GMAT Data Insights is one of the three scored sections on the GMAT Focus Edition, alongside Quant and Verbal. It runs 45 minutes for 20 questions and covers five formats: Data Sufficiency, Multi-Source Reasoning, Table Analysis, Graphics Interpretation, and Two-Part Analysis. Unlike the old Integrated Reasoning section, Data Insights counts fully toward your total score, worth exactly as much as Quant or Verbal. That's why it can no longer be an afterthought in your prep.
What Is GMAT Data Insights?
Data Insights measures how well you pull relevant information out of tables, charts, passages, and quantitative prompts, then use it to make a decision. It replaced the old GMAT's separate Integrated Reasoning section and absorbed Data Sufficiency, which used to live inside Quant.
The section is 45 minutes long, contains 20 questions, and allows an on-screen calculator. You can take the three sections (Quant, Verbal, Data Insights) in any order you choose at the start of the exam, and Data Insights is graded on the same 60-90 scale as the other two sections. Because it's newer and less familiar to most test-takers than Quant or Verbal, it's also where a lot of avoidable points get left on the table.
What Is Data Sufficiency?
Data Sufficiency gives you a question and two statements. Your job isn't to solve the problem. It's to decide whether each statement, alone or together, gives you enough information to answer the question with certainty.
Worked example: Is integer divisible by 6?
(1) is divisible by 2.
(2) is divisible by 3.
Statement (1) alone isn't sufficient: is divisible by 2 but not 6. Statement (2) alone isn't sufficient either: is divisible by 3 but not 6. Together, a number divisible by both 2 and 3 is divisible by 6, so the combination is sufficient. The answer is C.
Tactic: Use the AD/BCE grid. Test statement (1) completely on its own before you even glance at statement (2). If (1) is sufficient, the answer is A or D. If (1) is not sufficient, the answer is B, C, or E. Never let information from one statement leak into your evaluation of the other.
What Is Multi-Source Reasoning?
Multi-Source Reasoning (MSR) presents two or three tabbed sources, which might be an email, a data table, a policy document, or a chart, and then asks a set of two or three questions built on those combined sources. Some questions test a single tab; others require you to reconcile information that appears in two different places.
Worked example: Tab 1 is a customer's email describing a delayed shipment. Tab 2 is the company's refund policy, which states refunds apply only to shipments delayed more than 5 business days. Tab 3 is an order log showing the shipment was delayed 4 business days. A question asks whether the customer qualifies for a refund. You need Tab 2's threshold and Tab 3's actual delay together. Since 4 is less than 5, the answer is no, even though Tab 1 (the complaint) reads as though the customer deserves one.
Tactic: Skim all tabs once before answering anything, just to learn what lives where. Then treat each question as a targeted lookup instead of rereading everything from scratch. MSR rewards a mental map of the sources more than it rewards speed-reading.
What Is Table Analysis?
Table Analysis gives you a sortable table, similar to a spreadsheet, and asks you to evaluate a series of statements as true/false or yes/no based on what the table shows. You can sort by any column, which is the whole point: most questions are really asking you to filter or rank the data first.
Worked example: A table lists 40 employees with columns for department, salary, and years of tenure. A statement claims "more than 10 employees in the Sales department earn over $70,000." Sorting by department, then scanning salaries within the Sales rows, turns a scan-the-whole-table problem into a five-second count.
Tactic: Sort before you read closely. Sorting by the column mentioned in the statement almost always turns the question into a straightforward count or comparison instead of a manual search.
What Is Graphics Interpretation?
Graphics Interpretation shows a chart, which could be a scatter plot, bar chart, line graph, pie chart, or statistical distribution, and asks you to complete one or two sentences by choosing from dropdown menus. The sentences typically describe a relationship, a trend, or a specific data point.
Worked example: A scatter plot shows advertising spend on the x-axis and monthly sales on the y-axis for 15 stores, with a clear upward trend. A sentence reads: "The relationship between advertising spend and sales is best described as [dropdown]," with options like positive, negative, or no correlation. A second sentence asks which store deviates furthest from the trend line, with specific store names as dropdown options.
Tactic: Read the title, axis labels, and units before you look at the shape of the data. A lot of wrong answers come from correctly reading the chart but misreading what the axes actually measure.
What Is Two-Part Analysis?
Two-Part Analysis poses a problem with two related unknowns and asks you to pick one answer for each from a shared table of choices. The two parts can be independent tasks or, more often, dependent ones where solving for one constrains the other.
Worked example: An investor puts a total of $10,000 into two funds. Fund A earns 5% annually and Fund B earns 8% annually. Total interest earned after one year is $650. How much was invested in each fund?
Set up and . Substituting gives , which simplifies to , so and .
Tactic: Decide immediately whether the two parts are dependent or independent. If they're dependent, write the constraint as an equation before you touch the answer table. Guessing-and-checking against the table wastes far more time than solving algebraically first.
Question-Type Reference Table
How Is Data Insights Scored?
Data Insights is scored on a 60-90 scale, in 1-point increments, exactly like Quant and Verbal. All three section scores combine into a total score of 205-805, and each section contributes equally.
This is the detail most test-takers miss coming from older GMAT prep material: the old Integrated Reasoning section had its own separate 1-8 score and never touched your 200-800 total. On the Focus Edition, Data Insights is worth exactly as much as Quant. A weak Data Insights score can cap your total the same way a weak Quant score always could. Treating it as a warm-up section instead of a scored third of the exam is one of the most common (and costly) prep mistakes right now.
How Do I Practice Data Insights?
Start by isolating each question type until the format itself stops slowing you down. Data Sufficiency logic, MSR tab-switching, Table Analysis sorting, Graphics Interpretation dropdowns, and Two-Part Analysis setups each require a different first move, and mixing them too early just trains confusion instead of skill.
Once each type feels routine on its own, move to mixed sets under real timing. The actual section shuffles question types with no warning, so your prep should too. Pay attention to the on-screen calculator during practice as well. It's available throughout Data Insights, and knowing exactly when reaching for it saves time versus mental math is its own skill worth building.
Because Data Insights is the newest section, there's far less practice material out there for it than for Quant or Verbal, and a lot of what exists doesn't match the real format closely enough to be useful. Hire A Clanker builds Data Insights practice sets with the same sortable tables, tabbed source panels, dropdown-based Graphics Interpretation, and on-screen calculator you'll actually see on test day. You can read more about how the section fits into the full exam on our GMAT Focus overview, see our approach on the method page, jump straight into practice, or start a free trial to try a full Data Insights set yourself.
Data Insights rewards a specific kind of preparation: format familiarity first, speed second. Most test-takers still under-prepare it relative to how much of the total score it controls. That gap is closing fast, which makes now the right time to close it in your own prep too.