Generating Realistic Synthetic Data with Synner

Aneesha Bakharia
1 min readApr 10, 2021


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
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:

I have created a fork of the github repo that includes instructions for running the tool locally using Docker



Aneesha Bakharia

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