, business professionals, and software engineers.

Many common analytical questions on data can be addressed using the charts, which are easy to use.

A working knowledge of Python will be an advantage but is not necessary to understand this book.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

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The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Superset-Quick-Start-Guide. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/9781788992244_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Our datasets will be public tables from Google BigQuery and .csv files from a variety of web resources, which we will upload to PostgreSQL."

A block of code is set as follows:

export SUPERSET_UPDATE_PERMS=0 
gunicorn -w 3 
 -k gevent 
 --timeout 120 
 -b 0.0.0.0:8088 
 superset:app

Any command-line input or output is written as follows:

sudo apt-get install build-essential libssl-dev libffi-dev python-dev python-pip libsasl2-dev libldap2-dev

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "After launching, on the VM instances screen, we can see that our g1-small GCE instance is up and running!"

Warnings or important notes appear like this.

Tips and tricks appear like this.

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