01
What is a CTE and why use it?
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A Common Table Expression is a named temporary result defined with WITH that makes complex queries readable and allows recursion.
Data Analytics Interview Questions in Indore
36 practice questions with answers for Data Analytics interviews in Indore.
Data 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 data analysts in Indore.
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02
Which KPIs would you track for an e-commerce app?
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DAU/MAU, conversion rate, average order value, cart abandonment, retention/churn, CAC, LTV, return rate and NPS.
03
Your NOT IN query unexpectedly returns zero rows. Why might that happen, and how do EXISTS and IN differ?
Show answer
IN checks whether a value is in a list or subquery result; EXISTS checks whether a subquery returns at least one row and stops at the first match. Results are the same in most cases, and modern optimisers often run them similarly. The big difference is NOT IN with NULLs: if the subquery returns any NULL, NOT IN returns no rows. NOT EXISTS behaves correctly, so prefer it for anti-joins.
04
Tell me about a time you found a mistake in a report after it had already been shared.
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Situation: a day after sending a weekly report, I noticed one region's numbers included test orders. Task: correct it before decisions were made. Action: I quantified the impact, a 3 percent overstatement, and emailed the same audience with the corrected figures, a short explanation and the fix I had added to prevent repeats. Result: my manager appreciated the quick ownership, and the test-order filter became part of our shared dataset.
05
Write Excel formulas to calculate ROAS and CPA for each campaign and flag campaigns below a ROAS target.
Show answer
-- B = Spend, C = Conversions, D = Revenue, target ROAS in H1
E2 (ROAS): =IFERROR(D2/B2, 0)
F2 (CPA): =IF(C2=0, "No conversions", B2/C2)
G2 (Flag): =IF(E2<$H$1, "Below target", "OK")
-- Copy down, then add conditional formatting on G to highlight 'Below target'
06
Tell me about a time you used data to challenge an assumption.
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Situation: our team believed weekend discounts drove most sales. Task: I was preparing the monthly review. Action: I compared discount and non-discount weekends over six months and controlled for paydays and festivals. Discounts moved sales forward from the following week but added little overall. I presented it with one clear chart. Result: management trialled fewer discount weekends, and margin improved without a fall in monthly revenue.
07
Write SQL to calculate users, conversions and conversion rate for each test variant.
Show answer
SELECT
a.variant,
COUNT(DISTINCT a.user_id) AS users,
COUNT(DISTINCT o.user_id) AS converters,
ROUND(100.0 * COUNT(DISTINCT o.user_id)
/ COUNT(DISTINCT a.user_id), 2) AS conversion_pct
FROM experiment_assignments a
LEFT JOIN orders o
ON o.user_id = a.user_id
AND o.order_ts >= a.assigned_ts
WHERE a.experiment_id = 'checkout_v2'
GROUP BY a.variant;
08
Orders arrive in the warehouse with customer IDs that do not exist yet in the customer dimension. What do you do?
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.
09
Why does correlation not imply causation? Give a business example.
Show answer
Two variables can move together because of a third factor, reverse causation or pure chance. Example: stores with more staff have higher sales, but busy locations get more staff because they already sell more, so hiring alone may not raise sales. Ice-cream sales and AC sales both rise in summer because of temperature. To claim causation you need experiments, natural experiments or careful control of confounders.
10
What is incrementality testing in marketing?
Show answer
Incrementality testing measures sales that happened because of a campaign, compared with what would have happened anyway. You hold out a random group of users or a set of matched cities from the campaign and compare their conversions with the exposed group. Attribution tools often over-credit channels like retargeting and brand search, which reach people already likely to buy, so incrementality tests show the true lift and the true cost per incremental sale.
11
What is descriptive vs inferential statistics?
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Descriptive statistics summarise the data you have; inferential statistics use a sample to draw conclusions about a larger population.
12
Mean vs median vs mode — when do you use which?
Show answer
Mean for symmetric data without outliers, median for skewed data (salaries, house prices), mode for categories (the most common city).
13
What is a data mart?
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A data mart is a subset of the warehouse built for one department or subject, such as sales, finance or HR. It contains the facts and dimensions that team needs, often pre-aggregated and with business-friendly names. Marts make reporting faster and simpler for that team. Ideally they are built from the central warehouse using conformed dimensions, so the finance mart and the sales mart still agree on revenue.
14
Write a DAX measure for cumulative sales from the start of the data to the selected date.
Show answer
Cumulative Sales =
VAR maxDate = MAX('Date'[Date])
RETURN
CALCULATE(
[Total Sales],
FILTER(ALL('Date'[Date]), 'Date'[Date] <= maxDate)
)
-- for a running total that resets each year use TOTALYTD([Total Sales], 'Date'[Date])
15
Brand keyword ads show a ROAS of 15, and the team wants to double the budget. How do you respond?
Show answer
Brand search ROAS is usually inflated because people searching the brand name were already looking for you and would often click the free organic result anyway. Before increasing spend, I would propose an incrementality test, such as pausing brand ads in some matched cities or time periods and measuring the drop in total brand-search orders. The incremental ROAS is often far lower, so the extra budget may work better elsewhere.
16
How does the FILTER function work in Excel? Write a formula to list all North region orders.
Show answer
-- A2:D500 holds Order, Customer, Region, Amount
=FILTER(A2:D500, C2:C500="North", "No orders")
-- two conditions (AND) multiply the tests
=FILTER(A2:D500, (C2:C500="North")*(D2:D500>10000), "No orders")
-- OR conditions add the tests
=FILTER(A2:D500, (C2:C500="North")+(C2:C500="East"))
17
What is the difference between a t-test and a z-test?
Show answer
Both compare means. A z-test assumes the population standard deviation is known or the sample is large, so the normal distribution applies. A t-test estimates standard deviation from the sample and uses the t-distribution, which has heavier tails for small samples. In practice analysts mostly use t-tests: one-sample, independent two-sample (Welch's version if variances differ) or paired, for before-after measurements on the same users.
18
How do you calculate a rolling average?
Show answer
df['sales'].rolling(window=7).mean() gives a 7-period moving average, useful to smooth daily noise.
19
What is Row-Level Security?
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Rules that restrict data per user role, for example sales managers seeing only their region, defined with DAX filters and assigned in the Service.
20
What are indexes and when can they hurt?
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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.
21
What is Tableau and what are its main products?
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Tableau is a visual analytics tool for building interactive charts and dashboards by dragging fields onto shelves. Tableau Desktop is used to author workbooks, Tableau Prep cleans and shapes data, Tableau Server and Tableau Cloud host and share dashboards with security and scheduled refresh, and Tableau Public is a free version where work is saved publicly. Analysts usually build in Desktop and publish to Server or Cloud.
22
Organic search traffic fell 40% overnight. How do you investigate?
Show answer
First check whether it is a tracking problem: did the analytics tag break on some templates, did consent settings change, does server log or backend order data show the same fall? If the drop is real, check the search console for impressions and rankings, recent site releases such as changed URLs, missing redirects, noindex tags or robots.txt changes, and whether a search algorithm update or seasonal pattern matches. Then break the drop down by page group.
23
Write Python code to bootstrap a 95% confidence interval for the difference in revenue per user between two groups.
Show answer
import numpy as np
rng = np.random.default_rng(42)
control = df.loc[df.variant == 'A', 'revenue'].to_numpy()
treat = df.loc[df.variant == 'B', 'revenue'].to_numpy()
diffs = []
for _ in range(5000):
c = rng.choice(control, size=len(control), replace=True)
t = rng.choice(treat, size=len(treat), replace=True)
diffs.append(t.mean() - c.mean())
low, high = np.percentile(diffs, [2.5, 97.5])
print(f'95% CI for difference: {low:.2f} to {high:.2f}')
24
What is the difference between SUM and SUMX in DAX?
Show answer
SUM adds up a single column in the current filter context. SUMX is an iterator: it goes row by row over a table, evaluates an expression for each row, then sums the results. Use SUMX when the value must be computed per row first, for example SUMX(Sales, Sales[Qty] * Sales[Price]). Iterators are flexible but can be slower on very large tables, so storing a simple column is sometimes better.
25
Sales data from different countries mixes currencies and some weights are in grams while others are in kilograms. How do you handle it?
Show answer
Never add mixed units. Identify the unit for each row from a currency or unit column, or infer it from the source system. Convert to one standard, for example INR using a dated exchange rate table joined on transaction date, and kilograms using a conversion factor. Keep the original value and unit columns for audit. Document which rates were used, and flag rows where the unit could not be determined.
26
Write pandas code to calculate monthly revenue from an orders DataFrame.
Show answer
import pandas as pd
orders = pd.read_csv('orders.csv', parse_dates=['order_date'])
orders['revenue'] = orders['qty'] * orders['unit_price']
monthly = (
orders
.groupby(orders['order_date'].dt.to_period('M'))['revenue']
.sum()
.reset_index(name='revenue')
)
print(monthly)
27
What is broadcasting in NumPy?
Show answer
Broadcasting lets NumPy perform operations on arrays of different shapes without copying data, by virtually stretching the smaller array. For example, subtracting a 1D array of column means from a 2D array centres every column in one line: X - X.mean(axis=0). Shapes are compatible when trailing dimensions are equal or one of them is 1. It is a key reason vectorised code is much faster than Python loops.
28
What is bidirectional cross-filtering in Power BI and when is it risky?
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Normally filters flow from the one side to the many side, for example from Product to Sales. Bidirectional filtering lets filters also flow back, so a Sales filter can limit Product. It helps in some many-to-many or bridge-table cases. The risks are ambiguous filter paths, unexpected results and slower performance. Prefer single direction and use CROSSFILTER inside a specific measure when you need both directions only there.
29
Marketing wants to A/B test two email subject lines on a list of 2,000 subscribers. What do you advise?
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.
30
What is statistical significance vs practical significance?
Show answer
A result can be statistically significant yet too small to matter; always report effect size and business impact together with the p-value.
31
What is a holdout group and why do teams keep one?
Show answer
A holdout group is a small share of users, often 5-10%, kept out of a feature or of all marketing campaigns for a long time. Comparing them with everyone else shows the cumulative long-term impact, which individual short tests miss, and checks whether many small wins really add up. For example, a notification holdout shows whether push messages raise monthly retention or just shift activity earlier.
32
How do you detect and handle skewed data?
Show answer
Check histograms and skew(), then apply log, square-root or Box-Cox transforms, or use medians and robust statistics.
33
Tell me about a time a stakeholder rejected your first dashboard design.
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Situation: I built a Tableau operations dashboard, and the warehouse head said it was too complex to use on the floor. Task: make it useful for them. Action: I watched how supervisors worked, learned they needed three numbers on a tablet every hour, and rebuilt it with large KPI tiles and one drill-down. Result: daily usage went from a handful of users to every shift supervisor within two weeks.
34
What are the main dimensions of data quality?
Show answer
Common dimensions are accuracy, values reflect reality; completeness, required fields are present; consistency, the same fact matches across systems; validity, values follow formats and rules such as a 6-digit pin code; uniqueness, no unwanted duplicates; and timeliness, data is fresh enough for its use. Measuring these with simple checks, like percent missing or duplicate rate, turns vague complaints about bad data into fixable issues.
35
Tell me about a time you migrated or rebuilt reports in a new BI tool.
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Situation: our team moved 15 Excel and older BI reports into Tableau. Task: I owned the sales set. Action: I listed every metric with its definition, rebuilt the shared data source first, then the dashboards, and ran side-by-side number checks for two weeks with the old reports. I held short demos for users. Result: all reports went live with matching numbers, and refresh effort fell from a day to an automatic schedule.
36
What do CTR, CPC, CPA and ROAS mean in digital marketing?
Show answer
CTR, click-through rate, is clicks divided by impressions. CPC, cost per click, is spend divided by clicks. CPA, cost per acquisition, is spend divided by conversions such as orders or leads. ROAS, return on ad spend, is revenue from ads divided by ad spend, so a ROAS of 4 means 4 rupees of revenue per rupee spent. ROAS ignores product margin, so a high ROAS can still lose money.
Companies with offices in Indore (1)
Few big employers listed in Indore?
Many Indore candidates also apply to teams in Pune and to remote or hybrid roles. Practise the Pune set as well.
Frequently asked questions
Which companies hire Data Analytics professionals in Indore?
Companies with large offices in Indore include YASH Technologies. Use their company pages below to practise employer-specific sets.
Are Data 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 Data Analytics jobs in Indore?
Shortlist companies with Indore offices, keep your CV focused on Data Analytics projects, apply on company career pages and job portals with the Indore filter, and practise the questions on this page before each interview.
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