When is Partial Reload useful?

Partial Reload is particularly useful when there is a need to add only new data into an already existing dataset without reloading the entire dataset from scratch. This approach significantly enhances efficiency and performance by minimizing the amount of data that needs to be processed during a reload operation.

In scenarios where large datasets are involved, performing a complete reload can be time-consuming and resource-intensive. By utilizing Partial Reload, you can save both time and computational resources since only the new or changed records are appended to the existing data model.

This functionality is especially advantageous in cases where data is being continuously generated or updated, allowing for real-time or near-real-time analytics without the overhead of re-processing static data. As a result, businesses can deliver timely insights while optimizing performance and reducing load times.