Which statement correctly distinguishes exploratory from predictive analytics?
Select an answer to reveal the explanation.
Short Explanation
The difference is purpose. You use exploration to characterize existing data and shape questions, while prediction fits models on history to estimate outcomes for unseen cases. Only prediction owes you an accuracy number.
Full Explanation
The correct statement is the one that defines exploratory work as characterizing existing data to find patterns and shape questions, and predictive work as fitting models on historical examples to estimate outcomes for unseen cases. The distinction is the question each answers. Exploration profiles and compares existing data to surface patterns and refine the question. Prediction fits a model on historical examples so it can estimate an outcome for cases outside that set, and it is evaluated on how well it does so. The option saying exploratory work runs on smaller data volumes and predictive work is defined by operating at scale is incorrect because volume is orthogonal. Exploration frequently runs over the full corpus, and models are often trained on modest samples. The option saying exploratory work is performed by analysts and predictive work by engineers is incorrect because job titles do not define analytic categories. The same person routinely does both, often in the same session. The option saying exploratory work is interactive and predictive work is always batch is incorrect because execution mode is an implementation detail. Exploration can be scheduled and models are often scored interactively at request time. For the exam, define both by purpose—discovery versus estimation—and reject options that define them by scale, tooling, or role.