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Using Fakestream to generate synthetic data for your Segment event pipeline

What is Fakestream?

The "Fakestream" package, developed by Human37 and shared on GitHub, is a tool designed for generating synthetic data for event pipelines. Synthetic data refers to artificially generated data that mimics the statistical properties and patterns of real-world data, without containing any personally identifiable information (PII) or sensitive details. This type of data is especially useful for training, demonstrating, or testing purposes where using actual customer data is not considered a best practice due to privacy concerns.

How does it work?

The Fakestream package leverages the Faker.js framework and integrates it into an event pipeline, specifically designed for use with Segment. It is preconfigured with a variety of events but can be customised to fit specific needs. This flexibility and customization potential make Fakestream a versatile tool for organisations looking to simulate realistic data scenarios while ensuring privacy and compliance with data protection regulations.

Why did we build Fakestream?

Fakestream allows teams to test, tain and conduct solution demos using non-production demo, but close variations. This package represents Human37's commitment to advancing data privacy and security in the analytics community, as evidenced by their open-source contributions and overall focus on customer data strategy and privacy-centered technological solutions.

If you are intersted in our Fakestream package, feel free to reach out!


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