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Wipro · Data Analyst

Wipro Data Analyst Interview Questions (2026): process, questions and answers

Updated 6 November 2026 · prep guide

The Wipro Data Analyst interview usually focuses on SQL, Excel, visualization tools and basic statistics. Use this guide to rehearse concise answers, understand typical case questions and plan a focused last‑minute review.

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How the Wipro Data Analyst interview usually works

  1. application: Candidates usually submit a resume and an online assessment that tests basic analytical thinking
  2. technical screening: A recruiter or analyst often asks SQL, Excel and visualization questions over a video call
  3. case discussion: Interviewers commonly present a business scenario and expect you to outline an analytical approach
  4. final interview: A senior manager may explore your past projects, communication style and cultural fit

Technical questions and answers

How would you write a query to find customers who placed orders in the last 30 days but not in the previous month?

Use a subquery or CTE to select distinct customer IDs from the orders table where order_date is between current_date minus interval '30 days' and current_date, then left join to the same table filtered for the period 30‑60 days ago and keep rows where the right side is null. This isolates recent customers without activity in the prior month.

Explain how you would use the LAG() window function to compare each day's revenue with the previous day’s revenue.

Select date, revenue, and LAG(revenue) OVER (ORDER BY date) as prev_rev from the sales table. Then compute revenue‑prev_rev as daily_change. LAG returns the value from the preceding row according to the order clause, allowing a direct day‑over‑day comparison without a self‑join.

What steps do you take to normalize a dataset that contains mixed units for the same metric?

Identify the metric and list all unit variations, create a mapping table that defines a conversion factor to a standard unit, then apply a calculated column that multiplies the original value by the factor. Verify the conversion by sampling a few rows and checking totals before and after.

How do you calculate the 95 % confidence interval for a sample mean in Excel?

First compute the sample mean with AVERAGE, the standard deviation with STDEV.S, and the count with COUNT. Then use the formula mean ± T.INV.2T(0.05, count‑1)*stdev/SQRT(count). The T.INV.2T function returns the two‑tailed t‑value for the desired confidence level.

Describe a method to detect and flag outliers in a numeric column using the IQR rule in SQL.

Calculate Q1 and Q3 with PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY col) and PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY col). Compute IQR as Q3‑Q1, then define lower_bound as Q1‑1.5*IQR and upper_bound as Q3+1.5*IQR. Use a CASE expression to label rows where col < lower_bound or col > upper_bound as outlier.

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When would you prefer a stacked bar chart over a grouped bar chart in Power BI?

Use a stacked bar when you want to show the composition of each category and emphasize the total size across categories. Choose a grouped bar if the focus is on comparing individual sub‑categories side by side. Stacked bars help illustrate part‑to‑whole relationships, while grouped bars highlight differences between sub‑categories.

How do you create a calculated field in Tableau to show year‑over‑year growth percentage?

Create a field called YoY Growth with the formula ((SUM([Sales])‑LOOKUP(SUM([Sales]), -12))/LOOKUP(SUM([Sales]), -12))*100. The LOOKUP function fetches the value from the same month last year, and the expression computes the percentage change.

What is the purpose of a data dictionary and how would you maintain one for a reporting project?

A data dictionary documents each field’s name, type, definition, source and allowed values. Maintain it by storing the information in a shared spreadsheet or wiki, updating entries whenever a new column is added or its meaning changes, and linking it to the ETL scripts or model metadata for easy reference by analysts and developers.

Explain how you would use conditional formatting in Excel to highlight rows where the profit margin falls below a threshold.

Select the data range, choose Conditional Formatting > New Rule > Use a formula to determine which cells to format, and enter a formula like =$D2<$E$1 where column D holds margin and E1 contains the threshold. Then set a fill colour. Excel will apply the colour to any row where the condition is true.

How can you verify that a Power BI measure respects row‑level security when testing a report?

Create two test user accounts, assign them different security roles, and publish the report to the service. Log in as each user and observe the measure’s values; they should reflect only the data permitted for that role. Additionally, use the ‘View as Role’ feature in Power BI Desktop to preview results without publishing.

Scenario questions

A client in the banking sector asks you to identify why loan approval rates have dropped over the last quarter. How would you approach this?

Start by clarifying the metric definition and time frame, then gather relevant tables such as applications, approvals, and customer demographics. Perform data quality checks for missing or inconsistent fields. Use SQL to calculate approval rates by segment and month, and create visualisations in Power BI to spot trends. Look for changes in applicant profiles, credit scores or policy parameters, and prepare a concise recommendation based on the findings.

Your manager needs a dashboard that shows real‑time ticket volume and average resolution time for an IT support project. What steps would you take?

Identify the source system that stores ticket data and confirm the availability of an API or incremental load. Design an ETL pipeline that extracts new records every few minutes, transforms timestamps and calculates daily averages, then loads into a Power BI dataset. Build a report with a line chart for volume, a KPI card for average resolution, and a slicer for priority. Validate the numbers against the source system before publishing.

During a data cleaning task you find that dates are stored in multiple formats across several CSV files. How do you standardise them before analysis?

Load the files into a staging table or Power Query, create a column that parses each format using conditional logic, for example CASE WHEN ISDATE(col, 'MM/DD/YYYY') THEN CONVERT(date, col, 101) WHEN ISDATE(col, 'DD‑MM‑YYYY') THEN CONVERT(date, col, 105) END. After conversion, store the result in a single ISO‑8601 date column and drop the original raw column.

HR and behavioural questions

Tell me about a time you missed a deadline and how you handled it.

Use the STAR structure: Situation, you had a reporting deadline, Task, deliver a dashboard, Action, you discovered a data source issue, communicated early to the stakeholder, worked overtime and involved a colleague to resolve the problem, Result, delivered the dashboard two days later with an explanation and a post‑mortem to prevent recurrence.

Describe a situation where you had to explain a complex analytical finding to a non‑technical audience.

Explain the context, simplify the metric, use an analogy, and focus on business impact. For example, compare churn probability to a weather forecast, show a clear visual, and end with actionable recommendations. Emphasise clarity and avoid jargon.

Give an example of how you dealt with conflicting priorities from two senior managers.

Explain that you first gathered requirements, assessed impact on key metrics, and presented a prioritized plan with trade‑offs. You sought a brief alignment meeting, documented the decision, and kept both managers informed of progress, ensuring transparency and minimizing friction.

What motivates you to work as a data analyst in a consulting environment?

Mention the variety of industries, the chance to solve real business problems, continuous learning through new data sets, and the collaborative nature of consulting projects that allow you to see the impact of your analysis on client decisions.

Your last 48 hours before the interview

  1. Review the key SQL window functions and write one example query for each
  2. Refresh pivot‑table steps and conditional formatting in Excel with a sample file
  3. Re‑create a simple Power BI report using a public dataset to practice slicers and KPI cards
  4. Read a short article on confidence intervals and practice the Excel formula once
  5. Sketch brief answers for the three scenario questions on a notecard
  6. Do a mock interview with a friend, focusing on concise answers within the word limit

Common mistakes to avoid

Frequently asked questions

How many interview rounds are typical for a Wipro Data Analyst role?

Candidates commonly report 3 to 4 rounds, including an HR screen, a technical screening, a case or scenario discussion, and a final manager interview.

What should I prepare for the technical screening?

Focus on SQL joins, window functions, Excel data‑cleaning techniques, basic statistics and a quick demo of Power BI or Tableau. Practice writing short, clear explanations.

Do I need to know programming languages like Python?

It is helpful but not always required. Most candidates report that strong SQL and Excel skills are enough for the initial rounds, and Python may be discussed later if the role involves advanced analytics.

How important is domain knowledge for Wipro projects?

Understanding the client’s industry helps you frame answers, but interviewers usually assess analytical thinking first. Mention any relevant experience and show willingness to learn the specific domain.

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This is an independent preparation guide based on commonly reported interview patterns. The process varies by team, location and year. Interview AI Helper is not affiliated with Wipro.

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