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Generating Artificial Data in Databricks

Ben Hazan needs some fake data:

While attending the SQLBits 2023, I took part in André Kamman’s session about “Generate test data quick, easy and lots of it with the Databricks Labs Data Generator”.

In this blog, I will share with you my insights about the DataBricks Data Generator library and I’ll give an example.

Synthetic data is a valuable resource for data scientists, engineers, and analysts who need to test, benchmark, or demonstrate their solutions without compromising sensitive or confidential information. However, generating realistic and relevant synthetic data can be challenging and time-consuming.

That’s why Databricks Labs has developed a Python library called dbldatagen that can help you create large-scale synthetic data sets using Spark.

Click through to learn more about the library and see how you can use to to generate arbitrary amounts of artificial data following certain constraints.