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Data interpretation

Placement essentials (aptitude, reasoning, verbal, communication, interviews, Excel, workplace) (All) · Quantitative aptitude · free study notes for exams, placements and interviews

In short

Data interpretation (DI) is the skill of reading numbers presented as a table, bar graph or mixed data set and answering questions on totals, shares, ratios, averages and growth. It is pure arithmetic — percentages, ratios and averages — applied under time pressure, so the difficulty lies in reading the data correctly and calculating fast, not in new theory. It is the largest single block in banking and insurance exams (IBPS, SBI, RBI, LIC), forms the DILR section of CAT and the QA-DI section of XAT, and appears in every campus aptitude test (TCS NQT, Infosys, Wipro NLTH, Capgemini, Accenture, Cognizant, Deloitte, ZS). On the job the same skill is MIS reporting, dashboard reading and business review analysis in every Indian company.

Explained

What a DI set is and what it asks

Tabular data interpretation

Bar graphs and their variants

Core calculations used in every DI set

Missing-data and multi-set DI

Approximation, estimation and time management

Traps, reading rules and limitations

Key points

Formulas and examples

Percentage change = (New value − Old value) / Old value × 100 (%; negative means a fall)
Percentage share of a part = Part / Total × 100 (%)
Overall (combined) percentage = (Σ parts / Σ bases) × 100 — the weighted average
Comparison of ratios: a/b > c/d ⇔ a·d > b·c (b, d > 0)
Net effect of two successive changes a% and b% = a + b + (a·b)/100 (%)
CAGR = [(Final / Initial)1/n − 1] × 100, n = number of periods (years)
If A is x% more than B, then B is less than A by 100x/(100 + x) %
If A is x% less than B, then B is more than A by 100x/(100 − x) %
Average = Sum of values / Number of values; Missing value = (Average × n) − (sum of known values)
Percentage point difference = P₂ − P₁ (both in %); relative change = (P₂ − P₁)/P₁ × 100

Example 1 — Table DI: revenue of five IT firms (₹ crore)

FirmFY23FY24ChangeGrowth %
Alpha1,2001,500+30025.0
Beta8001,040+24030.0
Gamma1,5001,650+15010.0
Delta640800+16025.0
Epsilon9601,152+19220.0
Total5,1006,142+1,04220.43

Example 2 — Grouped bar graph: students appeared and passed

CollegeAppearedPassedFailedPass %
A80060020075.00
B1,20084036070.00
C95076019080.00
D1,05073531570.00
Total4,0002,9351,06573.375

Example 3 — Table with absolute values and percentages: bank recruitment

ZoneApplicants (thousand)Selection %Selected
North1202.53,000
South904.03,600
East1501.82,700
West803.52,800
Total440—12,100

Example 4 — Missing-data table: employees by department (total 2,400; male : female = 5 : 3)

Males = 2,400 × 5/8 = 1,500; females = 2,400 × 3/8 = 900.

DepartmentTotalMaleFemale
Sales600420180
Technology900600300
HR300120180
Operations400220180
Finance20014060
Total2,4001,500900

Example 5 — Growth, CAGR and reverse percentage

Where it is used

Interview questions

Common mistakes

Related topics

Percentages · Ratio, proportion and partnership · Averages, mixtures and alligation · Data interpretation: pie charts, line graphs and caselets · Simplification and approximation · Excel formulas, pivot tables and charts

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