36 practice questions with answers for Business Analytics interviews in Nagpur.
Business Analytics jobs in Nagpur
Nagpur's MIHAN SEZ hosts IT-services and BFSI delivery centres, giving central India a steady market for data and QA roles. Interviews are usually service-company style, with aptitude, technical and HR rounds.
Below are 36 questions that match the mix of service, product and domain employers hiring business analysts in Nagpur.
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Before: agree scope and process boundaries, invite people who actually do the work, not only managers, and collect existing documents and sample cases. During: state the goal, map the happy path first on a wall or digital board, then add exceptions, pain points, handoffs and volumes, and park off-topic issues. Keep timing visible. After: convert the output to a clean BPMN diagram within two days, circulate it for validation, and record open questions with owners and dates.
Story points measure relative effort, complexity and uncertainty compared with a reference story, using a scale like 1, 2, 3, 5, 8. People are better at comparing sizes than predicting exact hours, and points do not depend on who does the work. Over a few sprints the team's velocity, points completed per sprint, makes forecasting reliable. Points should never be used to compare productivity across teams.
08
How would you size the market for IT courses in Delhi NCR?
Top-down: NCR population aged 18–30 × share of graduates × share wanting paid upskilling × average fee. Cross-check bottom-up with institutes × batches × students × fees. State your assumptions.
A star schema has one central fact table holding numeric events (sales, orders) linked to surrounding dimension tables (date, product, customer, region). BI tools prefer it because filters flow cleanly from dimensions to facts, DAX and Tableau calculations stay simple, and compression and query performance improve. A flat single table repeats text values and gets slow, while a snowflake with many chained lookups makes filtering and maintenance harder.
12
A release passed all system testing, but business users reject it during UAT. What went wrong and what do you do?
The team built what was written, but not what users needed, which points to gaps in elicitation, missing real-world scenarios or users not involved early. Capture each rejection and classify it as a defect, a missed requirement or a new request. Prioritise blockers with the product owner and agree on a fix plan and date. Going forward, involve users in demos every sprint and base UAT scenarios on real workflows.
13
Write a SQL query to calculate the DAU to MAU stickiness ratio for a month.
WITH daily AS (
SELECT event_date, COUNT(DISTINCT user_id) AS dau
FROM events
WHERE event_date >= '2026-10-01' AND event_date < '2026-11-01'
GROUP BY event_date
),
monthly AS (
SELECT COUNT(DISTINCT user_id) AS mau
FROM events
WHERE event_date >= '2026-10-01' AND event_date < '2026-11-01'
)
SELECT ROUND(AVG(d.dau) * 1.0 / MAX(m.mau), 3) AS stickiness
FROM daily d CROSS JOIN monthly m;
14
Three departments describe the same order process in three different ways during workshops. How do you arrive at the true AS-IS?
Treat each version as a hypothesis. Walk the process physically or observe real cases end to end, and pull a sample of 20 to 30 recent orders from the system to trace what actually happened. Compare timestamps and status changes with each department's story. Then hold a joint session, show the evidence-based map and mark the variants openly. Often all three are partly right because different order types follow different paths, which should be modelled explicitly.
15
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.
16
Write SQL checks to validate a customer data migration between the legacy and new systems during UAT.
-- 1. Row counts should match
SELECT
(SELECT COUNT(*) FROM legacy.customers) AS legacy_rows,
(SELECT COUNT(*) FROM target.customers) AS target_rows;
-- 2. Records missing in the target
SELECT l.customer_id
FROM legacy.customers l
LEFT JOIN target.customers t ON t.customer_id = l.customer_id
WHERE t.customer_id IS NULL;
-- 3. Financial totals should reconcile
SELECT SUM(outstanding_balance) FROM legacy.customers;
SELECT SUM(outstanding_balance) FROM target.customers;
17
Guesstimate: how many laptops are sold in India each year?
Segment by buyer. Households: about 30 crore households, roughly 15 percent own a laptop, so 4.5 crore laptops, replaced every 5 years, gives about 90 lakh a year, plus around 20 lakh first-time student buyers. Businesses: assume 4 crore office workers using laptops, replaced every 4 years, giving 1 crore. Government and education schemes add around 10 lakh. Total is about 2.2 crore. Sanity check against industry trends and give a range of 1.5 to 2.5 crore.
A short requirement written as 'As a user, I want X so that Y', backed by acceptance criteria. Good stories follow INVEST: independent, negotiable, valuable, estimable, small and testable.
Send an agenda with the goal and the decisions needed beforehand, along with any pre-read. Invite only people who contribute or decide. Start by restating the goal, keep to time, park off-topic issues and confirm decisions aloud. End by summarising actions with owners and dates. Send minutes within a day. A meeting without a clear decision or output usually could have been an email.
Log the change, assess impact on scope, cost and timeline, get approval through change control or backlog grooming, and update documents and stakeholders.
Horizontal analysis compares line items across periods, showing growth, for example revenue up 18 percent year on year while employee costs grew 30 percent. Vertical analysis expresses each item as a percentage of a base within one period, such as each expense as a percentage of revenue, or each asset as a percentage of total assets. Together they show both trends and structure, and vertical analysis also makes companies of different size comparable.
25
Daily active users dropped 10 percent week over week. How do you investigate?
Rule out data issues first: tracking changes, app release bugs, pipeline delays or bot filters. Check whether the drop is seasonal by comparing with the same week last year or a festival calendar. Then segment by platform, app version, country or city, acquisition channel and new versus returning users to locate it. Look at the funnel for the core action. Connect findings to releases, outages or marketing changes, then recommend fixes.
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;
28
What is a change request and how does change control work?
A change request is a formal proposal to modify agreed scope, requirements, timeline or budget. In change control, the request is logged, the BA analyses impact on effort, cost, schedule, risk and other requirements, and a decision body such as the sponsor or change board approves, rejects or defers it. Approved changes update the requirements, plan and traceability. In Agile, most changes go through backlog reprioritisation instead.
29
Compare Import mode, DirectQuery and Live Connection in Power BI.
Import copies data into the compressed in-memory model, giving the fastest visuals and full DAX, but data is only as fresh as the last refresh and size is limited. DirectQuery sends queries to the source at view time, so data is near real time but visuals are slower and some DAX is restricted. Live Connection points to an existing published semantic model or Analysis Services model without its own model. Composite models mix Import and DirectQuery.
30
What are Excel Tables (Ctrl+T) and why should analysts use them?
An Excel Table turns a range into a named, structured object. It expands automatically when rows are added, so formulas, charts, PivotTables and Power Query sources pick up new data without range edits. It supports structured references like =SUM(Sales[Amount]), calculated columns that fill down automatically, built-in filters, banded formatting and a total row. Tables make reports far less error-prone than fixed ranges like A2:F5000.
31
Push notifications increased weekly engagement, but app uninstalls also rose. What do you recommend?
Quantify both effects: extra sessions and revenue from notifications versus users lost through uninstalls and notification opt-outs, including their lifetime value. Segment by notification type and frequency to find which ones annoy users. Recommend frequency caps, personalised timing, relevance rules and easy preference settings, then test them with uninstall rate and opt-out rate as guardrails. Short-term engagement should not cost long-term users.
32
What are unit economics and why do investors and leaders focus on them?
Unit economics measure revenue and cost for one unit of business, such as one order, one customer or one subscription. For an order you compute average order value minus product cost, delivery, payment fees, discounts and support cost to get contribution margin. If each unit loses money, scale only increases losses. Leaders use unit economics to decide pricing, which cities or channels to grow and where to cut cost.
33
What is Customer Acquisition Cost (CAC) and what is CAC payback period?
CAC is total sales and marketing spend in a period divided by new customers acquired in that period. If you spend 10 lakh and gain 2,000 customers, CAC is 500 rupees. CAC payback period is how many months of gross profit from a customer it takes to recover that CAC. A shorter payback means the business can reinvest faster; many subscription businesses aim for under 12 months.
34
Tell me about a time careful listening helped you uncover a hidden requirement.
Situation: during interviews for a new order system, a warehouse supervisor kept mentioning that Friday evenings were chaotic. Task: understand whether this mattered for the requirements. Action: instead of moving on, I asked what happened on Fridays and learned that bulk orders were split manually because of truck capacity limits. Result: we added an automatic order-splitting rule that nobody had listed, which saved the team about four hours a week and avoided a likely UAT failure.
35
How would you prioritise 10 features with a limited budget?
Score them with RICE or value-vs-effort, align with goals, consider dependencies and risks, validate with stakeholders, then use MoSCoW for the release plan.
36
How do you calculate cycle time, touch time and process efficiency? Give an example.
Cycle time (lead time) is the total elapsed time from the start to the end of a case. Touch time is the time someone actually works on it. Process cycle efficiency is touch time divided by cycle time. Example: a refund takes 5 working days (40 working hours) end to end, but the agents spend only 2 hours in total working on it. Efficiency is 2 / 40 = 5 percent, so 95 percent of the time is waiting, and queues are the main target.
Which companies hire Business Analytics professionals in Nagpur?
Companies with large offices in Nagpur include Persistent Systems, GlobalLogic. Use their company pages below to practise employer-specific sets.
Are Business Analytics interviews in Nagpur different from other cities?
The questions depend more on the company than the city. Nagpur's mix of employers decides the style: Interviews are usually service-company style, with aptitude, technical and HR rounds
How do I find Business Analytics jobs in Nagpur?
Shortlist companies with Nagpur offices, keep your CV focused on Business Analytics projects, apply on company career pages and job portals with the Nagpur filter, and practise the questions on this page before each interview.