Generating Realistic Synthetic Data with Synner

Aneesha Bakharia
1 min readApr 10, 2021
http://synner.io/

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

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Aneesha Bakharia

Data Science, Topic Modelling, Deep Learning, Algorithm Usability and Interpretation, Learning Analytics, Electronics — Brisbane, Australia