Batchwise

Batchwise refers to the practice or manner of handling items in groups, or batches, rather than one at a time. The term combines batch, meaning a set collected for processing, with the adverbial suffix -wise indicating manner or regard. It is used across disciplines to describe operations, processing strategies, or analyses that apply to whole batches rather than individual units.

In computing, batchwise processing means applying operations to a collection of data points in a single step. This contrasts with samplewise or per-item processing. In machine learning, batchwise approaches are common in training where updates to model parameters are made after processing a mini-batch of examples, rather than after every single example. Batchwise normalization or statistics use aggregated information from an entire batch to perform computations, which can improve efficiency but may introduce dependence on batch composition.

In manufacturing, batchwise production produces goods in discrete groups. Batchwise processes are typical in pharmaceuticals, food and beverage, and specialty manufacturing where products pass through the same sequence of steps before moving to the next batch. This approach offers flexibility and easier quality control but can incur higher setup costs and longer lead times compared to continuous production.

In data processing and analytics, batchwise workflows process large volumes of data at scheduled intervals, suitable for systems with variable data inflow or where real-time processing is not required. Batchwise analysis may aggregate results across multiple batches to identify trends or quality metrics.

See also batch processing, batch size, batch normalization, and batch scheduling.