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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
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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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Dashboards

A dashboard layout presents a set of charts in a way that viewers can scan them and get key insight. Layouts make use of different components such as a heading, divider, and data filters.

We'll work with all of the dashboard components available in the Superset v0.28 release. By breaking down examples, we'll create the dashboards for Chapter 1, Getting Started with Data Exploration; Chapter 5, Comparing Feature Values; and Chapter 7, Mapping Data That Has Location Information. Our familiarity with the charts and the dataset will be critical in helping us to make the right decisions about the layout.

Hopefully, in this section, we'll improve our intuition for building dashboard layouts that are effective in reporting insights for any set of charts.

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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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