Banking Notes / Quantitative Aptitude / Chapter 19
Chapter 19 of 26

Data Interpretation (Table, Line, Bar, Pie, Caselet, Missing DI)

Every DI format tested in bank mains, with the calculation-speed techniques that make each one manageable within the time limit.

📖 ~11 min read 🏦 Banking Quantitative Aptitude

Introduction

Data Interpretation applies every earlier arithmetic chapter — percentage, ratio, average — to a real dataset presented as a table, graph, or short passage (caselet). DI carries the heaviest weightage in bank mains and rewards accurate approximation over exact calculation.

DI Formats You'll See

FormatWhat It Tests
Table DIReading and cross-referencing multiple rows/columns of raw data
Line GraphTrend and rate-of-change reading across periods
Bar GraphDirect value comparison across categories
Pie ChartPercentage-of-total distribution; often needs conversion to actual values
CaseletData embedded in a written paragraph — must be extracted before calculating
Missing DISome data cells are blank and must be derived from the relationships given
Q. A pie chart shows a company's expenses: Salary 40%, Rent 15%, Marketing 20%, Others 25%. If total expense is ₹8,00,000, find the amount spent on Marketing.
Marketing = 20% of 8,00,000 = (20/100) × 800000 = ₹1,60,000.
Q. In a table, Store A sold 240 units in Jan and 300 in Feb. Find the percentage increase.
Increase = 300−240 = 60. % increase = (60/240) × 100 = 25%.
⚠️ Key Insight: In Missing DI, use row/column totals and any given ratio or percentage relationship as simultaneous clues — work out the easiest missing value first, since it often unlocks the rest.
💡 Exam Tip: Use the fraction-equivalent table from the Percentage chapter to estimate DI answers quickly, then compare against the options — bank DI rarely needs exact decimal precision.
✅ Practice Focus: Converting pie chart percentages to actual values · Reading trends from line graphs · Extracting numeric relationships from caselet paragraphs · Filling in Missing DI using totals.

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