Lead Data Analyst at Govcio LLC

8 questions, about 5 minutes. This is a diagnostic, not a certification — it estimates your skill readiness, it does not guarantee you are qualified for or will be hired into this role.

1. You need each customer's most recent order. Which approach is most reliable?

ORDER BY order_date DESC LIMIT 1 with no grouping A window function (ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC)) MAX(order_date) alone with SELECT * GROUP BY customer_id with no aggregate on the other columns

2. What does `df.groupby('region')['sales'].sum()` return?

The total sales across the whole dataframe Total sales summed for each distinct region A count of rows per region An error, because groupby requires two columns

3. A p-value of 0.03 from a hypothesis test at a 0.05 significance threshold suggests:

The null hypothesis is definitely false There is statistically significant evidence against the null hypothesis The result is not usable The sample size was too small

4. Which clause filters rows before they are grouped by GROUP BY?

HAVING WHERE ORDER BY LIMIT

5. Which measure of central tendency is least affected by extreme outliers?

Mean Median Range Standard deviation

6. Which library is most commonly used for tabular data manipulation in Python?

pandas flask requests pytest

7. An INNER JOIN between orders and customers drops rows where...

the customer has no matching order the order has no matching customer both a and b nothing is dropped

8. A query aggregates revenue by region but SELECT also lists an ungrouped column. What happens on strict SQL engines (e.g. MySQL with ONLY_FULL_GROUP_BY, or PostgreSQL)?

It runs and picks an arbitrary value for the ungrouped column It errors — every selected column must be aggregated or in GROUP BY It silently returns NULL for the ungrouped column It automatically adds the column to GROUP BY

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