Apache Superset Quick Start Guide - Shashank Shekhar

Apache Superset Quick Start Guide

Develop interactive visualizations by creating user-friendly dashboards
Buch | Softcover
188 Seiten
2018
Packt Publishing Limited (Verlag)
978-1-78899-224-4 (ISBN)
29,90 inkl. MwSt
Apache Superset is a modern, open source, enterprise-ready Business Intelligence web application. This book will teach you 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.
Integrate open source data analytics and build business intelligence on SQL databases with Apache Superset. The quick, intuitive nature for data visualization in a web application makes it easy for creating interactive dashboards.

Key Features

Work with Apache Superset's rich set of data visualizations
Create interactive dashboards and data storytelling
Easily explore data

Book DescriptionApache 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.

What you will learn

Get to grips with the fundamentals of data exploration using Superset
Set up a working instance of Superset on cloud services like Google Compute Engine
Integrate Superset with SQL databases
Build dashboards with Superset
Calculate statistics in Superset for numerical, categorical, or text data
Understand visualization techniques, filtering, and grouping by aggregation
Manage user roles and permissions in Superset
Work with SQL Lab

Who this book is forThis 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. Working knowledge of Python will be an advantage but not necessary to understand this book.

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.

Table of Contents

Getting Started with Data Exploration
Configuring Superset and Using SQL Lab
User Authentication and Permissions
Visualizing Data in a Column
Comparing Feature Values
Drawing Connections between Entity Columns
Mapping Data That Has Location Information
Building Dashboards

Erscheinungsdatum
Verlagsort Birmingham
Sprache englisch
Maße 75 x 93 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Software Entwicklung User Interfaces (HCI)
ISBN-10 1-78899-224-5 / 1788992245
ISBN-13 978-1-78899-224-4 / 9781788992244
Zustand Neuware
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