Anonymize 3 datasets using deep generative modelling with an SDK

Job ID: 31024176

Budget: $10 – $30 USD

Synthesized has recently launched the SDK version of its DataOps platform.

The SDK enables any data practitioner to anonymise and reshape structured data as needed. In particular for remote developers it allows more work to be done, faster, when data is too sensitive to share, maintaining trust with stakeholders.

We've created a Google Colab environment for you to try out our SDK in.

Your task is to run the SDK on 3 distinct datasets. The datasets are up to you to choose. The SDK supports any cvs, xls files.

1. With Dataset 1, you need to use the SDK to anonymize it.
2. With Dataset 2, you need to use the SDK to impute missing values in it.
3. With Dataset 3, you need to use the SDK to double the size of data using generative modelling.

We ask you to
- Record your screen and yourself (on video) during the trial session with any commentary and feedback that you may have on the SDK.
- Please use the following software to record the session.
- QuickTime Player
- Zoom
- Complete written product feedback survey form

You are given access to:
- Synthesized SDK Colab Environment
- SDK documentation
- Product survey form

What you’ll need:
- 3 datasets
- a webcam and microphone along with stable internet connection

The entire task should take ~1 hour to complete with the video recording expected to take ~30 minutes.

Instructions:
1. You’re given access to a Google Colab environment which will contain commentary and a link to the SDK guide
2. When you start using the environment, Imagine as if you were really working on a project as you would be in the course of your normal activities—we want to hear your thoughts out loud
3. There are no right or wrong answers. You are helping us :)
4. Please go through the entire flow with your dataset and then repeat the same steps for your other two datasets
5. Please fill out your written survey feedback no more than 24 hours after completing the exercise