Mastering the GMAT Data Insights Section: Comprehensive Review and Final Tips
- Goalisb
- Jun 22
- 5 min read
Updated: Jul 11
The GMAT Data Insights section is a comprehensive test of your data interpretation, critical thinking, and decision-making skills, integrating abilities that are invaluable in the modern business environment. In this post, we’ll recap the key question types—Multi-Source Reasoning, Table Analysis, Graphics Interpretation, and Two-Part Analysis—and provide you with a final set of strategies to help you approach each question type confidently.
1. Overview of the GMAT Data Insights Section
The Data Insights section evaluates your ability to analyze, interpret, and integrate data from multiple sources, including tables, graphs, text, and multi-part problems. Here’s a quick recap of each question type:
Multi-Source Reasoning: Requires synthesizing data from multiple sources, such as tables, graphs, and text in separate tabs. It tests your ability to cross-reference and draw insights from varied information.
Table Analysis: Focuses on sorting and filtering data within a table, often requiring you to calculate ratios, percentages, or identify trends.
Graphics Interpretation: Involves interpreting data presented in visual formats like line graphs, bar charts, pie charts, or scatter plots, testing your skills in extracting trends and understanding variable relationships.
Two-Part Analysis: Presents complex scenarios where you’ll need to provide two answers to a single problem, often balancing quantitative and verbal reasoning.
2. Comprehensive Strategy Guide for GMAT Data Insights
Each question type requires specific skills and strategies, but some overarching tips can help you approach the Data Insights section as a whole.
Step-by-Step Strategy for Each Question Type
Multi-Source Reasoning:
Focus on Each Source Separately: Start by reviewing each data source (tabs, text, graphs) to understand the key information in each. Familiarize yourself with what’s provided before cross-referencing.
Prioritize Relevant Data: These questions often contain distractors. Focus on data related to the question prompt and avoid unrelated information.
Cross-Reference Carefully: Practice moving between tabs efficiently to find relationships between data points across sources.
Table Analysis:
Skim and Sort: Start by skimming column headers and labels, then sort the table by the most relevant column(s) to streamline your analysis.
Use Calculations Sparingly: Only calculate values required by the question—this helps prevent errors and saves time.
Filter Out Unnecessary Rows: Narrow your focus by identifying the rows relevant to the question prompt.
Graphics Interpretation:
Examine Labels and Units: Titles, axis labels, and units provide critical context for understanding the graphic. Take a few seconds to examine these details.
Identify Major Trends or Points: Focus on high points, low points, or intersections, as these often hold clues for answering the question.
Estimate When Possible: Often, an approximate answer is all that’s needed. Use the graph’s scale to make quick estimations rather than precise measurements.
Two-Part Analysis:
Separate Each Part: Start by addressing each part of the question individually. Solve each part as if it were an isolated question, then bring the answers together.
Check for Compatibility: Ensure that your answers for Part 1 and Part 2 are compatible, especially in scenarios where one answer affects the other.
Consider Constraints and Relationships: Two-Part Analysis questions often include specific conditions (e.g., budget limits or minimum requirements) that you must satisfy.
3. Final Tips and Common Pitfalls to Avoid
Understand the Context of Each Problem: The Data Insights section often uses real-world business contexts, so think about the logical implications of each answer.
Avoid Over-Reliance on Calculation: While some questions require precise calculations, many do not. Look for ways to approximate or use logic to answer questions without performing every calculation.
Practice Multi-Tab Navigation: For Multi-Source Reasoning questions, practice moving between tabs efficiently. Familiarity with navigating and cross-referencing different tabs will save time.
Avoid Getting Bogged Down in Details: Many questions include extra data to test your ability to prioritize relevant information. Identify what’s relevant based on the question prompt and avoid distractions.
Time Management is Key: The Data Insights section is time-sensitive. Each question type has unique time demands, so be mindful of spending too long on any single question. If you’re struggling with a question, move on and return to it if time permits.
Sample Review Question Covering Multiple Types
Let’s bring everything together with a comprehensive question that combines different Data Insights skills.
Example Scenario
A company is evaluating sales and customer satisfaction data for three of its divisions—Retail, Technology, and Healthcare. The company has multi-tab data available with detailed figures.
Tab 1: Sales Data (Table)
Division | Q1 Sales (in millions) | Q2 Sales (in millions) | Q3 Sales (in millions) | Q4 Sales (in millions) |
Retail | 30 | 35 | 32 | 38 |
Technology | 40 | 45 | 42 | 48 |
Healthcare | 25 | 28 | 26 | 30 |
Tab 2: Customer Satisfaction (Line Graph)
The graph shows quarterly customer satisfaction scores (out of 100) for each division over the last four quarters, with Technology consistently scoring the highest.
Sample Question
Part 1: “Which division had the highest Q4 sales?”
Part 2: “Which division had the highest average customer satisfaction score across all quarters?”
Solution
Step 1: Examine Sales Data in Tab 1
For Q4 sales, we see:
Retail: $38 million
Technology: $48 million
Healthcare: $30 million
Highest Q4 Sales: Technology at $48 million.
Step 2: Check Customer Satisfaction Data in Tab 2
The line graph shows Technology consistently scoring the highest across all quarters.
Answer:
Part 1: Technology Division for highest Q4 sales.
Part 2: Technology Division for highest average customer satisfaction.
Correct Answer: Technology for both Part 1 and Part 2.
Conclusion
Mastering the GMAT Data Insights section requires a blend of quantitative, analytical, and decision-making skills. By understanding each question type and using these strategies, you can approach this section with confidence. Consistent practice with real-world scenarios will further solidify your ability to analyze, synthesize, and make decisions based on data.
Ready to Take Your Skills to the Next Level? Practice each question type with dedicated exercises, stay focused on time management, and remember that confidence comes from familiarity. For more tips and sample questions, subscribe to our GMAT prep resources or follow along with our blog series.
