36 practice questions with answers for SQL interviews in Nagpur.
SQL 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 data analyst (sql)s in Nagpur.
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01
Your GROUP BY query returns an error that a column is not in the group by clause. How do you fix it?
Each selected column must be grouped or aggregated. Decide what you need: add the column to GROUP BY if it defines the group, aggregate it with MIN, MAX or STRING_AGG if any or all values are acceptable, or remove it. If you need details of the top row in each group, use a window function such as ROW_NUMBER instead of GROUP BY.
02
Calculate a 7-day moving average of daily active users.
SELECT activity_date, dau,
ROUND(AVG(dau) OVER (
ORDER BY activity_date
ROWS BETWEEN 6 PRECEDING AND CURRENT ROW
), 1) AS dau_7d_avg
FROM daily_users
ORDER BY activity_date;
This assumes one row per day; fill missing dates with a calendar table first, or ROWS will span more than seven days.
03
Write an upsert that inserts a row or updates it if it exists.
PostgreSQL:
INSERT INTO inventory (sku, qty)
VALUES ('A100', 10)
ON CONFLICT (sku)
DO UPDATE SET qty = inventory.qty + EXCLUDED.qty;
MySQL:
INSERT INTO inventory (sku, qty) VALUES ('A100', 10)
ON DUPLICATE KEY UPDATE qty = qty + VALUES(qty);
SQL Server and others use MERGE. A unique key on sku is required.
04
What is the difference between putting a condition in ON versus WHERE in a LEFT JOIN?
In a LEFT JOIN, a condition in ON filters the right table before matching, so all left rows are still kept. A condition on the right table in WHERE runs after the join and removes rows where the right side is NULL, effectively turning it into an inner join. To get all customers with only their 2025 orders, put the date condition in ON.
05
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.
06
What is the difference between an index scan and an index seek?
An index seek navigates the B-tree directly to the matching keys, reading only the needed rows, which is efficient for selective filters. An index scan reads the whole index or a large range of it. A table scan reads every row. Scans are not always bad; for queries returning a large share of rows, a scan can be cheaper than many seeks.
07
What are referential actions such as ON DELETE CASCADE?
Referential actions define what happens to child rows when a parent row is deleted or updated. CASCADE deletes or updates children automatically, SET NULL sets the foreign key to NULL, SET DEFAULT uses the default value, and RESTRICT or NO ACTION blocks the change. CASCADE is convenient for dependent data like order items but risky on important data, because one delete can remove many rows.
Common types are INT, BIGINT and SMALLINT for whole numbers, DECIMAL or NUMERIC for exact values like money, FLOAT for approximate values, CHAR for fixed-length and VARCHAR for variable-length text, DATE, TIME, DATETIME or TIMESTAMP for dates, and BOOLEAN where supported. Choosing correct types saves space, improves performance and prevents errors such as storing amounts in FLOAT and getting rounding issues.
09
How do you read an EXPLAIN ANALYZE output in PostgreSQL?
EXPLAIN ANALYZE
SELECT * FROM orders WHERE customer_id = 101;
Read the tree from the innermost node outward. Check node types such as Seq Scan, Index Scan or Hash Join, compare estimated rows with actual rows, and look at actual time per node. Large estimate errors suggest stale statistics, and Seq Scan on a selective filter suggests a missing index.
10
Your team debates using UUIDs or auto-increment integers as primary keys. What do you advise?
Auto-increment integers are compact, fast to index and naturally ordered, but expose counts and are hard to generate across distributed systems. UUIDs are globally unique and good for distributed inserts and merging data, but larger and random, causing index fragmentation. Time-ordered UUIDs such as UUIDv7 reduce fragmentation. Choose based on scale, distribution and security needs.
11
Can you use window functions with aggregate functions in the same query?
Yes. Window functions are evaluated after GROUP BY, so they can operate on aggregated values. For example, SELECT region, SUM(sales) AS s, RANK() OVER (ORDER BY SUM(sales) DESC) AS rnk FROM orders GROUP BY region ranks regions by total sales. The aggregate is computed per group first, and then the window function runs over the grouped rows.
12
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.
A materialised view stores the result of a query physically, unlike a normal view. Reads are fast because data is precomputed, which suits heavy aggregations for dashboards. The trade-off is staleness, so it must be refreshed on schedule, on commit or incrementally depending on the database. PostgreSQL uses REFRESH MATERIALIZED VIEW, and SQL Server offers indexed views with similar benefits.
14
What are database statistics and why do they matter?
Statistics describe data distribution in columns, such as row counts, distinct values and histograms. The optimiser uses them to estimate how many rows each step returns and pick join types and indexes. Stale statistics after large data loads lead to bad plans, such as nested loops over millions of rows. Update them with ANALYZE in PostgreSQL or UPDATE STATISTICS in SQL Server.
NTILE(n) splits ordered rows into n roughly equal buckets, useful for quartiles or deciles. PERCENT_RANK returns (rank - 1) / (rows - 1), a relative position between 0 and 1. CUME_DIST returns the fraction of rows with values less than or equal to the current row. They are used for customer segmentation, percentile reports and scoring.
16
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.
17
Match each employee's salary to a grade using a range table.
SELECT e.name, e.salary, g.grade
FROM employees e
JOIN salary_grades g
ON e.salary BETWEEN g.min_salary AND g.max_salary;
This is a non-equi join. Ensure grade ranges do not overlap, otherwise an employee matches more than one grade and appears twice.
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.
19
What is the difference between clustered and non-clustered indexes?
A clustered index defines the physical order of rows in the table, so there can be only one, and in SQL Server the primary key creates it by default. A non-clustered index is a separate structure with key values and pointers to rows, and a table can have many. Range queries on the clustered key are very fast, while non-clustered indexes suit selective lookups.
20
A search on name LIKE '%sharma%' is very slow on a 20 million row table. What can you do?
A leading wildcard cannot use a normal B-tree index, so the database scans the table. Options are full-text indexing, trigram indexes in PostgreSQL, a reversed or computed column if the pattern is a suffix, or a search engine for heavy text search. Also limit the result, filter on other indexed columns first, and check whether users really need contains search.
A view is a saved SELECT query that behaves like a virtual table. It simplifies complex joins for users, hides sensitive columns for security, and provides a stable interface when underlying tables change. A normal view does not store data, so it runs the query each time. Simple views can be updatable, while views with aggregates or joins usually are not.
22
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.
23
Rewrite a non-SARGable date filter to use an index.
Slow:
SELECT * FROM orders
WHERE YEAR(order_date) = 2025
AND MONTH(order_date) = 3;
Fast:
SELECT * FROM orders
WHERE order_date >= '2025-03-01'
AND order_date < '2025-04-01';
The second form compares the raw column, so an index on order_date can be used with a range seek.
24
Write a query to show each employee with their manager's name.
SELECT e.emp_id,
e.name AS employee,
m.name AS manager
FROM employees e
LEFT JOIN employees m
ON e.manager_id = m.emp_id;
The same table is used twice with different aliases. LEFT JOIN ensures the CEO, who has no manager, still appears with a NULL manager name.
25
What is a composite index and why does column order matter?
A composite index covers multiple columns, such as (customer_id, order_date). It is sorted by the first column, then the second within it. It helps queries filtering on customer_id alone or on both columns, but not queries filtering only on order_date, because of the leftmost prefix rule. Put the most commonly filtered equality column first, followed by range columns.
Isolation levels balance consistency and concurrency. Read Uncommitted allows dirty reads. Read Committed, the default in PostgreSQL and SQL Server, prevents dirty reads but allows non-repeatable reads. Repeatable Read, the default in MySQL InnoDB, prevents non-repeatable reads, and InnoDB also prevents most phantoms with gap locks. Serializable prevents all anomalies but reduces concurrency. Choose based on business correctness needs.
27
A query that ran in 1 second now takes 40 seconds after a data load. What do you check?
Compare the current execution plan with the old one. A big data load often makes statistics stale, causing poor row estimates and a different join or scan choice, so update statistics first. Check for index fragmentation, missing indexes after the load, blocking from other sessions, and whether the data volume crossed a threshold. Test again after each change.
28
How do you explain a technical database issue to a non-technical manager?
Situation: my manager asked why a report was late every Monday. Task: explain and get approval for a fix. Action: I compared the database to a busy shop counter where reports and customers queue together, showed the timing data, and proposed a separate reporting copy. Result: he understood the trade-off in five minutes, approved the read replica, and Monday reports became on time.
29
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.
30
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.
31
Find employees who earn more than their department average.
SELECT e.emp_id, e.name, e.department_id, e.salary
FROM employees e
WHERE e.salary > (
SELECT AVG(e2.salary)
FROM employees e2
WHERE e2.department_id = e.department_id
);
This is a correlated subquery. A window version uses AVG(salary) OVER (PARTITION BY department_id) in a CTE and filters in the outer query.
32
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.
33
What does DISTINCT do and how is it different from GROUP BY?
DISTINCT removes duplicate rows from the result based on all selected columns. GROUP BY groups rows so you can apply aggregates per group. SELECT DISTINCT city FROM customers and SELECT city FROM customers GROUP BY city give the same output, but GROUP BY is needed when you also want counts or sums. Overusing DISTINCT to hide duplicate join rows is a common mistake.
34
Your running total jumps by large amounts on some dates instead of row by row. Why?
With ORDER BY and no explicit frame, the default frame is RANGE UNBOUNDED PRECEDING, which treats all rows with the same order value as peers and includes them together. When several rows share the same date, the running total adds them all at once. Specify ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, or add a unique tiebreaker to ORDER BY.
35
A query uses SELECT * on a table with 80 columns. Why is that a problem?
SELECT * fetches every column, increasing disk reads, memory, network transfer and application processing. It prevents covering indexes from being used and can break applications when columns are added or reordered. Select only required columns, which lets the optimiser use narrower indexes and makes the intent clear. SELECT * is acceptable only for quick exploration, not production code.
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.
Few big employers listed in Nagpur?
Many Nagpur candidates also apply to teams in Pune and to remote or hybrid roles. Practise the Pune set as well.
Companies with large offices in Nagpur include many IT services and product firms. Use their company pages below to practise employer-specific sets.
Are SQL 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 SQL jobs in Nagpur?
Shortlist companies with Nagpur offices, keep your CV focused on SQL projects, apply on company career pages and job portals with the Nagpur filter, and practise the questions on this page before each interview.