Basic Data Analytics questions
1. What does a data analyst do?
Collects, cleans and analyses data to answer business questions, then communicates findings through reports and dashboards using tools such as Excel, SQL, Power BI or Tableau, and Python.
2. What are the steps in a data analysis project?
Define the question, collect data, clean and prepare it, explore it, analyse or model it, visualise the results and present recommendations to stakeholders.
3. VLOOKUP vs XLOOKUP vs INDEX-MATCH?
VLOOKUP searches only the first column and returns a column to the right. INDEX-MATCH can look in any direction and is robust to inserted columns. XLOOKUP (newer Excel) searches any direction, has an exact match by default and supports a not-found value.
Intermediate Data Analytics questions
4. How do you handle missing data?
First understand why it is missing. Then remove rows if few and random, impute with mean, median, mode or forward fill, use a separate 'unknown' category, or flag missingness as a feature. Always document the choice.
5. How do you detect outliers?
Use box plots and the IQR rule (below Q1 - 1.5 x IQR or above Q3 + 1.5 x IQR), z-scores above 3, or domain rules. Investigate before removing; outliers can be errors or the most important insight.
6. Mean vs median: which do you report?
The mean is sensitive to extreme values; the median is the middle value and robust to skew. For skewed data like salaries or house prices, the median represents a typical value better.
7. What is DAX in Power BI?
Data Analysis Expressions is the formula language for measures and calculated columns. Measures such as Total Sales = SUM(Sales[Amount]) are evaluated in filter context; CALCULATE changes that context for comparisons like year-over-year.
8. Correlation vs causation?
Correlation means two variables move together; causation means one causes the other. Ice cream sales and drowning both rise in summer without one causing the other. Proving causation needs controlled experiments such as A/B tests.
Advanced Data Analytics questions
9. How would you analyse a sudden drop in sales?
Confirm the data is correct, then segment by time, region, product, channel and customer type to locate the drop. Check external factors (seasonality, competitors, price changes, outages) and present the root cause with a recommended action.
10. What makes a good dashboard?
It answers specific business questions for a known audience, shows a few key KPIs at the top, uses the right chart for each comparison, allows filtering and drill-down, uses consistent colours and refreshes reliably.
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