2. Topics
● Redash Introduction
○ Build local version by docker and docker-compose
○ Query json file
○ Join data from different sources
● Kaggle Usage: find EDA examples
3.
4. Redash Features
● Sharable queries
● Scheduling queries
● Various data source interface
● Open source with updated docker images
12. Steps
1. Create query from Google Spreadsheets
a. Google service credential setting
b. Dataset: world population
http://www.worldometers.info/world-population/world-population-by-year/
2. Query json for ‘year’ column
a. Data preprocessing
3. Join 2 views
13. Create Query from Google Spreadsheet
https://redash.io/help/data-sources/querying-a-google-spreadsheet
17. Steps
1. Create query from Google Spreadsheets
a. Google service credential setting
b. Dataset: world population
http://www.worldometers.info/world-population/world-population-by-year/
2. Query json for ‘year’ column
a. Data preprocessing
3. Join 2 views
20. Steps
1. Create query from Google Spreadsheets
a. Google service credential setting
b. Dataset: world population
http://www.worldometers.info/world-population/world-population-by-year/
2. Query json for ‘year’ column
a. Data preprocessing
3. Join 2 views
31. Differences with Superset
Data and Visualization
● Redash has more data source interface
● Redash visualization is based on plotly,
while Superset is based on D3.js
● Local Redash can do query in Python
Account
● Superset can integrated with LDAP
● Redash access control are group-based,
while Superset has different role levels
● Redash user can reset password by Email