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You're reading from  Apache Superset Quick Start Guide

Product typeBook
Published inDec 2018
Reading LevelIntermediate
Publisher
ISBN-139781788992244
Edition1st Edition
Languages
Python
Tools
Apache Superset
Concepts
Business Intelligence
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Author (1)
Shashank Shekhar
Shashank Shekhar
author image
Shashank Shekhar

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.
Read more about Shashank Shekhar

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Security features

Access to security features in Superset is available only to the admin user. It provides several tools for tracking every user action, login attempt, a list of users, and their permissions.

The user management system is built using the Flask-AppBuilder (fabmanager) framework. The list of permissions and views is inherited from the Flask-AppBuilder framework. Permissions and views are listed in the Views/Menus page of the Security section. A view represents many ways a user can interact with the web application. Each user has a specific set of permissions for actions that it can take when interacting with a web page or view. Viewing or deleting a dashboard are examples of actions.

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Apache Superset Quick Start Guide
Published in: Dec 2018Publisher: ISBN-13: 9781788992244
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Shashank Shekhar

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.
Read more about Shashank Shekhar

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