GMAT® Data Insights: A Complete Guide

If you are looking at the GMAT® for the first time, the Data Insights section might sound like something brand new that you need to figure out from scratch.

That is a reasonable reaction. "Data Insights" is a newer name on the GMAT® Focus Edition, and most prep resources still label their materials as "Integrated Reasoning" or "Data Sufficiency" — not "Data Insights."

So it is natural to wonder: what is this section? What does it test? Do you need special materials for it?

Here is the good news. Data Insights is not a new thing you have to learn. It is a combination of two problem types that have been on the GMAT® for a long time: integrated reasoning and data sufficiency. They just live in the same section now.

If you have studied for the old version of the GMAT®, you already know most of what you need. If you are starting from scratch, the content here overlaps heavily with quant and verbal. There is no new math. There is no new reading skill. The main adjustment is getting comfortable with the question formats.

This guide covers the format, the question types, the strategies, and how to study for the Data Insights section.

What Is the Data Insights Section?

Data Insights is one of the three sections on the GMAT® Focus Edition (the current version of the exam), alongside Quantitative Reasoning and Verbal Reasoning.

Here are the basics:

The section is adaptive, which means the difficulty adjusts based on your performance as you go. This is a change from the old GMAT®, where integrated reasoning was a separate, non-adaptive section. Now all three sections work the same way.

There is a calculator available. You can show it and hide it with a button on the screen. More on that later.

The Two Question Types

Data Insights has two categories of questions:

1. Integrated reasoning (about 12–15 questions)
2. Data sufficiency (about 5–8 questions)

The exact mix varies from test to test. But integrated reasoning tends to be about twice as important as data sufficiency by volume.

Here is the key thing to understand: there is no new content in this section. Integrated reasoning combines quant and verbal concepts. Data sufficiency is a logic question format that uses math content. Both have been around for a long time. They are just grouped together now.

That is why most prep providers recommend building your quant and verbal skills first. Improving those sections will naturally lift your Data Insights score. You can focus on DI-specific strategy and timing once your foundational skills are solid.

If you want a full breakdown of what the GMAT® tests across all three sections, see our complete topic list.

Integrated Reasoning: The Four Question Types

Integrated reasoning questions test your ability to work with data in real-world formats — graphs, tables, multi-tab scenarios. The content comes from quant and verbal. The format is what takes getting used to.

There are four question types. Let us walk through each one.

Type 1: Two-Part Analysis

These are problems where you solve for two variables. Hence the name. The content could be algebra, statistics, or even something closer to a critical reasoning question.

The main strategy here is about reading carefully. Two-part analysis questions hide the key constraint in plain sight. The test is betting you will skim past it. When people miss these questions, it is almost never a math problem. It is a reading problem.

Here is a system:

Write down what the question is asking you. Get crystal clear on that first.

Then go back and pull the key information from the prompt that relates to answering that question.

Integrated reasoning questions give you a lot of information. A lot of it does not matter. The core skill is sifting through everything to find the data you need. Writing down the question first helps you do that.

One thing to be ready for: you may need to guess and test with the answer choices. Two-part analysis questions sometimes give you two variables without a single equation to solve. That can feel uncomfortable if you are used to solving for one clean answer. Practice plugging in answer choices and testing them.

See an official example →

Type 2: Graphics Interpretation

These questions show you a graph and ask you to fill in blanks using dropdown menus.

The strategy here: read the title and the axes of the graph before you read the question.

Pay attention to units. The x-axis might say 1, 2, 3, 4, 5 — but there might be a note that says "in hundreds of millions." Under pressure, it is easy to pick 6 million instead of 600 million. That is an easy way to lose points on a question you know how to answer.

You might see some unfamiliar graph types — bubble charts, scatter plots, things that look strange. Try not to let that throw you off. If you stare at a graph and cannot figure out what is going on, pick an answer and move on. You can come back to it later.

See an official example →

Type 3: Table Analysis

These questions give you a spreadsheet-like table. You can sort the data by column, but you cannot manipulate it beyond that.

The strategy is straightforward: sort the data based on what the question is asking.

If the question asks about revenue per customer, sort by revenue. If it asks about profit per customer, sort by profit. If it asks about price points, sort by price points.

It sounds almost too basic. But this one habit unlocks table analysis for most people — even those who struggle with it. Be robotic about it. Sort first, then answer.

See an official example →

Type 4: Multi-Source Reasoning

These questions look like reading comprehension with numbers. You get two or three tabs of information — like a web browser with tabs open. You can only view one tab at a time. You will cycle through two or three questions based on the same data set.

For a lot of business professionals, this format feels familiar. It is like having an email in one tab, a spreadsheet in another, and writing a report based on both.

The strategy: treat it exactly like reading comprehension. Do a quick scan of all the tabs. Make light notes if that helps. Then answer based on the evidence — not your opinion.

Even if the question uses words like "infer" or "suggest," they are not asking for your take. They are asking which answer is provable based on the data given. Focus on what the evidence can prove.

See an official example →

Key IR Strategy Notes

A few things apply across all four IR question types.

No partial credit

Most IR questions have multiple parts. A two-part analysis has two answers. A graphics question has two dropdowns. A multi-source reasoning question might have three yes/no statements.

If you get one part right and another part wrong, the whole question is wrong. There is no partial credit.

That sounds stressful. But it works in your favor as a strategy tool. If you are unsure on a multi-part question, that is a good candidate to skip and come back to. Your odds of guessing correctly on a three-part question are lower than on a single-part question.

Time pressure

Most timing issues in Data Insights come from integrated reasoning. Even though there are 20 questions in 45 minutes, the multi-part structure makes it feel like more. A section with 12 IR questions might feel like 30 questions because each one has multiple parts.

Unlike most GMAT® question types where we recommend fewer problems with deeper review, integrated reasoning responds well to volume practice. Doing a lot of IR problems can help with both timing and comfort with the formats. Just make sure you are still learning from each question — do not grind mindlessly.

Old materials still work

If you are worried about a lack of Data Insights-specific resources, do not be. All integrated reasoning materials from GMAT® Classic are relevant. The question types have not changed. Old IR practice questions, old IR sections from past exams, community-created IR problems on GMAT Club — all of it works.

For data sufficiency, the same applies. The format is the same as it has always been. The only change is that about half the DS questions in Data Insights are pure logic questions with little or no computation. But the process for solving them is the same.

Data Sufficiency: The Deep Dive

Data sufficiency is unique to the GMAT® and related exams like the Executive Assessment. If you have never seen one before, the format can feel strange. That is normal.

On a regular math problem, you solve for an answer. X equals seven. You pick B. You move on.

Data sufficiency is different. You are not solving for the answer. You are asking: do you have enough data to answer the question?

That is a subtle but important difference. Let us break it down.

The Format

Every data sufficiency question has the same structure:

A question at the top of the screen.

Two statements below the question. The exam calls them Statement 1 and Statement 2. Think of them as facts — they are always telling you the truth.

Your job is to figure out whether the information in those statements is enough to answer the question definitively.

The five answer choices never change:

(A) Statement 1 alone is sufficient, but Statement 2 alone is not.

(B) Statement 2 alone is sufficient, but Statement 1 alone is not.

(C) Both statements together are sufficient, but neither alone is sufficient.

(D) Each statement alone is sufficient.

(E) Even with both statements together, there is still not enough data.

See an official example →

Memorize these as soon as possible. They are the same on every single data sufficiency question.

Value Questions vs. Yes/No Questions

There are two types of data sufficiency questions, and mixing them up is one of the most common mistakes students make.

Value questions ask for a specific number. "What is the value of X?" Sufficient data means you get one answer. If X could be 6 sometimes and 7 other times, that is not sufficient. It needs to always be the same value.

Yes/no questions ask a yes or no question. "Is X equal to 5?" You need a definitive answer — either always yes or always no.

Here is where it gets tricky. If the question is "Is X equal to 5?" and Statement 1 says "X is equal to 7" — that is sufficient. Because you know for sure the answer is no. It is never 5. A definitive "no" is just as sufficient as a definitive "yes."

But if Statement 1 says "X is greater than 4" — that is not sufficient. X could be 5. X could be 6. Sometimes yes, sometimes no. Not definitive.

If you find yourself getting confused, write "VALUE" or "YES/NO" at the top of your scratch pad for each DS question. It sounds basic. But it prevents one of the most common errors on this question type.

The Six-Step Process

Data sufficiency rewards a consistent process more than any other question type on the GMAT®. Here is the system we teach.

Step 1: Write what is given and what is asked.

Physically write it down on your scratch pad. Every time. If there is a constraint like "X is a positive integer," write it down. If there is no constraint on X, note that too — X could be negative, a fraction, a decimal, anything.

Step 2: Ask if you can simplify the question.

Some data sufficiency questions can be simplified with a little algebra. If you can make the question simpler before evaluating the statements, do it. You will not be able to simplify every question. But when you can, it helps.

Step 3: Evaluate Statement 1 alone, in a vacuum.

Do not look at Statement 2. Do not let it cloud your judgment. Ask: is Statement 1 by itself enough to answer the question?

If Statement 1 is not sufficient, you can eliminate A and D.

If Statement 1 is sufficient, you can eliminate B, C, and E.

Step 4: Forget Statement 1. Evaluate Statement 2 alone, in a vacuum.

This might be the hardest part. You have to actively delete Statement 1 from your mind. Scratch it off your scratch pad if that helps. Evaluate Statement 2 on its own.

If Statement 2 is sufficient and Statement 1 was not, pick B.

If Statement 2 is sufficient and Statement 1 also was, pick D.

Step 5: If neither statement alone is sufficient, combine them.

You have already established that Statement 1 alone is not enough and Statement 2 alone is not enough. Now you are allowed to put them together.

If combined they are sufficient, pick C.

If combined they are still not enough, pick E.

Step 6: Pick your answer.

That is the full process. It works because you can run it on every single data sufficiency question.

A Simple Example

Here is an easy DS question to see the process in action.

What is the value of x?

(1) x + 2 = 5

(2) x is a positive integer.

Step 1: Write what is given and what is asked.

Asked: the value of x. No constraints in the question stem — x could be anything.

Step 2: Can we simplify the question?

Not really. "What is the value of x?" is already as simple as it gets.

Step 3: Evaluate Statement 1 alone.

x + 2 = 5. Subtract 2 from both sides. x = 3.

That is one definitive answer. Statement 1 is sufficient. Eliminate B, C, and E.

Step 4: Forget Statement 1. Evaluate Statement 2 alone.

x is a positive integer. So x could be 1, 2, 3, 4, 5, and so on. There is no way to narrow it down to one value.

Statement 2 is not sufficient. Eliminate D.

Step 5: Combine?

Not needed — Statement 1 was already sufficient on its own.

Step 6: Pick your answer.

Statement 1 alone is sufficient. Statement 2 alone is not. That is answer choice (A).

Notice what happened. The math was trivial — you probably solved it in your head. But the point is the process. If you run these six steps on every DS question, you will not lose track of which statement you are evaluating or what you have already eliminated. On harder questions, that structure is what keeps you from making mistakes.

Write Everything Down

If it is happening in your head on a data sufficiency question, it should be happening on the page.

This goes against what a lot of people will tell you. Many students and even some instructors say you do not need to write everything down on DS. Our experience says otherwise.

The whole point of data sufficiency is to trick you. The questions are designed to make sufficient data look insufficient, or insufficient data look sufficient. Writing out your work helps you track where you are logically. It frees up brain power for problem-solving instead of holding information in your head.

If you are just starting out, let yourself be slow on DS questions. Do not worry about finishing in two minutes. Focus on building great scratch work habits and stepping through the process. Speed comes later.

Being fast and bad at data sufficiency is not much better than being slow and bad at it. Build the habits first. The speed will follow.

The Calculator: Use It

The Data Insights section has an on-screen calculator. You can show it and hide it with a button on the screen.

Our advice: keep it visible the entire section.

Here is why. On the quant section, there is no calculator. You spend 45 minutes training yourself to do math in your head and on paper. Then you switch to Data Insights and you have a calculator — but most students forget to use it because they are so conditioned to doing without.

Keeping the calculator visible the whole section prevents that.

When should you use it? For quick computations — anything under 90 seconds on the calculator. If you are about to do more than 90 seconds of calculations, you are probably better off estimating.

The calculator is not as useful as you might want it to be. But when it is useful, it makes a difference. It cuts down on computation errors and reduces mental fatigue across the exam.

Sometimes the calculator will cover up part of the question. If that happens, move it or hide it temporarily. Just bring it back as soon as you can.

What Score Do You Need in Data Insights?

For most top schools, a 78 out of 90 or higher in Data Insights is a good target.

Below that, you can still be competitive — but it becomes an area worth improving. If you are scoring 75 or 76 on practice tests, that should be a focus.

For schools outside the top 20, 76 or higher is probably fine. Outside the top 50, 73 or higher should work.

Once you reach your target score in DI, shift your energy to whichever section will move your overall three-digit score the fastest. One to two sub-score points on any section will typically move your overall score by about 10 points.

For a full breakdown of how scoring works, see our guide on how the GMAT® scoring algorithm works.

How to Study for Data Insights

Here is the approach we recommend.

Build quant and verbal first

Since integrated reasoning combines quant and verbal content, improving those sections will naturally help your DI score. Start there. Be all in on quant and verbal.

Transition to DI-specific strategy once your foundational skills are solid. The exception is if you are already strong in quant and verbal but struggling with DI. In that case, jump into DI work sooner.

Use old materials

All GMAT® Classic integrated reasoning and data sufficiency materials are relevant. Do not worry about finding resources labeled "Data Insights." Use old IR practice questions, old DS questions, past official exams, and community-created problems on GMAT Club.

For IR, volume helps

Unlike most GMAT® question types where we recommend fewer problems with deeper review, integrated reasoning responds well to repetition. If you are struggling with IR timing or accuracy, doing a lot of problems can help. Just make sure you are still learning from each one.

For DS, process first, speed later

Build your scratch work habits and six-step process first. Practice untimed if you need to. Once the process is automatic, speed will come.

If you have been struggling with data sufficiency and suspect your process or scratch work is the issue, take the time pressure away. Practice as many as you need untimed. Build the habits. Then add timing back in.

Take practice tests

The Data Insights section is adaptive. That means your strategy for the overall section — when to guess, when to invest, when to move on — matters. You can only practice that under realistic conditions.

Take full-length practice tests. Pay attention to how you feel during the DI section. Are you rushing? Are you forgetting the calculator? Are you running out of time on IR but finishing DS easily?

Those patterns tell you what to work on.

For a complete framework for building your study plan, see our GMAT® study guide and our guide on how to build a study plan that works.

FAQ

Is the GMAT® Data Insights section new?

It is newer in name, but not in content. Data Insights combines integrated reasoning and data sufficiency — two question types that have been on the GMAT® for years. Integrated reasoning is essentially unchanged from the old exam. Data sufficiency has one small change: about half the questions are now pure logic with little or no computation. The process for solving them is the same.

How many questions are on the Data Insights section?

20 questions in 45 minutes. You will see roughly 12–15 integrated reasoning questions and 5–8 data sufficiency questions. The exact mix varies.

Is there a calculator on Data Insights?

Yes. There is an on-screen calculator you can show and hide with a button. We recommend keeping it visible the entire section so you do not forget to use it. Use it for quick computations. For anything that would take more than 90 seconds on the calculator, estimate instead.

Is the Data Insights section adaptive?

Yes. All three sections on the GMAT® Focus Edition are question-adaptive. The difficulty adjusts based on your performance as you go. This is a change from the old exam, where integrated reasoning was not adaptive.

What is a good Data Insights score?

For most top schools, aim for 78 or higher out of 90. For schools outside the top 20, 76 or higher should work. Outside the top 50, 73 or higher is likely fine. Once you reach your target, focus on whichever section will move your overall score the fastest.

Do you need special materials for Data Insights?

No. All GMAT® Classic integrated reasoning and data sufficiency materials are relevant. The question types have not changed. Use old IR practice questions, old DS questions, official practice exams, and community-created problems. The lack of "Data Insights" labeled resources is not a problem.

Should you study Data Insights before quant and verbal?

Usually no. Since integrated reasoning combines quant and verbal content, building those skills first will naturally lift your DI score. Focus on DI-specific strategy and timing once your foundations are solid. The exception is if you are already strong in quant and verbal but struggling with DI — then start DI work sooner.

What is the difference between data sufficiency and problem solving?

Problem solving asks you to find an answer. Data sufficiency asks you whether you have enough information to find an answer. On DS, you do not always need to solve the problem — you just need to determine whether the given statements provide enough data to solve it. The five answer choices (A through E) are the same on every DS question.

Want to learn even more?

We covered all of this in depth on the podcast. Our complete guide to the Data Insights section walks through all four IR question types, the full data sufficiency process, calculator strategy, and scoring targets.

You can listen to the full episode on Spotify, Apple Podcasts, or on our podcast page.

If you are building your study plan, here are a few related guides:

• How to Study for the GMAT®: A Complete Guide
• What's on the GMAT®: The Complete Topic List
• How Long Should You Study for the GMAT®?
• What is a Good GMAT® Score?
• Is the GMAT® Hard?
• How to Build a GMAT® Study Plan That Works