36 practice questions with answers for Business Analytics interviews in Indore.
Business Analytics jobs in Indore
Indore is one of central India's fastest-growing IT hubs, with IT-services campuses and product start-ups in its Super Corridor and IT parks. Companies here hire many freshers and value hands-on project work.
Below are 36 questions that match the mix of service, product and domain employers hiring business analysts in Indore.
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A defect is logged as New with steps, expected and actual results, and evidence. It is reviewed in triage and moves to Open or Assigned, or to Rejected, Duplicate or Deferred. The developer fixes it and marks it Fixed or Ready for retest. The tester retests: if it passes it moves to Closed, and if not it is Reopened. Tracking status and age helps the UAT lead report readiness and spot defects stuck too long.
02
Guesstimate: how many cups of tea are sold in Delhi per day?
Population about 20 million, adult tea drinkers about 50%, cups bought outside per person around 1 on average. This gives roughly 10 million cups, then adjust for offices and stalls.
03
Users in a shared Excel tracker keep typing region names with different spellings. How do you stop this?
Use Data Validation with a List rule. Keep the allowed regions in a separate sheet as an Excel Table, name it, and set the validation source to that range so the dropdown grows when you add a region. Turn on an error alert so free text is rejected. Then clean existing entries once with Find and Replace or a mapping lookup. For stronger control, protect the sheet and unlock only the input cells, so the list cannot be edited by mistake.
04
What is the difference between gross margin and net margin?
Gross margin is revenue minus cost of goods sold, divided by revenue, and shows how profitable the product itself is. Net margin is net profit after all expenses, including salaries, rent, marketing, interest and tax, divided by revenue. A company can have a healthy 60 percent gross margin but a negative net margin if it overspends on marketing or overheads, which tells you where to look for fixes.
05
Tell me about yourself, for a business analyst role.
Keep it to about 90 seconds in a present, past, future flow. For example: I am a commerce graduate working as an analyst intern, where I build Excel and Power BI reports and write SQL queries for the sales team. Earlier, my college project analysed customer churn for a local gym and recommended changes they adopted. I want to grow as a business analyst because I enjoy turning business problems into clear requirements and data-driven decisions.
06
Monthly subscription churn jumped from 3 percent to 5 percent. How do you investigate?
Confirm the data first: definition changes, failed-payment handling or a billing date shift. Then segment churn by plan, tenure, acquisition channel, city and device to find where it concentrates. Separate voluntary cancellations from involuntary card failures. Look at events before the jump, like a price change, app release or competitor offer, and read cancellation reasons. Recommend targeted fixes, such as payment retries or win-back offers, and track the affected cohort.
07
What is an issue tree and how does a hypothesis-driven approach work?
An issue tree breaks the main question into smaller, MECE sub-questions until each can be answered with data, such as 'why are profits down?' into revenue and cost branches. A hypothesis-driven approach starts with a likely answer, for example 'profit fell because delivery costs rose', and uses the tree to decide which data proves or disproves it first. It focuses effort and keeps the case structured and fast.
08
A business head wants 25 charts on one dashboard page. How do you respond?
Ask what decisions they make weekly and which three to five KPIs drive them. Propose a summary page with those KPIs, trends and one breakdown, then drill-through or separate pages for detail. Show a quick mock-up of both versions so they see the clutter and the load time. Use bookmarks or a field parameter to let them switch views without adding charts. Agree on the layout before building.
09
A manager says the dashboard total does not match the finance team's Excel sheet. What do you do?
First agree on the definition: date range, gross or net, tax, returns, currency and which date (order or invoice) is used. Then reconcile at a small grain, such as one month and one region, comparing row counts and sums between the source query and the sheet. Common causes are filters on the page, missing relationships, duplicate rows after a join or a late refresh. Document the agreed definition in the report tooltip.
10
Your measure shows the same value on every row of a matrix. Why might that happen?
The filter from the row field is not reaching the fact table. Usually there is no relationship between that dimension and the fact, the relationship is inactive, or it filters in the wrong direction. It can also happen when the measure uses ALL or REMOVEFILTERS on that column, or when the row field comes from the fact table of a different grain. Check the model view and test the measure with a simple SUM.
11
What is a foreign key and what is referential integrity?
A foreign key is a column in one table that refers to the primary key of another, such as orders.customer_id pointing to customers.customer_id. Referential integrity means every foreign key value must exist in the parent table, so you cannot have an order for a customer who does not exist. The database enforces it on insert, update and delete, which keeps joins reliable for reporting.
12
Write Excel formulas for IRR with yearly cash flows and XIRR with irregular dates.
# Yearly cash flows in B2:B7, year 0 investment negative
=IRR(B2:B7)
# Irregular dates: cash flows in B2:B7, dates in C2:C7
=XIRR(B2:B7, C2:C7)
# XIRR returns an annualised rate based on actual dates,
# which suits SIP returns or projects with uneven payments.
13
A KPI on your dashboard dropped 40 percent overnight. What are your first steps?
Assume a data problem until proven otherwise, because real businesses rarely move 40 percent in a day. Check whether the refresh completed, whether source row counts look normal, and whether any tracking, pipeline or definition changed. Compare with a raw source query and a related metric, such as orders versus payments. If the data is fine, segment by channel, region and platform to locate the drop, then alert the owners quickly.
14
Finance asks you to build a monthly cohort retention table in Excel from raw order data. How do you approach it?
Add a helper column for each customer's first order month using MINIFS on customer ID, and another for the order month. Compute the month index as the difference in months between them. Then build a PivotTable or COUNTIFS grid with cohort month as rows, month index as columns and distinct customers as values. Divide each cell by the month-zero count to get retention percentages and add a colour scale to show decay.
Given a cart of 1,200 rupees and a valid coupon SAVE10 with a minimum order of 1,000 rupees, when the user applies it, then 10 percent is deducted and the new total is shown. Given an expired coupon, when applied, then the message 'This coupon has expired' appears and the total is unchanged. Given a cart below the minimum, when applied, then the user is told how much more to add.
17
Write a SQL query to get each customer's first order date and first order amount.
WITH ordered AS (
SELECT customer_id, order_date, amount,
ROW_NUMBER() OVER (PARTITION BY customer_id
ORDER BY order_date, order_id) AS rn
FROM orders
)
SELECT customer_id, order_date AS first_order_date,
amount AS first_order_amount
FROM ordered
WHERE rn = 1;
Understand the real need first: what decision is it for and what is the minimum that helps tomorrow? Offer a phased answer, such as a quick directional view with the top three numbers tomorrow, clearly labelled with caveats, and the full validated report in a week. Explain the trade-off between speed and accuracy. Confirm the agreed plan in writing so expectations are clear.
20
Describe a time you recommended delaying a go-live.
Situation: two days before the go-live of a loyalty points system, UAT showed points were doubled for refunded orders. Task: give a clear recommendation at the go or no-go meeting. Action: I presented the defect, estimated financial exposure at about 6 lakh rupees a month and showed the fix needed three days including regression. Result: the sponsor agreed to a one-week delay. The release went live cleanly, and the sponsor later cited the decision as an example of good risk management.
21
What is the profit equation and how do you use it in cases?
WITH per_customer AS (
SELECT customer_id, COUNT(DISTINCT order_id) AS orders
FROM orders
GROUP BY customer_id
)
SELECT
ROUND(100.0 * SUM(CASE WHEN orders >= 2 THEN 1 ELSE 0 END)
/ COUNT(*), 2) AS repeat_rate_pct
FROM per_customer;
23
Your AS-IS map of a loan approval process shows 14 handoffs between teams. How do you identify improvements?
First measure each handoff: waiting time, rework rate and volume, using system timestamps where possible. Then classify steps as value-adding, required for compliance or waste. Look for patterns: repeated approvals, information re-entered in two systems, work bouncing back for missing documents. Typical fixes are merging roles, adding a checklist at intake so applications arrive complete, parallelising checks and automating rule-based approvals. Quantify the expected reduction in cycle time for each option.
Situation: regional sales heads reviewed discount spend only at month end. Task: I was asked to give weekly visibility. Action: I built a Power BI report linking discounts to margin by product and region, with a drill-through to deal level and an alert when margin fell below target. Result: the team spotted two regions giving deep discounts on low-margin items, tightened approval rules, and margin improved by about two points the next quarter.
26
In UAT cycle 2, a feature that passed in cycle 1 is now broken after a defect fix. What does this tell you and what should change?
It is a regression: the fix for one defect broke existing functionality, which usually means changes were not impact-analysed and there is no regression suite. Log it as a new high-priority defect linked to the fix. Agree with the team that every UAT build comes with release notes listing the changes, and that QA runs an automated or core manual regression pack before handing the build to business testers. Also add the broken flow to the UAT regression checklist.
XLOOKUP can look left or right, uses exact match by default, returns a custom value if nothing is found and doesn't break when columns move. VLOOKUP only looks right and needs a column number.
28
A new onboarding flow increased sign-ups by 15 percent, but Day-7 retention fell. How do you analyse this?
Check whether the extra sign-ups are lower-intent users who would naturally retain less. Compare Day-7 retention for comparable users in both versions and count retained users in absolute terms, not just rates. If the new flow skips a step that led users to the aha moment, retention per user may truly fall. The decision depends on whether total retained, valuable users went up or down.
29
Write a SQL query to find requirements that have no linked UAT test case.
SELECT r.req_id, r.title, r.priority
FROM requirements r
LEFT JOIN test_case_links l ON l.req_id = r.req_id
WHERE l.req_id IS NULL
AND r.status = 'APPROVED'
ORDER BY r.priority;
-- Run this before UAT starts: every approved requirement
-- should trace to at least one test case.
30
Tell me about a time you found an error in a spreadsheet just before it went to management.
Situation: an hour before a quarterly review I noticed regional totals were higher than the company total. Task: find the issue without delaying the meeting. Action: I traced it to a SUMIFS range that stopped at row 5000 while new data went beyond it, plus one duplicated region. I fixed both, converted the data to an Excel Table, and added a check cell comparing totals. Result: the correct deck went out on time and the check became part of our template.
31
What is a data dictionary and why does a business analyst maintain one?
A data dictionary is a catalogue of data elements used in a system or report: field name, business definition, data type, length, allowed values, mandatory or optional, source system, owner and example values. A BA maintains it so business users, developers and testers use one definition, for example what counts as an active customer. It prevents mapping errors in integrations and migrations, speeds up testing and reduces disputes about why reports do not match.
32
What is the difference between OLTP and OLAP systems?
A single KPI can be gamed, so I would propose one headline with guardrails. The headline could be first-contact resolution rate, because it reflects solving problems, not just closing tickets. Guardrails would be customer satisfaction score after the ticket and median first response time. I would also watch ticket volume per thousand orders, which shows whether product issues are falling. Review targets quarterly with the support head.
34
What is a spike in Agile and when would a business analyst request one?
A spike is a time-boxed story used for research or experimentation to reduce uncertainty, not to deliver a feature. Its output is knowledge, such as a recommendation or a prototype. A BA might request one when the team cannot estimate a story because an external API, a data source or a regulation is unclear, for example checking whether a payment gateway supports partial refunds. The time box, often one to three days, prevents open-ended investigation.
35
Prepare a simple cost-benefit analysis for automating invoice processing.
Costs: software 12 lakh in year 1 plus 3 lakh per year support, and 4 lakh for implementation and training. Benefits: 60,000 invoices a year at 10 minutes saved each is 10,000 hours; at 400 rupees per hour that is 40 lakh, plus around 5 lakh from fewer late-payment penalties. Year-1 net benefit is 45 - 16 = 29 lakh and payback is under six months. Then test sensitivity, for example if only half the time saving is realised.
Stakeholders and the sponsor review the Business Requirements Document for completeness and accuracy, and the business owner gives formal sign-off before design begins.
Which companies hire Business Analytics professionals in Indore?
Companies with large offices in Indore include YASH Technologies. Use their company pages below to practise employer-specific sets.
Are Business Analytics interviews in Indore different from other cities?
The questions depend more on the company than the city. Indore's mix of employers decides the style: Companies here hire many freshers and value hands-on project work
How do I find Business Analytics jobs in Indore?
Shortlist companies with Indore offices, keep your CV focused on Business Analytics projects, apply on company career pages and job portals with the Indore filter, and practise the questions on this page before each interview.