Meridian's cargo-and-demand forecasting initiative ingests booking transactions, real-time weather feeds, and continuous engine-sensor telemetry from the in-service fleet, all arriving at different speeds and in different formats. Which Big Data characteristic is the PM primarily managing when comparing the batch-loaded booking data against the continuously streaming sensor telemetry?

Big Data is conventionally described by characteristics such as volume (amount), velocity (speed of arrival/processing), variety (range of formats and sources), and veracity (trustworthiness). The scenario contrasts batch-loaded booking transactions with continuously streaming sensor telemetry — that is a difference in how fast data arrives and must be processed, which is velocity. Variety (option D) is a plausible distractor because the scenario does mention multiple data sources and formats, but the specific comparison drawn in the question — batch versus continuous/real-time — isolates velocity, not the range of formats. Volume (option B) concerns quantity, not speed, and nothing in the stem quantifies size. Veracity (option A) concerns trustworthiness/accuracy of the data, which isn't addressed here. A PM designing a data architecture must recognize which Big Data characteristic is driving an infrastructure decision — high-velocity sensor streams typically demand a different pipeline pattern than batch-loaded transactional data, a distinction covered further under Task 3 (data pipelines).