Top 10 Data Analyst Interview Questions for Freshers in Bangalore (2025 Edition)

You've built your projects, polished your resume, and now the interview calls are coming in from top companies across Bangalore. This is the final hurdle. As a fresher, facing your first technical interview can be daunting. What will they ask? How deep do you need to go? If you've been searching for "data analyst interview questions for freshers Bangalore," you know that preparation is everything.

This guide cuts through the noise. We've compiled the most common and critical questions—across SQL, Python, Power BI, and more—that Bangalore's top tech and startup companies are asking freshers in 2025. At Vtricks Technologies, we don't just teach the skills; we prepare you to prove them. Let's dive in.

SQL Interview Questions (The Foundation)

Expect at least half of your technical round to focus on SQL. It's the bedrock of data analysis.

1. What is the difference between `WHERE` and `HAVING`?

Answer: "The `WHERE` clause is used to filter rows *before* any groupings or aggregations are made. It works on individual row data. The `HAVING` clause is used to filter groups *after* aggregations have been performed using `GROUP BY`. You use `WHERE` for raw data and `HAVING` for aggregated data, like `SUM()`, `COUNT()`, or `AVG()`."

2. You have a table of employees with `employee_id`, `name`, `department`, and `salary`. How would you find the second highest salary?

Answer: "There are a few ways, but a common and efficient method is to use `DENSE_RANK()` or a subquery. Using `DENSE_RANK()` would be:
WITH RankedSalaries AS (SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) as rnk FROM employees) SELECT salary FROM RankedSalaries WHERE rnk = 2;
This approach handles ties gracefully and is generally preferred by interviewers as it shows knowledge of window functions."

Power BI Interview Questions (The Visualization Tool)

Questions here test your ability to transform raw data into insightful business dashboards.

3. What is the difference between a Calculated Column and a Measure in DAX?

Answer: "A **Calculated Column** is computed row-by-row during data refresh and is stored physically in the model. It uses the context of the current row. A **Measure** is calculated on-the-fly at the time of the query, based on the context of the filters applied in the report (like slicers or visuals). You use a calculated column for static, row-level values and a measure for dynamic aggregations that respond to user interaction."

4. Scenario: You have a sales table and a calendar table. How do you ensure you can analyze sales data by year, quarter, and month?

Answer: "The key is to build a proper Star Schema data model. I would create a 'one-to-many' relationship from the calendar table's date column (the 'one' side) to the sales table's order date column (the 'many' side). The calendar table would be marked as the official 'date table' in Power BI. This allows DAX time intelligence functions like `TOTALYTD` or `SAMEPERIODLASTYEAR` to work correctly and enables users to slice and dice sales data by any attribute in the calendar table (year, quarter, month, day)."

Python and Scenario-Based Questions

These questions assess your practical problem-solving skills.

5. How would you handle missing values in a Pandas DataFrame?

Answer: "My approach depends on the context. First, I'd use `df.isnull().sum()` to see how much data is missing. If it's a small percentage, I might drop the rows using `df.dropna()`. For numerical data, I could impute the missing values with the mean or median using `df['column'].fillna(df['column'].median())`. For categorical data, I might fill it with the mode. The choice depends on whether the imputation would introduce bias."

6. Your manager says 'customer churn has increased' and gives you a dataset. What are your first steps?

Answer: "My first step is to define and clarify the problem. I would ask clarifying questions like: 'How are we defining churn?', 'Over what time period are we measuring this increase?', and 'What is the business impact we are trying to prevent?'. Once the objective is clear, I would perform Exploratory Data Analysis (EDA) to understand the data's structure, identify key features related to customers (like tenure, products used, support tickets), clean the data, and then start forming hypotheses to test."

How Vtricks Prepares You For the Toughest Interviews

Knowing the answers is one thing. Demonstrating your skills with confidence is another. The questions above aren't just theoretical; they are practical problems you solve every day in our program.

• Mock Interviews: Our instructors, who are industry veterans, conduct rigorous mock interviews that simulate the high-pressure environment of companies in Bangalore, providing you with direct feedback.
• Project-Based Learning: When you're asked a scenario-based question, you won't give a textbook answer. You'll describe how you solved a similar problem in one of the 50+ real-world projects you completed during the course.
• Hands-On Practice: Our curriculum is designed so that writing complex SQL queries and building dynamic Power BI dashboards becomes second nature. We ensure you are prepared for any technical challenge.

Don't just memorize answers. Build the experience that makes you the confident, hire-ready candidate that Bangalore's top companies are looking for.

Ready to turn your knowledge into a job offer? Explore our Data Analytics Course in Bangalore and learn how our 100% placement assistance program prepares you for success.