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https://current.confluent.io/2024-sessions/a-survey-of-fake-data-generation-tools-for-data-streaming-applications-stop-writing-your-own

Current Sessions | A Survey of Fake Data Generation Tools for Data Streaming Applications: Stop Writing Your Own

Dummy data is commonly used for testing applications. For small, functional tests, developers can quickly and easily mock up something close to what they expect. When it comes to data streaming applications, however, generating realistic streams of data that test all the functionality in an application means choosing from one of a crop of data stream generating tools, each with their own nuances, strengths, and limitations. So how does one choose?



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Current Sessions | A Survey of Fake Data Generation Tools for Data Streaming Applications: Stop Writing Your Own

https://current.confluent.io/2024-sessions/a-survey-of-fake-data-generation-tools-for-data-streaming-applications-stop-writing-your-own

Dummy data is commonly used for testing applications. For small, functional tests, developers can quickly and easily mock up something close to what they expect. When it comes to data streaming applications, however, generating realistic streams of data that test all the functionality in an application means choosing from one of a crop of data stream generating tools, each with their own nuances, strengths, and limitations. So how does one choose?



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https://current.confluent.io/2024-sessions/a-survey-of-fake-data-generation-tools-for-data-streaming-applications-stop-writing-your-own

Current Sessions | A Survey of Fake Data Generation Tools for Data Streaming Applications: Stop Writing Your Own

Dummy data is commonly used for testing applications. For small, functional tests, developers can quickly and easily mock up something close to what they expect. When it comes to data streaming applications, however, generating realistic streams of data that test all the functionality in an application means choosing from one of a crop of data stream generating tools, each with their own nuances, strengths, and limitations. So how does one choose?

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      Dummy data is commonly used for testing applications. For small, functional tests, developers can quickly and easily mock up something close to what they expect. When it comes to data streaming applications, however, generating realistic streams of data that test all the functionality in an application means choosing from one of a crop of data stream generating tools, each with their own nuances, strengths, and limitations. So how does one choose?
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      Current Sessions | A Survey of Fake Data Generation Tools for Data Streaming Applications: Stop Writing Your Own
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      Dummy data is commonly used for testing applications. For small, functional tests, developers can quickly and easily mock up something close to what they expect. When it comes to data streaming applications, however, generating realistic streams of data that test all the functionality in an application means choosing from one of a crop of data stream generating tools, each with their own nuances, strengths, and limitations. So how does one choose?

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      Current Sessions | A Survey of Fake Data Generation Tools for Data Streaming Applications: Stop Writing Your Own
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      Dummy data is commonly used for testing applications. For small, functional tests, developers can quickly and easily mock up something close to what they expect. When it comes to data streaming applications, however, generating realistic streams of data that test all the functionality in an application means choosing from one of a crop of data stream generating tools, each with their own nuances, strengths, and limitations. So how does one choose?
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