Wipro Data Analyst Interview Questions (2026)

1. 1Elite NTH Online Test60 minMedium

   Online assessment with aptitude/logical/verbal sections, a written essay to test business English, and two coding problems in a choice of languages.

2. 2Turbo Coding Challenge60 minHard

   Harder timed coding round for the premium Turbo package, with DSA problems demanding fully working, efficient solutions.

3. 3Technical Interview40 minMedium

   Panel covers programming fundamentals, OOP, SQL, projects, and simple code on demand; laterals are quizzed on the client account's specific technologies.

4. 4Managerial Round35 minMedium

   For experienced hires, a delivery/account manager explores ownership of deliverables, escalation handling, and team situations on past projects.

5. 5HR Round25 minEasy

   Discussion of Spirit of Wipro fit, integrity questions, relocation and shift willingness, service agreement, and compensation.

1. Q1

   Write a SQL query to find duplicate customer records in Wipro's e-commerce client's returns analysis. How would you decide which record survives?

   MediumSQL roundduplicate detectionWipro-specific

   Context: Wipro e-commerce client's returns analysis

   How to answer: Use GROUP BY/HAVING or ROW_NUMBER over a business key, define survivorship rules, and push the fix upstream. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

2. Q2

   Using window functions, how would you add a 7-day rolling total and a rank within category to Wipro's healthcare client's appointment no-show reporting?

   MediumSQL roundwindow functionsWipro-specific

   Context: Wipro healthcare client's appointment no-show reporting

   How to answer: Contrast aggregate vs window behavior, frame clauses, and partition choices. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

3. Q3

   For Wipro's logistics client's delivery SLA tracking, when would an INNER JOIN silently drop rows a LEFT JOIN would keep? Show the row counts you would check.

   MediumSQL roundjoinsWipro-specific

   Context: Wipro logistics client's delivery SLA tracking

   How to answer: Explain join semantics with unmatched keys, and the count-before/count-after habit. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

4. Q4

   Your monthly GROUP BY summary for Wipro's credit-card client's spend-category dashboard does not match the source system's total. How do you reconcile them?

   HardSQL roundaggregation and reconciliationWipro-specific

   Context: Wipro credit-card client's spend-category dashboard

   How to answer: Compare grain, filters, timezone/date boundaries, late-arriving rows, and duplicates. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

5. Q5

   Which results change when key columns in Wipro's banking client's loan-portfolio reporting contain NULLs — filters, joins, COUNT vs COUNT(col), averages?

   MediumSQL roundNULL handlingWipro-specific

   Context: Wipro banking client's loan-portfolio reporting

   How to answer: Walk NULL semantics through WHERE, JOIN keys, aggregates, and COALESCE defaults. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

6. Q6

   After adding a join, revenue in Wipro's retail client's daily sales dashboard doubled. Debug the query and prove the fix.

   HardSQL roundjoin fan-out debuggingWipro-specific

   Context: Wipro retail client's daily sales dashboard

   How to answer: Detect one-to-many fan-out, pre-aggregate or dedupe the many side, verify with row counts. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

7. Q7

   When would you restructure a nested-subquery report for Wipro's telecom client's churn reporting into CTEs, and what does it cost?

   MediumSQL roundCTEs and subqueriesWipro-specific

   Context: Wipro telecom client's churn reporting

   How to answer: Readability, reuse, debugging layer by layer; note optimizer behavior differences. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

8. Q8

   Find the top 3 products per region by revenue in Wipro's insurance client's claims data mart, handling ties explicitly.

   MediumSQL roundranking problemsWipro-specific

   Context: Wipro insurance client's claims data mart

   How to answer: ROW_NUMBER vs RANK vs DENSE_RANK, and which tie behavior the business actually wants. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

9. Q9

   Your XLOOKUP against the master sheet in Wipro's e-commerce client's returns analysis returns #N/A for valid IDs. What do you check?

   MediumExcel and BI roundlookupsWipro-specific

   Context: Wipro e-commerce client's returns analysis

   How to answer: Trailing spaces, number-vs-text types, exact match mode, and TRIM/VALUE cleanup. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

10. Q10

    Build a pivot summary for Wipro's healthcare client's appointment no-show reporting: what goes in rows, values, and filters, and when does a pivot beat formulas?

    MediumExcel and BI roundpivot tablesWipro-specific

    Context: Wipro healthcare client's appointment no-show reporting

    How to answer: Structure the source as a flat table, choose aggregations, and know pivot refresh limits. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

11. Q11

    List the cleaning steps you would run on a raw extract for Wipro's logistics client's delivery SLA tracking before any analysis.

    MediumExcel and BI rounddata cleaning in ExcelWipro-specific

    Context: Wipro logistics client's delivery SLA tracking

    How to answer: Duplicates, blanks, types, date formats, merged cells, and a repeatable order of operations. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

12. Q12

    In Power BI, when does Wipro's credit-card client's spend-category dashboard need a DAX measure instead of a calculated column?

    HardExcel and BI roundDAX measuresWipro-specific

    Context: Wipro credit-card client's spend-category dashboard

    How to answer: Row context vs filter context, storage cost, and totals that only measures get right. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

13. Q13

    Design the Power BI model for Wipro's banking client's loan-portfolio reporting: which tables are facts, which are dimensions, and why not one flat table?

    MediumExcel and BI rounddata modelingWipro-specific

    Context: Wipro banking client's loan-portfolio reporting

    How to answer: Star schema, relationship directions, and what breaks when everything is one wide table. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

14. Q14

    The client says the Wipro dashboard for retail client's daily sales dashboard takes a minute to load. How do you make it fast?

    MediumExcel and BI rounddashboard performanceWipro-specific

    Context: Wipro retail client's daily sales dashboard

    How to answer: Reduce cardinality, trim visuals, pre-aggregate, and measure before optimizing. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

15. Q15

    Which KPIs go on the first screen of Wipro's telecom client's churn reporting, and what do you deliberately leave out?

    MediumExcel and BI rounddashboard designWipro-specific

    Context: Wipro telecom client's churn reporting

    How to answer: Lead with decisions the client makes weekly; park detail in drill-throughs. State the business question, the data you would pull, and the checks that make the number trustworthy. Walk through the query or steps concretely, naming tables, joins, filters, and edge cases. Close with how you would validate the result and explain it to the stakeholder.

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Clear the online test; revise programming fundamentals and your projects; prepare HR questions

Indicative Data Analyst pay in India: ~₹6–22 LPA (role-level range, not a Wipro-specific figure).

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