Beginner · Systems

Offline Processing

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. Computing predictions or transforming data in batches, without strict latency requirements.

Technical Definition

Computing predictions or transforming data in batches, without strict latency requirements.

How it works

Used for nightly scoring, large analytic jobs, model retraining, and dataset preparation. Trades latency for throughput and cost efficiency. Many production ML systems combine real-time and offline pipelines.

Related Concepts

• Data Pipeline — An automated workflow that ingests, transforms, and delivers data to models.
• Batching — Grouping multiple inference requests so they run together on the GPU.
• Real-time Processing — Handling data and producing results within strict latency bounds, often milliseconds.