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GMAT Data Insights: The Section That Defines Focus Edition

The new third of the GMAT — five question types that test whether you can read data and reason across sources, calculator allowed.

The big picture

Why Data Insights matters

Data Insights is equally weighted with Quant and Verbal, so it's a full third of your score — no longer an afterthought. It tests reading, interpreting and combining data from tables, charts and text to make decisions, and an on-screen calculator is available here (unlike Quant).

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Real example: Business schools care about this section because it mirrors real analytics work — turning messy data into a decision. Neglecting it now costs a third of your total score.
🧠 Memory hook: DI = a full third of the score, with a calculator. Never treat it as optional.

Data Sufficiency — enough, not the answer

Data Sufficiency gives a question plus two statements; you decide whether each alone, both together, or neither is enough to answer — you usually don't compute the final answer. The five choices never change, so learn them cold.

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Real example: 'Is x > 5?' Statement 1: x > 3 (not enough). Statement 2: x = 7 (enough alone). You answer 'statement 2 alone is sufficient' — without needing anything beyond that judgement.
🧠 Memory hook: DS asks 'is it ENOUGH?', not 'what's the answer?'. Judge sufficiency, don't solve.

Multi-Source & Table — organise before you answer

Multi-Source Reasoning spreads information across tabs (text, tables, charts) you must combine. Table Analysis lets you sort a table to judge true/false statements. Both reward a calm, find-the-relevant-data-first approach over rushing.

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Real example: In Table Analysis, sorting the column the statement is about (e.g. by revenue) often makes 'the top 3 all exceed X' instantly checkable — use the sort, don't eyeball.
🧠 Memory hook: Sort and locate first. In DI, finding the right data is half the answer.

Graphics & Two-Part — read the format carefully

Graphics Interpretation gives a chart and dropdown sentences to complete from it. Two-Part Analysis asks for two answers (one per column) that together satisfy a condition. Both punish careless reading of the chart or the prompt's exact requirement.

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Real example: In Two-Part Analysis, the two columns might be 'maximises revenue' and 'minimises cost' — a choice can be right for one column and wrong for the other, so read each column's requirement separately.
🧠 Memory hook: Read the chart axes / each column's requirement exactly. DI traps are misreads.

Frequently asked questions

How is the Data Insights section weighted, and is a calculator allowed?
It's equally weighted with Quant and Verbal (a full third of the score), and an on-screen calculator is available in Data Insights.
What does a Data Sufficiency question actually ask?
Whether the given statements are sufficient to answer — not what the final answer is.
What are the five Data Insights question types?
Data Sufficiency, Multi-Source Reasoning, Table Analysis, Graphics Interpretation and Two-Part Analysis.
What's the best approach to Table Analysis?
Sort the relevant column first, then judge the true/false statements — don't eyeball the data.
What must you watch for in Two-Part Analysis?
Each of the two columns has its own requirement, so an option can be right for one and wrong for the other.

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