An ecommerce company receives multiple gigabytes of customer data daily. The company uses the data to train an ML model to forecast future product demand. The company needs a solution to perform…

The correct answer is A. Batch inference. Batch inference is designed for high‑volume, scheduled predictions: you can point it at the day’s gigabytes of data, run a job once daily, and generate all forecasts in one go without needing a persistent endpoint.

Submitted by salim_om· Mar 30, 2026Implementing AI Solutions

Question

An ecommerce company receives multiple gigabytes of customer data daily. The company uses the data to train an ML model to forecast future product demand. The company needs a solution to perform inferences once each day. Which inference type meets these requirements?

Options

ABatch inference
BAsynchronous inference
CReal-time inference
DServerless inference

How the community answered

(19 responses)

A
74% (14)
B
11% (2)
D
16% (3)

Explanation

Batch inference is designed for high‑volume, scheduled predictions: you can point it at the day’s gigabytes of data, run a job once daily, and generate all forecasts in one go without needing a persistent endpoint.

Topics

#batch inference#inference types#demand forecasting#ML deployment

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