Description: Offline processing refers to the manipulation and analysis of data that is not performed in real-time, allowing organizations to manage large volumes of information without the pressure of immediacy. This approach is fundamental in situations where latency is not critical, enabling systems to accumulate data and process it in batches. It is often used in conjunction with various technologies that facilitate distributed processing of large datasets and in applications where complex analyses can be performed without the need for constant cloud connectivity. Key characteristics of offline processing include the ability to conduct deeper and more thorough analyses, optimize the use of computational resources, and allow for the integration of data from various sources. This type of processing is especially relevant in the current context, where the amount of data generated is overwhelming, and organizations seek efficient ways to extract value from this information without compromising the performance of their real-time systems.
