👉 Pre-computing, also known as offline or batch processing, refers to the method of performing computations on large datasets beforehand, typically during a non-real-time operation. In this approach, data is collected and processed in advance, often during scheduled maintenance or when resources are not constrained by immediate demand. This allows for the creation of optimized models, large-scale simulations, or complex calculations that can be executed quickly and efficiently once the data is ready. Pre-computing is particularly useful in scenarios where real-time processing is not critical, such as training deep learning models, running large-scale data analytics, or generating reports. By offloading these intensive tasks to a pre-processing phase, systems can operate more smoothly and effectively, reducing latency and improving overall performance.
