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Infosys · Data Analyst

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

Updated 22 October 2026 · prep guide

Infosys Data Analyst interviews usually focus on practical SQL, reporting, Excel, dashboarding, and basic statistics, plus how you handle business problems and data quality. Use this page to practise short, clear answers and to revise the areas that candidates commonly get tested on.

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How the Infosys Data Analyst interview usually works

  1. Screening: Candidates commonly report an initial screening on resume, project experience, and communication. Be ready to explain your current work clearly, especially the data sources, tools used, and the business outcome.
  2. Technical discussion: This stage usually checks your core SQL, Excel, and dashboard skills. Expect direct questions and small scenario based problems where you must explain your logic step by step.
  3. Problem solving: You may be given a business case from a client project, such as reporting, sales analysis, or operations tracking. The interviewer often wants to see how you define the metric, clean the data, and turn findings into action.
  4. Behavioural fit: You may be asked about teamwork, handling unclear requirements, and working with deadlines. Keep answers structured, calm, and focused on what you did and what changed because of it.

Technical questions and answers

How do you use COUNT(*), COUNT(column), and COUNT(DISTINCT column) differently in SQL?

COUNT(*) counts every row, including rows with NULL values. COUNT(column) counts only rows where that column is not NULL. COUNT(DISTINCT column) counts unique non NULL values. In reporting, this matters when you want total records, valid responses, or unique customers. A common mistake is using COUNT(column) and expecting it to include missing values.

What is the difference between ROW_NUMBER(), RANK(), and DENSE_RANK()?

ROW_NUMBER() gives each row a unique sequence, even if values are tied. RANK() gives the same rank to ties, then skips the next rank number. DENSE_RANK() also gives the same rank to ties, but does not skip numbers. Use ROW_NUMBER() for de duplication or top 1 per group, and use the others when ranking tied values in a report.

How would you calculate a rolling 7 day total in SQL?

Use a window function with an ordered date column and a frame clause. For example, SUM(sales) OVER (ORDER BY sale_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW). This gives the current day plus the previous 6 rows, so it works well when there is one row per day. If dates can be missing, you may need to first create a complete date calendar.

How do you handle text values that come in different formats in Excel?

I first standardize the structure with functions like TRIM, UPPER, LOWER, LEFT, RIGHT, and TEXT. If values are inconsistent, I split them into separate columns, clean spaces and special characters, and then rebuild a clean field. For large files, I prefer Power Query if available. The key is to make the format consistent before analysis so filters and joins work correctly.

What is a slicer in Power BI, and when would you use it?

A slicer is a visual filter that lets users interactively choose values such as region, month, product, or business unit. I use it when the report is meant for managers who need quick self service analysis. A good slicer setup should be simple, aligned with the business questions, and not overcrowd the page. It is best for fast filtering, not for complex logic.

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How do you check if a report metric is behaving unusually?

I compare the current value with previous periods, look for sudden spikes or drops, and verify whether the change is real or caused by data issues. I check data freshness, filters, duplicates, and source changes. If needed, I break the metric by region, product, or channel to find the driver. This helps distinguish business movement from reporting errors.

What is the difference between population and sample standard deviation?

Population standard deviation measures variation for the full group, while sample standard deviation estimates variation from a subset. In a sample, the formula uses n - 1 in the denominator to reduce bias. This matters in analysis when you are working with limited data and want to infer behavior of a larger population, such as customers or transactions.

How do you identify outliers in a dataset?

I first check the context, because a value may be unusual but still valid. Then I use simple methods like the IQR rule, z score, or visual checks such as box plots. After finding outliers, I decide whether to correct data entry errors, cap them, exclude them, or keep them. The right choice depends on the business question and whether the value is truly abnormal.

How would you analyse monthly sales data for an IT services account?

I would first confirm the KPI definition, then clean the data and create a time series view. Next I would compare month on month trends, segment by client, project, or region, and check for seasonality or one time events. I would also look at pipeline, delivery status, and billing if available. The final output should explain what changed and what action the business should take.

How do you explain a SQL query to a non technical stakeholder?

I describe the business question first, then explain the query in plain language. For example, I would say it filters the relevant records, combines data from the required tables, and then summarizes the result by month or region. I avoid code heavy detail unless asked. The goal is to show that the query answers a business problem, not just that it runs successfully.

Scenario questions

A client says the dashboard total does not match the source system. How would you investigate it?

Start by confirming whether both sides use the same definition, filters, and time period. Then check for duplicate rows, missing records, refresh timing, and join logic in the model. I would compare totals at a lower level, such as by date or region, to isolate where the mismatch starts. The answer should show a methodical approach, not a quick guess.

You are asked to report customer churn, but the business has not defined churn clearly. What would you do?

I would first ask how the business wants to define churn, for example no activity for 30 days, contract cancellation, or service closure. Then I would test the definition on sample data and confirm whether it fits the process. If there are multiple possible definitions, I would present each one with its impact. The key is to align on a single metric before building the report.

A monthly report has many blanks and inconsistent category names. How would you clean it before analysis?

I would profile the data first to see where blanks and inconsistent labels appear. Then I would standardize category names, handle missing values based on business rules, and document every change. If possible, I would create a repeatable cleaning step in SQL, Excel, or Power Query instead of doing manual fixes. The goal is clean, traceable data that can be refreshed easily.

HR and behavioural questions

Tell me about yourself.

Structure it as present, past, future. Start with your current role or most recent project, then mention the tools you use, such as SQL, Excel, or Power BI, and one result you contributed to. End with why this role fits your skills. Sample answer: I work on reporting and analysis, mainly using SQL and dashboards, and I enjoy turning messy data into clear business insights.

Describe a time you worked with a difficult stakeholder.

Use Situation, Task, Action, Result. Focus on how you clarified requirements, stayed calm, and gave progress updates. Sample answer: A stakeholder wanted a report urgently, but the source data was incomplete. I clarified the exact need, delivered a smaller first version, and then improved it after the data was fixed. The result was better trust and a usable report on time.

Why do you want to work as a Data Analyst?

Link your interest to problem solving, data quality, and business impact. Mention that you like converting data into decisions and communicating clearly with non technical teams. Sample answer: I enjoy finding patterns in data and turning them into practical actions. I also like working with business teams, because analysis is most useful when it leads to better decisions and measurable improvement.

How do you handle tight deadlines?

Show that you prioritize, communicate, and stay organized. Mention that you break work into must have and nice to have items, confirm dependencies early, and update the team if a risk appears. Sample answer: I first identify the critical output, then I focus on the most important tables, checks, and visuals. If there is a risk, I inform the team early and suggest a phased delivery.

Your last 48 hours before the interview

  1. Revise core SQL concepts, especially joins, filtering, aggregation, and window functions.
  2. Practise explaining one project clearly, including the business problem, data source, cleaning steps, and result.
  3. Review Excel formulas you use often, such as XLOOKUP, INDEX MATCH, SUMIFS, COUNTIFS, and TRIM.
  4. Open one dashboard you built and rehearse why each chart, filter, and KPI is there.
  5. Prepare short answers for common behavioural questions using Situation, Task, Action, Result.
  6. Do one timed mock session where you answer out loud in 60 to 90 seconds per question.

Common mistakes to avoid

Frequently asked questions

What SQL questions are asked in an Infosys Data Analyst interview?

Candidates commonly report questions on joins, aggregation, window functions, filtering, ranking, and query logic. You should also be ready to explain how you would verify results and handle messy data. Interviewers often prefer clear reasoning over memorized syntax.

Do I need advanced Power BI or Tableau skills for Infosys?

Usually you need solid reporting and dashboard basics, plus the ability to explain measures, filters, and visuals. You should know how to build a clean report, choose the right chart, and make the output easy for business users to read. Deep development is helpful, but practical understanding matters most.

How should I answer case based questions?

Start with the business goal, then state the data you would need, the checks you would perform, and the output you would deliver. Keep the answer organized and focused on decisions, not only tools. Interviewers usually want to see how you think, not just whether you know formulas.

What is the best way to prepare in two days?

Focus on SQL, Excel, dashboards, statistics, and one or two strong project stories. Practise answering out loud in short, clear sentences and review your own work for business impact. A small number of well understood examples is usually better than trying to cover too many topics at once.

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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 Infosys.

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