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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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SQL Lab

SQL Lab is a powerful SQL IDE inside Superset. It works with any database that has a SQLAlchemy Python connector. It is great for data exploration. It can query any data sources in the Superset, including the metadata database.

It is a solid playground from which we can slice and dice the dataset in many ways to arrive at a form that needs to be visualized to solve the analytical question that the chart was created to answer.

First, we need to enable SQL Lab use on the superset-bigquery data source. We will explore and visualize the data in the table using SQL queries.

After clicking on the Sources | Databases option on the navigation bar, select the Edit record option for the superset-bigquery data source:

The overview chart of the list of databases

Then, make sure the following three options are enabled. Allow Run Sync should be enabled by default. We are doing this...

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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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