Data analyst
30 important interview questions.

Answer

A data analyst collects, cleans and analyses data to answer business questions, then presents the findings in reports and dashboards so managers can make decisions. Typical questions: why did sales drop last month, which customers are likely to leave, which product sells best in which region.

Answer

1. Understand the business question and how success will be measured.
2. Collect the data from databases, files or APIs.
3. Clean and prepare it.
4. Explore and analyse it.
5. Visualise the results.
6. Present the insights with clear recommendations.

Answer

Data cleaning fixes problems that would make the analysis wrong: duplicates, missing values, wrong formats (dates stored as text), inconsistent labels ("Kochi", "kochi", "Cochin"), typos and outliers. Real-world data is rarely clean, and bad data leads to bad decisions, so cleaning is often the largest part of the work.

Answer

First find out why it's missing. Then choose based on how much is missing and how important the column is:

• Remove the rows, if only a few are affected.
• Fill with the mean, median or mode, or a value from related data.
• Fill forward or backward for time series.
• Flag it as "Unknown" for categories.

Always note what you did, because it affects the results.

Answer

Data analysis usually means examining a specific dataset to answer a question. Data analytics is the broader field — the tools, processes and methods (including analysis) used to turn data into decisions. In job titles the two are often used interchangeably.

Answer

Structured data fits neatly into rows and columns with a fixed format — sales tables, customer records — and is easy to query with SQL. Unstructured data has no fixed format — emails, reviews, images, call recordings — and needs extra processing (text analysis, tagging) before it can be analysed. Semi-structured data such as JSON sits in between.

Answer

Key Performance Indicators are the few numbers that show whether a business goal is being met — monthly revenue, conversion rate, customer churn, average delivery time. A good KPI is tied to a goal, measurable, clearly defined and something the team can act on.

Answer

Filtering (WHERE), sorting, aggregation (GROUP BY, HAVING), joins, CASE WHEN for categories, date functions, subqueries and CTEs, and window functions for rankings, running totals and period-over-period changes.

Answer

WITH monthly AS (
  SELECT DATE_TRUNC('month', order_date) AS month, SUM(amount) AS revenue
  FROM orders
  GROUP BY 1
)
SELECT month, revenue,
       LAG(revenue) OVER (ORDER BY month) AS prev_revenue,
       ROUND(100.0 * (revenue - LAG(revenue) OVER (ORDER BY month))
             / LAG(revenue) OVER (ORDER BY month), 1) AS growth_pct
FROM monthly;

LAG reads the previous row's value. Date function names vary slightly between databases.

Answer

Use CASE WHEN:

SELECT customer_id,
       CASE WHEN total_spend >= 50000 THEN 'High'
            WHEN total_spend >= 10000 THEN 'Medium'
            ELSE 'Low' END AS segment
FROM customer_totals;

Answer

Count rows and compare with the source, look for NULLs in key columns, find duplicates with GROUP BY ... HAVING COUNT(*) > 1, check values fall in a valid range (no negative quantities, no future dates), and confirm joins don't multiply rows unexpectedly.

Answer

• Comparison between categories: bar chart.
• Trend over time: line chart.
• Part of a whole: stacked bar, or a pie with very few slices.
• Relationship between two numbers: scatter plot.
• Distribution: histogram or box plot.
• One key number: a KPI card.

Keep charts simple, label axes and highlight what matters.

Answer

Both build interactive dashboards. Power BI is strongly integrated with Excel and Microsoft 365, uses DAX for calculations and is cheaper for many organisations. Tableau is known for flexible, polished visual exploration. The concepts — data models, measures, filters, dashboards — transfer between them.

Answer

DAX (Data Analysis Expressions) is Power BI's formula language.

• A calculated column is computed row by row and stored in the table.
• A measure is calculated on the fly for the current filter context — the slicers and visuals in use.

Total Sales = SUM(Sales[Amount])
Sales LY = CALCULATE([Total Sales], SAMEPERIODLASTYEAR('Date'[Date]))

Use measures for totals and ratios; they're more efficient and react to filters.

Answer

A data model with one central fact table (transactions: sales, orders, with numbers to add up) linked to dimension tables (describing the facts: date, product, customer, region). It's simple to understand and fast for BI tools to filter and aggregate.

Answer

It answers the audience's key questions in seconds. Put the most important KPIs at the top, keep a few clear visuals, use consistent colours and labels, provide filters people actually need, show comparisons (target, last year) and make sure the numbers can be trusted.