SQL and Data Querying

SQL and Data Querying Questions

Q1.What is the difference between WHERE and HAVING in SQL?+

WHERE filters rows before aggregation — applied to individual rows. HAVING filters groups after aggregation — applied to aggregated results. Example: WHERE salary > 50000 filters individual employees. HAVING AVG(salary) > 50000 filters departments whose average salary exceeds 50000. You cannot use aggregate functions in WHERE.

Q2.Explain different types of JOINs with examples.+

INNER JOIN: returns only matching rows from both tables. LEFT JOIN: all rows from left table + matching from right (NULL for non-matches). RIGHT JOIN: all rows from right + matching from left. FULL OUTER JOIN: all rows from both tables. CROSS JOIN: every row from left paired with every row from right (cartesian product). Self JOIN: table joined with itself (e.g., find employees and their managers).

Q3.Write a SQL query to find employees who earn more than their department average.+

Using a subquery: SELECT * FROM employees e WHERE salary > (SELECT AVG(salary) FROM employees WHERE department_id = e.department_id). Using window function: SELECT * FROM (SELECT *, AVG(salary) OVER (PARTITION BY department_id) as dept_avg FROM employees) t WHERE salary > dept_avg. The window function approach is more efficient and readable.

Q4.What are CTEs (Common Table Expressions) and when do you use them?+

CTEs are temporary named result sets defined with WITH keyword. Use for: breaking complex queries into readable steps, recursive queries (hierarchical data), replacing nested subqueries, and reusing the same subquery multiple times. Example: WITH monthly_sales AS (SELECT month, SUM(amount) as total FROM orders GROUP BY month) SELECT * FROM monthly_sales WHERE total > 100000.

Q5.How do you find the running total of sales by date in SQL?+

SELECT date, daily_sales, SUM(daily_sales) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as running_total FROM daily_sales_table. The window function SUM() OVER (ORDER BY date) calculates a cumulative sum. ROWS BETWEEN clause specifies the window frame. This is a common analytics pattern for tracking growth over time.

Excel and Visualization

Excel and Visualization Questions

Q6.What is the difference between VLOOKUP and INDEX-MATCH?+

VLOOKUP searches the first column of a range and returns a value from a specified column. INDEX-MATCH is more flexible: MATCH finds the row position, INDEX returns the value from any column. INDEX-MATCH advantages: lookup column can be anywhere (not just first), handles insertions/deletions better, and works with columns to the left. Always prefer INDEX-MATCH for reliability.

Q7.How do you create a pivot table and when would you use one?+

Select data range, Insert > PivotTable. Drag fields to Rows (grouping), Columns (categories), and Values (metrics with Sum/Count/Average). Use for: summarizing large datasets, cross-tabulating two dimensions, creating quick reports. Add filters for interactive analysis. Pivot tables are the single most important Excel skill for data analysts.

Q8.What makes a good dashboard?+

Clear purpose: answers specific business questions. KPIs at top: 3-5 key metrics with context (vs target, vs last period). Visual hierarchy: most important data is largest and top-left. Consistent colors: use a limited palette with semantic meaning (red for bad, green for good). Interactivity: filters and drill-downs. Minimal clutter: remove chart junk, gridlines, and unnecessary decoration. Mobile responsive.

Q9.How do you choose the right chart type for your data?+

Comparison over time: line chart. Comparison across categories: bar chart (horizontal for many categories). Part of whole: pie chart (max 5 slices) or stacked bar. Distribution: histogram or box plot. Relationship: scatter plot. Composition: stacked area chart. Ranking: horizontal bar sorted by value. Rule: if you need a legend to understand the chart, simplify it.

Q10.What is DAX in Power BI and how is it different from SQL?+

DAX (Data Analysis Expressions) is the formula language in Power BI. Unlike SQL which queries rows, DAX works on columnar data and aggregations. Key DAX functions: CALCULATE (modify filter context), SUMX/AVERAGEX (row-by-row calculations), RELATED (navigate relationships), and time intelligence (SAMEPERIODLASTYEAR, DATESYTD). DAX is more powerful for dynamic calculations but has a steeper learning curve.

Want to master these concepts hands-on?

CodingClave's Data Analytics training in Lucknow covers all these topics with practical projects and mock interviews.

Learn Data Analytics at CodingClave

Business Analytics

Business Analytics Questions

Q11.What KPIs would you track for an e-commerce website?+

Revenue: total revenue, AOV (average order value), revenue per visitor. Conversion: conversion rate, cart abandonment rate, checkout completion rate. Customer: CAC (customer acquisition cost), CLV (customer lifetime value), repeat purchase rate, NPS. Product: top-selling products, inventory turnover, return rate. Channel: traffic by source, attribution, ROI by channel.

Q12.How would you investigate a 20% drop in website revenue?+

Decompose: Revenue = Traffic x Conversion Rate x AOV. Check which factor dropped. Segment by: time period (when did it start), traffic source (organic, paid, direct), device (mobile vs desktop), geography, product category. Look for external factors: competitor actions, seasonality, site issues (check error logs). Correlate with changes: pricing updates, UI changes, marketing campaign end. Present hypothesis and data to support it.

Q13.Explain cohort analysis and when it is useful.+

Cohort analysis groups users by a shared characteristic (usually signup month) and tracks their behavior over time. Example: compare retention rates of January vs February signups. Useful for: understanding user lifecycle, measuring impact of changes (features shipped in March), identifying retention patterns, and calculating LTV. Visualize with cohort retention tables showing % active over time.

Problem Solving

Problem Solving Questions

Q16.A product manager asks you to determine which feature to build next. How would you approach this?+

Quantify impact: analyze usage data for existing features (which are most used), survey users (what do they want), look at support tickets (what causes problems). Score features by: expected impact on key metric x reach (% users affected) x confidence / effort (ICE framework). Present data-driven recommendation with trade-offs. A/B test if possible before full build.

Q17.How would you measure the success of a new marketing campaign?+

Define success metrics before launch: primary (conversions, revenue from campaign) and secondary (brand awareness, traffic). Set up tracking: UTM parameters, conversion pixels, unique landing pages. Compare against baseline (same period last year, control group). Calculate ROI: (revenue - cost) / cost. Segment by channel, audience, and creative. Report with statistical significance where possible.

Frequently Asked Questions

Common Questions

What topics are asked in data analytics interviews?+

SQL queries, Excel skills, visualization tool knowledge (Power BI/Tableau), basic statistics, and business case studies. Communication skills are heavily evaluated.

Does CodingClave prepare students for data analytics interviews?+

Yes. The 6-month Data Analytics program at CodingClave in Lucknow includes mock interviews covering SQL, Excel, and case study rounds.

How important is SQL for data analyst interviews?+

SQL is the most tested skill. Every data analyst interview includes SQL questions. Practice complex JOINs, window functions, and data transformation queries daily.

What salary can I expect after clearing a data analytics interview?+

₹2.5-6 LPA for freshers. In Lucknow, ₹3-5 LPA. Adding Python and Power BI skills pushes offers higher.

Should I prepare case studies for analytics interviews?+

Yes. Analytics interviews often include business scenario questions: how would you measure the success of a feature, what metrics would you track for an e-commerce site, how would you investigate a drop in revenue.

Is Power BI or Tableau more useful for interviews?+

Power BI is more commonly asked in India, especially at companies using Microsoft tools. Tableau knowledge is valuable for consulting firms. Learn at least one deeply.

Do data analyst interviews include coding?+

SQL coding is standard. Python coding is a bonus but not always required for entry-level roles. Excel proficiency (pivot tables, VLOOKUP, macros) is tested through practical exercises.

How should I prepare for a data analyst interview in 2 weeks?+

Focus on: SQL (practice 5 queries daily), review these 15 questions, prepare 2-3 case study frameworks, review Excel pivot tables and VLOOKUP, and practice explaining a data analysis project you have completed.

Related Resources

Explore More Resources

PHP Laravel Interview Questions 2026

Top 15 PHP Laravel interview questions with answers for freshers and experienced...

Python Django Interview Questions 2026

Top 15 Python Django interview questions with answers for freshers. Prepare for ...

MERN Stack Interview Questions 2026

Top 15 MERN Stack interview questions with answers for freshers. MongoDB, Expres...

MEAN Stack Interview Questions 2026

Top 15 MEAN Stack interview questions with answers. Angular, Node.js, Express, M...

Get Started

Learn Data Analytics at CodingClave Lucknow

Join our practical-based Data Analytics training in Lucknow. 28-day, 45-day, and 6-month programs with projects, mentorship, and job assistance.

Apply Now WhatsApp Us View Data Analytics Course

Data Analytics Interview Questions and Answers 2026

Top 15 Data Analytics interview questions with answers. SQL, Excel, Power BI, and business analytics questions for freshers in India.