36 practice questions with answers for SQL interviews in Indore.
SQL 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 analyst (sql)s in Indore.
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01
Join three tables to get total sales by product category.
SELECT cat.category_name,
SUM(oi.quantity * oi.unit_price) AS revenue
FROM order_items oi
JOIN products p ON oi.product_id = p.product_id
JOIN categories cat ON p.category_id = cat.category_id
GROUP BY cat.category_name
ORDER BY revenue DESC;
Join from the most detailed table outward and aggregate at the end.
02
Write a query for monthly revenue for the current year.
SELECT EXTRACT(MONTH FROM order_date) AS month,
SUM(amount) AS revenue,
COUNT(DISTINCT customer_id) AS buyers
FROM orders
WHERE order_date >= DATE '2025-01-01'
AND order_date < DATE '2026-01-01'
GROUP BY EXTRACT(MONTH FROM order_date)
ORDER BY month;
A date range in WHERE keeps an index on order_date usable.
03
What is the difference between FULL OUTER JOIN and UNION of LEFT and RIGHT joins?
A FULL OUTER JOIN returns matched rows plus unmatched rows from both sides in one operation. MySQL does not support it, so it is emulated with a LEFT JOIN UNION a RIGHT JOIN, or LEFT JOIN UNION ALL a RIGHT JOIN filtered to unmatched rows. Using plain UNION removes duplicates but can also remove genuinely repeated rows, so the UNION ALL pattern is safer.
In standard SQL, GROUP BY and HAVING are evaluated before SELECT, so aliases are not available there. MySQL and PostgreSQL allow aliases in GROUP BY, and MySQL allows them in HAVING, but SQL Server does not. For portable code, repeat the expression or wrap the query in a subquery or CTE and filter on the alias in the outer query.
05
Get the top 2 highest paid employees in each department.
WITH r AS (
SELECT emp_id, name, department_id, salary,
ROW_NUMBER() OVER (
PARTITION BY department_id ORDER BY salary DESC
) AS rn
FROM employees
)
SELECT * FROM r WHERE rn <= 2;
Use DENSE_RANK instead of ROW_NUMBER if tied salaries should all be included.
06
Tell me about a time you used advanced SQL to solve a business problem.
Situation: the product team wanted to know where users dropped off in the onboarding flow. Task: build a funnel from raw event logs. Action: I used window functions to order events per user, LEAD to find the next step and time taken, and grouped the results into a funnel with conversion rates. Result: we found a 40 percent drop at KYC upload, and the redesign improved completion by 15 percent.
07
Tell me about a time you automated a manual data task with SQL.
Situation: the operations team spent four hours every Monday merging Excel files for a weekly report. Task: reduce the effort. Action: I loaded the files into staging tables, wrote SQL with joins and aggregations to produce the report, and scheduled it as a job. Result: the report was ready automatically at 8 AM, saving about 16 hours a month and removing copy-paste errors.
08
What is GROUP BY and what is the rule for selected columns?
GROUP BY groups rows that share values in specified columns so aggregates can be computed for each group. Every column in SELECT must either be in GROUP BY or inside an aggregate function. SELECT city, COUNT(*) FROM customers GROUP BY city is valid, but adding name without aggregating it is an error in standard SQL, though older MySQL modes allowed it.
09
A business user needs a dashboard on a complex 6-table join that runs slowly. Would you use a view or a materialised view?
A normal view only simplifies the query; it still runs the full join every time, so performance does not improve. If the data can be a few minutes or hours old, a materialised view or summary table refreshed on schedule gives fast reads. If real-time data is required, tune the underlying query with indexes or build an incrementally maintained table.
10
Why is NOT IN dangerous when the subquery contains NULL?
If the subquery returns any NULL, value NOT IN (list) becomes unknown for every row, because comparing with NULL is unknown, so the query returns no rows. For example, NOT IN (SELECT manager_id FROM employees) fails when a manager_id is NULL. Use NOT EXISTS or filter out NULLs in the subquery to get correct results.
Situation: after college I knew only basic SELECT queries. Task: become interview-ready for data roles. Action: I solved two practice problems daily, read execution plans for my own queries, revised window functions weekly and built a small project analysing public sales data in PostgreSQL. Result: within three months I could solve medium-level problems confidently, and I continue practising regularly.
An execution plan shows how the database will run a query: which tables are scanned or seeked, which indexes are used, the join algorithms, sort and aggregate steps, and estimated row counts and costs. Use EXPLAIN in MySQL and PostgreSQL, EXPLAIN ANALYZE for actual timing, and the estimated or actual plan in SQL Server. Reading plans is the first step in tuning slow queries.
13
Your NOT IN query returns zero rows even though you expect results. What do you check?
Check whether the subquery returns any NULL values, because NOT IN with a NULL makes every comparison unknown. Run the subquery alone and look for NULLs. Fix it with NOT EXISTS, which handles NULLs correctly, or add WHERE column IS NOT NULL inside the subquery. Also confirm data types match so values compare as expected.
14
What is the CASE expression and where can it be used?
CASE adds conditional logic in SQL, returning a value based on conditions: CASE WHEN marks >= 60 THEN 'First' WHEN marks >= 45 THEN 'Second' ELSE 'Fail' END. It can be used in SELECT, WHERE, ORDER BY, GROUP BY and inside aggregates, for example SUM(CASE WHEN status = 'Paid' THEN amount ELSE 0 END) to pivot data. Conditions are checked in order and the first true one wins.
15
Your query WHERE manager_id <> 5 is not returning employees who have no manager. Why?
Employees with no manager have manager_id as NULL, and NULL <> 5 evaluates to unknown, not true, so those rows are excluded. Rewrite it as WHERE manager_id <> 5 OR manager_id IS NULL, or use COALESCE(manager_id, 0) <> 5. This three-valued logic with true, false and unknown causes many subtle bugs in reports and NOT IN subqueries.
16
Get the latest 3 orders for every customer using a lateral join.
SELECT c.customer_id, o.order_id, o.order_date
FROM customers c
CROSS JOIN LATERAL (
SELECT order_id, order_date
FROM orders
WHERE orders.customer_id = c.customer_id
ORDER BY order_date DESC
LIMIT 3
) o;
With an index on (customer_id, order_date), each lookup is fast. SQL Server uses CROSS APPLY with TOP 3.
17
Produce region subtotals and a grand total in one query.
SELECT COALESCE(region, 'All Regions') AS region,
COALESCE(city, 'Subtotal') AS city,
SUM(sales) AS sales
FROM store_sales
GROUP BY ROLLUP(region, city)
ORDER BY region, city;
In MySQL use GROUP BY region, city WITH ROLLUP. Use GROUPING() to label totals when real NULLs exist.
18
Write a query to pivot order counts by status into columns.
SELECT
customer_id,
SUM(CASE WHEN status = 'Delivered' THEN 1 ELSE 0 END) AS delivered,
SUM(CASE WHEN status = 'Cancelled' THEN 1 ELSE 0 END) AS cancelled,
SUM(CASE WHEN status = 'Returned' THEN 1 ELSE 0 END) AS returned
FROM orders
GROUP BY customer_id;
Conditional aggregation works in every database, unlike vendor-specific PIVOT syntax.
WHERE filters individual rows before grouping and cannot use aggregate functions. HAVING filters groups after GROUP BY and can use aggregates such as COUNT or SUM. For example, WHERE city = 'Pune' keeps Pune rows, and HAVING COUNT(*) > 5 keeps only groups with more than five rows. Filtering early with WHERE is also more efficient.
20
Compare this month's and last month's sales per product using a full outer join.
SELECT COALESCE(c.product_id, p.product_id) AS product_id,
COALESCE(c.sales, 0) AS this_month,
COALESCE(p.sales, 0) AS last_month
FROM cur_month c
FULL OUTER JOIN prev_month p
ON c.product_id = p.product_id;
Products sold in only one of the months still appear, with zero for the other month.
21
After joining orders with payments, revenue doubled. What went wrong?
Some orders have multiple payment rows, such as partial payments or retries, so each order row repeats and SUM(order amount) counts it multiple times. This is join fan-out. Fix it by aggregating payments per order in a subquery or CTE before joining, or summing order amounts from the orders table alone. Always check row counts before and after a join.
22
What is the difference between OLTP and OLAP databases?
OLTP systems handle many short transactions such as orders and payments, with normalised schemas, row-based storage and focus on fast inserts and updates. OLAP systems support analysis over large history, using denormalised star or snowflake schemas, columnar storage and heavy aggregations. A bank's core system is OLTP, while its data warehouse used for monthly reports is OLAP.
23
What is the difference between SUM with CASE and filtering with WHERE?
WHERE removes rows from the entire query, so all aggregates see only filtered data. SUM(CASE WHEN condition THEN amount END) applies the condition to one aggregate only, letting you calculate several conditional totals in one pass, such as paid and refunded amounts per customer. Some databases support the cleaner FILTER clause: SUM(amount) FILTER (WHERE status = 'Paid').
A natural key is a real-world identifier like PAN number, email or product code. A surrogate key is a system-generated value, usually an integer or UUID, with no business meaning. Surrogate keys are stable, compact and good for joins, while natural keys can change or be long. A common design uses a surrogate primary key plus a unique constraint on the natural key.
25
What is the difference between a join and a union?
A join combines columns from different tables side by side based on a matching condition, making rows wider. A union stacks results of queries with the same column structure vertically, making the result longer. Use a join to bring customer names next to orders, and a union to combine 2024 and 2025 order tables into one list.
26
A recursive CTE on a category tree runs forever. What is the likely cause and fix?
The data probably has a cycle, such as category A as parent of B and B as parent of A, so recursion never ends. Add a depth column and stop at a maximum level, track a path string or array and exclude nodes already visited, and use database limits such as MAXRECURSION in SQL Server. Then fix the cyclic data at the source with constraints or validation.
A SARGable (Search ARGument able) predicate lets the optimiser use an index seek. Wrapping an indexed column in a function, such as WHERE YEAR(order_date) = 2025 or WHERE LOWER(email) = 'x', usually prevents index use. Rewrite as WHERE order_date >= '2025-01-01' AND order_date < '2026-01-01'. Leading wildcards and implicit type conversions also make predicates non-SARGable.
28
How would you design data archiving for a table growing by 10 million rows a month?
Partition the table by month so old partitions can be detached or moved to an archive table or cheaper storage without heavy deletes. Define a retention policy with business and compliance teams, for example 24 months online. Keep archived data queryable through a separate schema or warehouse, update indexes and statistics, and automate the process with monitoring and alerts.
29
What is a window frame and what is the default frame?
A frame defines which rows around the current row are included, such as ROWS BETWEEN 2 PRECEDING AND CURRENT ROW for a 3-row moving average. When ORDER BY is present and no frame is specified, the default is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which produces a running total but includes all ties of the current value. Without ORDER BY, the frame is the whole partition.
30
Average order value looks too low in a report. What could be wrong?
Check the grain: if the query averages order items instead of orders, each line counts separately and the average drops. Joins can also duplicate rows. Verify whether cancelled or zero-value orders are included and how NULL amounts are treated. Compute SUM(amount) / COUNT(DISTINCT order_id) at order level and compare with business definitions before changing the report.
31
Describe a time you found and fixed a wrong number in a report.
Situation: a monthly dashboard showed 30 percent higher revenue than finance figures. Task: find the cause before the leadership review. Action: I traced the SQL, found a join to the shipments table that duplicated orders with split shipments, rewrote it with a pre-aggregated CTE and reconciled totals with finance. Result: numbers matched exactly and I added a row-count test to the report pipeline.
Constraints enforce rules on data: PRIMARY KEY for unique row identity, FOREIGN KEY for valid references, UNIQUE for no duplicates, NOT NULL for required values, CHECK for conditions like age >= 18, and DEFAULT for automatic values. They protect data quality at the database level, so bad data is rejected even if an application has a bug.
It depends on the database. SQL Server and MySQL usually inline CTEs like subqueries. PostgreSQL before version 12 always materialised CTEs, which could hurt performance; since version 12 non-recursive CTEs referenced once are inlined, and you can force behaviour with MATERIALIZED or NOT MATERIALIZED. Referencing a heavy CTE many times may cause repeated work, so check the plan.
34
What are dirty reads, non-repeatable reads and phantom reads?
A dirty read sees uncommitted changes from another transaction that may roll back. A non-repeatable read gets different values when reading the same row twice because another transaction updated and committed it. A phantom read gets a different set of rows for the same query because another transaction inserted or deleted matching rows. Higher isolation levels prevent more of these.
WITH m AS (
SELECT DATE_TRUNC('month', order_date) AS month,
SUM(amount) AS revenue
FROM orders GROUP BY 1
)
SELECT month, revenue,
ROUND(100.0 * (revenue - LAG(revenue) OVER (ORDER BY month))
/ NULLIF(LAG(revenue) OVER (ORDER BY month), 0), 2) AS mom_pct
FROM m ORDER BY month;
NULLIF avoids division by zero.
36
A reporting team wants to query the production OLTP database directly. What are the risks and alternatives?
Heavy analytical queries can lock rows, use CPU and slow customer transactions, and normalised schemas make reporting complex. Alternatives are a read replica for reporting, a data warehouse loaded by ETL or CDC with a star schema, or materialised summary tables. Grant read-only access with limits if direct access is unavoidable, and schedule heavy jobs off-peak.
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.
Companies with large offices in Indore include many IT services and product firms. Use their company pages below to practise employer-specific sets.
Are SQL 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 SQL jobs in Indore?
Shortlist companies with Indore offices, keep your CV focused on SQL projects, apply on company career pages and job portals with the Indore filter, and practise the questions on this page before each interview.