Which of the following best explains the term ‘derived dataset’?

The term 'derived dataset' refers to a dataset that is created by transforming and combining existing data sources. This process often involves applying various calculations, filters, or aggregations to raw data to produce outcomes that serve specific analytical or reporting needs. Derived datasets are particularly valuable because they allow users to create more meaningful insights from the raw data by tailoring it to their particular purposes.

In contrast, other options reflect different concepts. A dataset created from scratch without transformations would not be classified as derived since it lacks the elements of transformation and combination that define a derived dataset. Default settings alone indicate a lack of customization or transformation, making it unsuitable for defining a derived dataset. Holding raw input data only focuses solely on the original data, which does not incorporate any of the enhancements or alterations that characterize a derived dataset. Thus, option B is the most accurate representation of what a derived dataset is within the context of data analysis and reporting.