Data Interpretation Decoded For CAT- Pattern, How To Prepare

The candidate’s capability to interpret, understand, and analyze data to come to an optimal decision is evaluated in the data interpretation section. A manager is required to utilize and handle data in terms of budget allocations, demand forecasts, market analysis, sales reports, and other data analysis. The syllabus of data interpretation for the CAT section is comprised of data comparison and data analysis questions. 

The Pattern Of Data Interpretation For CAT

The CAT exam is for 40 minutes and has 24 questions. Every answer carries 3 marks and there is a negative marking of one mark for a wrong answer. The data for data interpretation is in the form of cases, graphs, charts, and tables in this section. If we look into the previous question papers then this section had 5 sets of questions. Out of these, 2 sets comprised of 6 questions and 3 sets had 4 questions. 

The pattern can be explained as mentioned below:

Data Interpretation in DILR sectionComposition
Name of the sectionData Interpretation and Logical reasoning
Total questions in the DILR section32
Number of questions in Data Interpretation section4
Type of questions in data interpretation4 sets of questions based on 4 data interpretation 
Total questions based on data interpretation16
Composition of data interpretation based questions4 Non-MCQ’s12 MCQ’s
Questions in DI section based on time and distanceNil
Total time allotted for DILR section1 hour (regular), 40 minutes (Expected)
Marks for every correct answer3
Negative marks for every wrong answer-1
Difficulty levelModerate to high
No negative marking questions in Data interpretation4 Non-MCQ’s
Recommended books for Data InterpretationHow to prepare for Data Interpretation for CAT authored by Arun SharmaLogical Reasoning and Data Interpretation for CAT authored by Nishit K Sinha

The composition of questions in the data interpretation for CAT are mentioned below:

Set of questionsQuestion detailsNumber of Questions
Set 1: Charts and TablesData Comparison in the form of years, age, and others4
Set 2: Bar diagrams, GraphsComparison and Analysis of data in the form of groups, years, and others4
Set 3: Pie charts, TablesFinding, Interpreting, or decoding missing links, missing periods, taking clues, and data4
Set 4: Graphs, chartsFuture projections, Conclusion, Data analysis4
Total Questions4 non-MCQ’s and 12 MCQ’s16

How To Prepare For The CAT Data Interpretation Exam?

The only means to prepare for this section of the CAT exam is to practice more and more. The reason for the same is that there is no particular formulae or concept in data interpretation. It is recommended that data interpretation should be decoded for CAT in this section of the question paper, through solving with the easier and less time-consuming set of questions. 

Some of the skills that the candidate should concentrate on for gaining proficiency in this section of the exam is as follows:

Some of the skills that the candidate should concentrate on for gaining proficiency in this section of the exam is as follows:

1. Approximations & Calculations

A person has to be an expert in calculation skills when you are solving the data interpretation section of exams. These questions normally include decimal to fraction conversions, ratios, percent changes, and many more. Learning approximation techniques, and advanced calculation would be an added advantage for the preparation.

2. Structure & Logic

If the candidate can understand the logic behind any given data, then solving any questions based on it becomes easier. A particular structure is always followed in the given data and information. If you identify this logic and structure, then solving the question and finding the answer to it becomes easier and quicker. 

3. Practice

To become an expert in solving data interpretation questions it is vital to practice it regularly. The best practice is to solve at least 3 to 4 questions daily. The most important benefit of such a practice is that it enhances speed and accuracy. Also, the candidate would be able to develop the skills more efficiently and effectively. The elimination technique can be a resort when there are a lot of calculations to be done to arrive at the answer.

Some of the quick tips and tricks to prepare for the data interpretation section are mentioned below:

  • Refer latest trends and questions as in the CAT examination
  • It is recommended to read the best data interpretation books
  • Practice several and different types of questions and answers in data interpretation
  • Develop the skills for data analysis and comparison and logical thinking to solve any questions accurately and meticulously.
  • Practising more and more DI questions develop a better solving procedure.
  • Get preparation material from any good coaching platform like Oliveboard.
  • Read and refer to the strategy followed by CAT toppers.
  • Follow mock test for data interpretation for CAT

Frequently asked Questions

What is data interpretation for CAT?

The section where the candidates have to analyze the data in the form of a myriad of graphs, tables, and charts and draw a conclusion is called data interpretation. The questions can be solved easily by understanding, decoding, and interpreting data.

How do you start data interpretation?

Data interpretation can be done by following the below-mentioned steps:
Assemble the required information
Develop and analyze findings
Create conclusions
Provide recommendations

State the different types of data interpretation.

Data interpretation can be categorized as ordinal data and nominal data. The same method is used for interpreting both data types. However, if compared ordinal data interpretation is easier as compared to nominal data.

What is the difference between data interpretation and data analysis?

The process of uncovering trends and patterns in the data is called data analysis. The process of concluding the data is called data interpretation. This includes explaining the patterns and trends that are discovered in the data in a more meaningful way.

State the different techniques for data interpretation

Consecutive interpretation
Simultaneous interpretation
Whispered Interpretation
Sight Translation


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