• Written by Azhar Aliyar, Director

When a shift supervisor checks the maintenance log, they expect the system to return accurate results, but sometimes the query returns inconsistent or incorrect data, this is often due to a failure in the golden dataset, which is a fixed set of questions that the system is regression tested against to ensure its accuracy. A golden dataset is a set of pre-defined questions that are used to test the system's ability to return correct results. The purchase order table, for example, is a critical component of the system, and the golden dataset will include questions that test the system's ability to retrieve and manipulate data from this table.

Definition

A golden dataset is a collection of questions that are used to test the system's functionality and accuracy, it is not a dynamic set of questions, but rather a fixed set that is used to ensure that the system is working as expected. The golden dataset is typically created during the development phase of the system, and it is used to test the system's ability to retrieve and manipulate data from various tables, such as the customer database or the inventory management system.

The golden dataset is an essential component of the system, as it allows developers to test the system's functionality and accuracy in a controlled environment, before deploying it to a live environment.

Differences

Many people confuse the golden dataset with the training data, but they are not the same thing, the training data is used to train the system's algorithms, whereas the golden dataset is used to test the system's functionality and accuracy. The training data is typically a large dataset that is used to teach the system to recognize patterns and make predictions, whereas the golden dataset is a smaller, more focused set of questions that are used to test the system's ability to return correct results.

The golden dataset is also different from the test data, which is used to test the system's performance and scalability, the golden dataset is used to test the system's functionality and accuracy, whereas the test data is used to test the system's ability to handle large volumes of data and user traffic.

Applications

In a large organisation, the golden dataset is typically used to test the system's ability to retrieve and manipulate data from various tables, such as the customer database or the inventory management system. For example, a category manager may use the system to compare two suppliers, and the golden dataset will include questions that test the system's ability to retrieve and manipulate data from the supplier database.

The golden dataset is also used to test the system's ability to handle complex queries, such as queries that involve multiple tables or queries that require the system to perform calculations or aggregations. The golden dataset is an essential component of the system, as it allows developers to test the system's functionality and accuracy in a controlled environment, before deploying it to a live environment.

Limitations

Most people think that the golden dataset is a magic bullet that can solve all the system's problems, but this is not the case, the golden dataset is only as good as the questions that are included in it, and if the questions are not comprehensive or accurate, the golden dataset will not be effective.

For example, if the golden dataset does not include questions that test the system's ability to handle edge cases or unexpected input, the system may not be able to handle these cases correctly, and this can lead to errors or inconsistencies in the results. To get the most out of the golden dataset, it is essential to continuously monitor and update the questions to ensure that they are comprehensive and accurate.

When it is the wrong choice

The golden dataset is not always the right choice, for example, if the system is being used to answer complex or open-ended questions, the golden dataset may not be effective, as it is typically used to test the system's ability to return correct results to pre-defined questions.

In these cases, it may be more effective to use a different approach, such as using a human evaluator to assess the system's performance, or using a different type of testing, such as usability testing or user acceptance testing. The golden dataset is an essential component of the system, but it is not a one-size-fits-all solution, and it is essential to carefully consider the system's requirements and limitations before deciding whether to use a golden dataset.