A strategy guide to CAT Data Interpretation sets - tables, graphs, and caselets - and how to decide which sets to attempt first under time pressure.
Data Interpretation sets are usually presented as a group of four to six linked questions built around one shared dataset, as noted in CAT Syllabus. This structure means the decision of which sets to attempt is often as important to your score as your accuracy within any single set.
The common DI formats CAT uses, why set selection matters more here than in most other LRDI question types, and a practical approach to reading a new dataset efficiently.
Because DI questions are grouped into sets built around one dataset, getting the initial data setup right unlocks four to six questions at once — but a set built around a confusing or unusually dense dataset can consume disproportionate time for the same four to six marks. Spending 90 seconds scanning a set before committing to attempt it, specifically to judge how quickly the data can be organized, is time well spent rather than time wasted.
Committing to the first DI set encountered simply because it appears first, rather than scanning all available sets briefly and starting with the one that looks most tractable. Sets are not presented in order of difficulty, so there is no advantage to attempting them strictly in sequence.
Continue to CAT LRDI: Puzzles, or revisit CAT LRDI: Arrangements since both topics reward similar notation-first habits.
Part of: CAT Skill Building