Mockingbird solves a major issue for teams looking for test data sets that can mimic the breadth and depth of real-life sensitive data. Open Raven built Mockingbird for this very purpose, and uses it for testing and benchmarking the data classification engine. Improve testing and benchmarking without creating more risk for your organization or customers.
Quickly generate and populate files with synthetic sensitive data such as social security numbers or credit card numbers. Create data sets in various file formats such as office documents, Apache parquet and log files. Relevant metadata such as the amount and type of data that was placed into each document is tracked to allow for independent grading and evaluation.Learn more
Set tunable parameters to generate files of various size and composition to cover a wide range of data generation and benchmarking scenarios. For instance Mockingbird can generate files of arbitrarily large (or small) sizes to test speed and performance of data classification tools across a range of file sizes or test speed and accuracy when encountering files with a wide range of the type of sensitive data and the composition of those types.Learn more
Mockingbird has direct integration with Mockaroo to convert a user’s custom Mockaroo API into Mockingbird documents. Mockaroo provides “mock-data-as-a-service”, and has an extensive library of randomly generated mock data, which provides a convenient entry point for Mockingbird to use as seed data.Learn more