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Big Data Glossary

What is Batch Processing?

Definition of Batch Processing

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What is Batch Processing?

Batch processing refers to the processing of a large set of data or tasks in a non-interactive mode, typically in a scheduled time frame. It is a way of processing large volumes of data, where a large number of transactions or data records are collected over a period of time, and then processed together in a single batch, rather than processing each transaction or data record individually in real-time.

In batch processing, data is collected and stored, usually in a data file or database, and then processed in a specific time frame, such as overnight or at regular intervals. The data is processed in a sequence of steps, and it can include tasks such as data validation, data transformation, and data loading.

Batch processing is commonly used in situations where real-time processing is not required, and it can be useful in various fields such as finance, retail, and manufacturing. For example, in a retail business, the sales data collected during the day can be processed and analyzed in a batch process overnight to determine the sales trends and inventory needs. Batch processing can be efficient for large data sets and can handle high-volume and complex data. However, it has a drawback in the sense that it may have a delay in the availability of the processed data and it can be less responsive to the real-time needs.

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