Examples
~~~~~~~~

In this section, we provide comprehensive examples to demonstrate the workflow for processing different types of file
sources using our schema-driven approach. These examples will guide you through the steps required to configure,
execute, and evaluate the data based on specific file formats.

For each file source, we will cover the following key steps:
 1. **Running the Schema Generation Command**: This step involves executing a command to generate a schema based on the specified file format. The schema will define how the data should be processed and evaluated.
 2. **Creating the Schema**: We provide the schema configuration file, detailing the necessary settings and parameters for processing the data.
 3. **Description of the Data We Want to Search**: This section includes a sample dataset in the specified file format that we aim to search and analyze.
 4. **File to Run the Schema Against**: Here, we present another sample dataset against which the schema will be applied to find matches.
 5. **Expected Results**: Finally, we show the expected output after running the schema against the sample data, demonstrating the effectiveness of the schema-driven approach.

By following these examples, you will gain a clear understanding of how to handle different file formats, configure the schema appropriately, and interpret the results of the evaluation. This will enable you to apply similar workflows to your own datasets, ensuring accurate and efficient data processing across various file sources.


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