For which scenario would using a flat file for data import be least effective?

Using a flat file for data import is least effective for very large datasets due to the limitations inherent in flat file handling. When dealing with large volumes of data, several challenges arise. For instance, flat files may not offer efficient data processing and retrieval speeds, leading to long loading times and potential timeouts during import. Additionally, managing data integrity and consistency can become difficult, as flat files do not have built-in mechanisms for handling data relationships or enforcing schema constraints.

In contrast, flat files can be quite effective for small datasets where the overhead of establishing more complex data import methods may not be justified. They are also suitable for structured data because they can represent a clear organization of information in formats like CSV or JSON. Furthermore, flat files excel when the data is already in a compatible format, as with CSV, making it easy to parse and import. However, as the dataset grows in size, the drawbacks become more pronounced, making alternative data import strategies more viable for handling such scenarios.