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Data Analytics Interview Questions in Pune

36 practice questions with answers for Data Analytics interviews in Pune.

Data Analytics jobs in Pune

Pune combines IT-services campuses in Hinjewadi and Kharadi with product, automotive and BFSI technology centres. It has a large mid-level job market for data and QA roles, and interviews are often practical and project-based.

Below are 36 questions that match the mix of service, product and domain employers hiring data analysts in Pune.

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What is the difference between extract filters and data source filters in Tableau?

TableauMedium

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Extract filters decide which rows go into the extract file at all, which reduces its size and speeds every view; filtered rows are simply not available. Data source filters apply to all worksheets using that data source, for live or extract, and are useful for security or scope, such as only the India business. Both act before context filters. Normal worksheet filters only affect one sheet.

Traffic suddenly doubled from one city, with near-zero engagement time and no conversions. What is happening and what do you do?

Web & Marketing AnalyticsMedium

Show answer

This is very likely bot or spam traffic, or a misfiring tag. Check the user agents, IP ranges, hostnames, screen resolutions and landing pages for that traffic. If it is bots, exclude it with filters or data segments in analytics and in your reporting layer, and inform the web team so they can block it. Then restate the affected dashboard numbers, because bots inflate sessions and pull down conversion rate.

You share a forecasting workbook and users keep overwriting formulas. How do you protect it?

ExcelMedium

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Separate input cells from calculation cells and colour inputs clearly. Unlock only the input cells through Format Cells, Protection, then protect the sheet so formulas cannot be edited, and optionally hide formulas. Add data validation on inputs to block wrong values such as negative quantities. Protect workbook structure so sheets cannot be deleted, keep a version history, and add a short instructions sheet so users know where to type.

After joining orders to payments, your revenue total doubles. What went wrong?

SQLMedium

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This is a join fan-out: an order has more than one matching payment row, for example split payments or retries, so each order line is repeated and sums are inflated. Check by counting rows per key on both sides. Fix it by aggregating payments to one row per order before joining, joining at the correct grain, or using the right key. Always compare row counts and totals before and after a join.

Orders arrive in the warehouse with customer IDs that do not exist yet in the customer dimension. What do you do?

Data Modelling & WarehousingMedium

Show answer

These are late-arriving dimensions. Do not drop the orders, or revenue will be understated. Common practice is to insert a placeholder customer row with the natural key and 'Unknown' attributes, link the order to it, and update that row when full details arrive. Alternatively map to a single Unknown member with key -1. Also monitor how many such rows appear daily, because a spike usually means a broken feed.

Explain the common marketing attribution models.

Web & Marketing AnalyticsMedium

Show answer

Attribution decides how credit for a conversion is shared across touchpoints. Last click gives all credit to the final touch, first click to the first one. Linear splits credit equally, time decay gives more to recent touches, and position-based gives most to first and last. Data-driven attribution uses an algorithm on your own paths to estimate each channel's contribution. Each model answers a different question, so state which one a report uses.

Marketing wants to A/B test two email subject lines on a list of 2,000 subscribers. What do you advise?

A/B Testing & ExperimentsMedium

Show answer

With 1,000 per group and a typical click rate of 3%, only a very large difference, roughly 70% relative or more, would be detectable, so a small real lift would look like noise. I would suggest testing on a larger send, pooling several campaigns, or using open-to-click rate with a bigger effect. If they still run it, report the confidence interval and treat the result as directional.

What does the IF function do and how do you nest it?

ExcelEasy

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IF returns one result if a test is true and another if false. Nest IFs for multiple outcomes, or use IFS for cleaner formulas.

What is an enterprise bus matrix?

Data Modelling & WarehousingHard

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A bus matrix is a planning grid with business processes as rows, such as orders, shipments and returns, and conformed dimensions as columns, such as date, customer, product and warehouse. A tick shows which dimensions each process uses. It helps prioritise which fact tables to build, shows which dimensions must be shared and conformed first, and gives leaders a one-page roadmap of the warehouse without technical detail.

What are parameters in Tableau and how do you use them?

TableauMedium

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A parameter is a single user-controlled value, such as a number, date or string, that is independent of the data. On its own it does nothing; you reference it in calculations, filters, reference lines or bins. Common uses are a Top N selector, a what-if growth rate, or a measure switcher where a CASE statement picks Sales, Profit or Quantity based on the parameter. Parameter actions let users set it by clicking a mark.

What is Power Query and why is it useful?

Power BIMedium

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An ETL tool inside Excel for importing, cleaning and shaping data with recorded steps that refresh automatically when the source changes.

What is data cleaning and why does it take so much of an analyst's time?

Data CleaningEasy

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Data cleaning means fixing or removing incorrect, incomplete, duplicated or inconsistent data so analysis is trustworthy. Real data comes from many systems and manual entry, so you meet typos, mixed formats, missing values and duplicates. Analysts often spend half or more of a project on it because every later chart and model depends on it. Wrong inputs give confident but wrong answers, which is worse than no answer.

What is the difference between OLTP and OLAP systems?

Data Modelling & WarehousingEasy

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OLTP systems run day-to-day operations, such as billing or order entry. They handle many small inserts and updates, use normalised tables and need fast single-row access. OLAP systems support analysis, scanning millions of rows to aggregate sales by month or region. They use denormalised star schemas, columnar storage and are mostly read-heavy. Analysts should query OLAP copies so heavy reports do not slow down the live application.

What are indexes and when can they hurt?

SQLMedium

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Indexes speed up lookups by keeping sorted pointers. They slow writes and use space, so index columns used in filters and joins, not every column.

Write Python code to calculate the sample size per group for a conversion test with a 4% baseline and a 10% relative lift.

A/B Testing & ExperimentsMedium

Show answer

from statsmodels.stats.power import NormalIndPower from statsmodels.stats.proportion import proportion_effectsize baseline = 0.04 target = baseline * 1.10 # 4.4% effect = proportion_effectsize(target, baseline) n = NormalIndPower().solve_power( effect_size=effect, alpha=0.05, power=0.8, alternative='two-sided' ) print(round(n)) # roughly 39,000 users per group

What are bookmarks and drill-through in Power BI?

Power BIMedium

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Bookmarks save a report view state for navigation; drill-through jumps to a detail page filtered to the item you picked.

Explain time intelligence functions.

Power BIMedium

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DAX functions like TOTALYTD, SAMEPERIODLASTYEAR and DATEADD compare periods; they need a proper continuous date table marked as a date table.

How do you handle errors like #N/A and #DIV/0!?

ExcelMedium

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Fix the root cause when possible, or wrap formulas with IFERROR or IFNA to return a clear fallback value.

What is a Data Table in Excel's What-If Analysis?

ExcelMedium

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A Data Table shows how a formula's result changes when one or two inputs vary. For example, place a loan EMI formula in a corner, list interest rates down the column and tenures across the row, then use What-If Analysis, Data Table to fill every combination. It is ideal for sensitivity analysis in pricing or budgeting. Large Data Tables slow recalculation, so set calculation to automatic except tables when needed.

What are table calculations in Tableau?

TableauMedium

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Table calculations are computed on the aggregated results already in the view, not on the underlying rows. Examples are running total, percent of total, difference from previous, rank and moving average. Their result depends on the direction and partition you set with Compute Using, for example table across or by specific dimensions. They are quick to add from Quick Table Calculation, but incorrect Compute Using settings are a frequent cause of wrong numbers.

What is the difference between a primary key and a unique constraint?

SQLEasy

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Both prevent duplicate values. A table can have only one primary key, it cannot contain NULLs, and it is the main identifier other tables reference through foreign keys. A table can have several unique constraints, for example on email and on PAN number, and most databases allow NULLs in a unique column. Use the primary key for the row identity and unique constraints for other business rules.

Tell me about a time you designed or improved a data model.

Data Modelling & WarehousingMedium

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Situation: our sales reports used five separate Excel extracts and numbers never matched. Task: build one reliable model. Action: I listed the business questions, fixed the grain at invoice line, built conformed date, product and branch dimensions and moved logic into SQL views, then rebuilt the Power BI reports on top. Result: refresh time dropped from 40 to 6 minutes and month-end reconciliation queries fell sharply.

What are additive, semi-additive and non-additive facts?

Data Modelling & WarehousingMedium

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Additive facts, like sales amount or quantity, can be summed across every dimension. Semi-additive facts, like account balance or stock on hand, can be summed across accounts or stores but not across time; for time you take the closing or average value. Non-additive facts, like percentages, ratios or unit prices, cannot be summed at all, so you store their components (profit and revenue) and calculate the ratio at query time.

What is the difference between pd.cut and pd.qcut?

Python for AnalysisEasy

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pd.cut bins values into intervals you define or into equal-width ranges, for example age groups 18-25, 26-35 and 36-50. pd.qcut bins by quantiles so each bin has roughly the same number of rows, for example dividing customers into spend quartiles. Use cut when business-defined boundaries matter and qcut when you want balanced groups such as deciles. Both return a categorical column you can group by.

What is the difference between a calculated table in DAX and a table created in Power Query?

Power BIMedium

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A Power Query table is built during data refresh using M, before data enters the model, and is compressed like any imported table. A DAX calculated table is computed after load from other model tables, using functions such as CALENDAR, SUMMARIZE or DISTINCT. Prefer Power Query for shaping and cleaning source data. Use calculated tables for model-dependent needs, such as a date table from existing data or a small what-if table.

How do you present insights to non-technical stakeholders?

Data StorytellingMedium

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Lead with the answer, use one simple chart per point, translate numbers into business impact (₹, %), avoid jargon and end with a clear recommendation and next step.

What is the difference between WHERE and HAVING?

SQLEasy

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WHERE filters rows before grouping. HAVING filters groups after GROUP BY and can use aggregates like SUM() or COUNT().

What is the logical order in which SQL executes a SELECT query?

SQLMedium

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Although written as SELECT first, a query is logically processed as FROM and JOIN, then WHERE, GROUP BY, HAVING, SELECT, DISTINCT, ORDER BY and finally LIMIT. This explains common errors: you cannot use a SELECT alias in WHERE because SELECT runs later, but you can use it in ORDER BY. It also explains why aggregates belong in HAVING, not WHERE, and why window functions cannot be filtered in the same query level.

How do you detect and handle skewed data?

Statistics and Case StudiesMedium

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Check histograms and skew(), then apply log, square-root or Box-Cox transforms, or use medians and robust statistics.

What is the difference between melt and pivot?

Python for AnalysisMedium

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melt converts wide data to long format; pivot converts long data to wide, and they are used to reshape data for analysis or charts.

How would you present the same churn analysis to the CEO and to the customer support team?

Data StorytellingMedium

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For the CEO, lead with the headline and money: churn rose 2 points, costing about 3 crore annually, mainly from one segment, with two recommended actions and their expected impact, all on one or two slides. For the support team, go deeper into drivers they control: ticket types, resolution times and specific customer pain points, with operational next steps and how progress will be tracked. Same data, different level and call to action.

Write a Tableau calculation to find each customer's first purchase date and flag new versus repeat orders.

TableauMedium

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// First Purchase Date { FIXED [Customer ID] : MIN([Order Date]) } // Order Type IF [Order Date] = [First Purchase Date] THEN 'New' ELSE 'Repeat' END // Cohort Month for retention analysis DATETRUNC('month', [First Purchase Date])

Write pandas code for a pivot table of sales by region and category with sum and count.

Python for AnalysisMedium

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import pandas as pd summary = pd.pivot_table( df, index='region', columns='category', values='sales', aggfunc=['sum', 'count'], fill_value=0, margins=True # adds an All row and column ) print(summary)

What is the difference between a data warehouse, a data lake and a lakehouse?

SQLMedium

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A data warehouse stores cleaned, structured data in modelled tables optimised for SQL reporting. A data lake stores raw data of any type, such as logs, JSON and images, cheaply in files, with structure applied when read. A lakehouse combines them: open table formats on lake storage add transactions, schemas and fast SQL on top of files. Analysts typically query the warehouse or the curated layer of a lakehouse.

How do you combine text from several cells with a separator in Excel?

ExcelEasy

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-- join first and last name with a space =TEXTJOIN(" ", TRUE, A2, B2) -- all products of one order in a single cell, comma separated =TEXTJOIN(", ", TRUE, FILTER(C2:C500, A2:A500=F2)) -- older method =A2 & " " & B2 -- TRUE in TEXTJOIN skips empty cells, which CONCAT and & do not

What are statistical power and minimum detectable effect (MDE)?

A/B Testing & ExperimentsMedium

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Power is the probability that the test detects a real effect of a given size, commonly set at 80%. The minimum detectable effect is the smallest lift you care about and can reliably detect with your sample size. Smaller MDEs, lower baseline rates and higher power all need more users. If you can only get 10,000 users a week, you may only be able to detect large lifts, which should shape what you test.

Companies with offices in Pune (57)

IT services

TCS

Data Analytics interview questions

40 questions
4 rounds

Mumbai, Chennai, Pune +2

Data Analytics Interview Questions in Pune

Data Analytics jobs in Pune

What is the difference between extract filters and data source filters in Tableau?

Traffic suddenly doubled from one city, with near-zero engagement time and no conversions. What is happening and what do you do?

You share a forecasting workbook and users keep overwriting formulas. How do you protect it?

After joining orders to payments, your revenue total doubles. What went wrong?

Orders arrive in the warehouse with customer IDs that do not exist yet in the customer dimension. What do you do?

Explain the common marketing attribution models.

Marketing wants to A/B test two email subject lines on a list of 2,000 subscribers. What do you advise?

What does the IF function do and how do you nest it?

What is an enterprise bus matrix?

What are parameters in Tableau and how do you use them?

What is Power Query and why is it useful?

What is data cleaning and why does it take so much of an analyst's time?

What is the difference between OLTP and OLAP systems?

What are indexes and when can they hurt?

Write Python code to calculate the sample size per group for a conversion test with a 4% baseline and a 10% relative lift.

What are bookmarks and drill-through in Power BI?

Explain time intelligence functions.

How do you handle errors like #N/A and #DIV/0!?

What is a Data Table in Excel's What-If Analysis?

What are table calculations in Tableau?

What is the difference between a primary key and a unique constraint?

Tell me about a time you designed or improved a data model.

What are additive, semi-additive and non-additive facts?

What is the difference between pd.cut and pd.qcut?

What is the difference between a calculated table in DAX and a table created in Power Query?

How do you present insights to non-technical stakeholders?

What is the difference between WHERE and HAVING?

What is the logical order in which SQL executes a SELECT query?

How do you detect and handle skewed data?

What is the difference between melt and pivot?

How would you present the same churn analysis to the CEO and to the customer support team?

Write a Tableau calculation to find each customer's first purchase date and flag new versus repeat orders.

Write pandas code for a pivot table of sales by region and category with sum and count.

What is the difference between a data warehouse, a data lake and a lakehouse?

How do you combine text from several cells with a separator in Excel?

What are statistical power and minimum detectable effect (MDE)?

Companies with offices in Pune (57)

TCS

Infosys

Wipro

Accenture

Cognizant

Capgemini

Deloitte

Amazon

Google

Microsoft

Oracle

Cisco

PhonePe

Mastercard

Barclays

HSBC

Tech Mahindra

IBM

KPMG

Mphasis

LTIMindtree

Persistent Systems

Hexaware

Coforge

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