Generating Realistic Synthetic Data with Synner
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Ever needed to generate synthetic data and felt that tools such as Faker don’t go far enough to match your requirements. Synner may just be what you need.
Synner is a tool developed by Azza Abouzied (@AzzaAbouzied) and Mino Mannino and documented in their UIST 2019 paper. A demo video of the tool in use is also available https://www.youtube.com/watch?v=BH9tiuoayp0
The main features include the ability to:
- Add numeric and categorical columns
- Define the distribution of generated data
- Define relationships between columns (you can even draw a relationship) <← Killer feature!
- Define sub cases within a column with their own distribution
- Export generated data
- Export settings used to generate the data
The tool is open source, available on github and online to start generating your own synthetic data: http://synner.io/
I have created a fork of the github repo that includes instructions for running the tool locally using Docker https://github.com/aneesha/synner