Master SQL for Data Science: 2026 Practice Questions for Analysts

Welcome to the most comprehensive practice exams designed to help you master Data Science SQL for Analysts. In the rapidly evolving landscape of 2026, SQL remains the bedrock of data discovery. This course is meticulously crafted to bridge the gap between basic syntax and the complex analytical reasoning required in modern data roles.

Why Serious Learners Choose These Practice Exams

Serious learners understand that watching tutorials is not the same as solving problems. These exams provide a rigorous environment to test your limits. Unlike generic quizzes, our question bank focuses on the logic of data manipulation, ensuring you can handle messy, high-volume datasets. By choosing this course, you are investing in a resource that emphasizes deep comprehension over rote memorization.

Course Structure

Our curriculum is organized into six strategic pillars to ensure a progressive learning curve:

• Basics / Foundations: We begin by solidifying your understanding of data types, filtering, and basic aggregations. This section ensures you can navigate databases and retrieve specific information without errors.

• Core Concepts: Here, we dive into the essential mechanics of SQL, including Joins and Group By clauses. You will learn how to connect disparate tables to create a unified view of your data.

• Intermediate Concepts: This stage introduces Subqueries and Common Table Expressions (CTEs). You will learn how to break down complex problems into manageable, readable code blocks.

• Advanced Concepts: We tackle Window Functions, recursive queries, and performance optimization. These are the tools that separate junior analysts from senior data scientists.

• Real-world Scenarios: These questions simulate actual business problems, such as calculating Churn Rates, Monthly Recurring Revenue (MRR), and cohort analysis using realistic schemas.

• Mixed Revision / Final Test: The ultimate challenge. This section mixes all previous concepts into high-pressure exams to ensure you are fully prepared for interviews or technical certifications.

Sample Practice Questions

Question 1

You are analyzing a sales table named orders. You need to find the total revenue for each month in 2025, but you only want to include months where the total revenue exceeded 50,000. Which clause is used to filter the aggregated revenue?

• Option 1: WHERE

• Option 2: FILTER

• Option 3: HAVING

• Option 4: GROUP BY

• Option 5: ORDER BY

Correct Answer: Option 3

Correct Answer Explanation: The HAVING clause is used specifically to filter data after an aggregation has been performed. Since the requirement is to filter based on "total revenue" (an aggregate), HAVING is the correct choice.

Wrong Answers Explanation:

• Option 1: WHERE is used to filter individual rows before any grouping or aggregation occurs. It cannot be used with aggregate functions like SUM().

• Option 2: FILTER is used in specific window function syntax or specific SQL dialects, but it is not the standard clause for filtering grouped result sets.

• Option 4: GROUP BY is used to arrange identical data into groups but does not perform the filtering action itself.

• Option 5: ORDER BY is used to sort the final output and has no impact on which rows or groups are included in the result.

Question 2

Which Window Function would you use if you wanted to assign a unique rank to each row within a partition, ensuring that if two rows have the same value, they receive different rank numbers based on their physical order?

• Option 1: RANK()

• Option 2: DENSE_RANK()

• Option 3: NTILE()

• Option 4: ROW_NUMBER()

• Option 5: PERCENT_RANK()

Correct Answer: Option 4

Correct Answer Explanation: ROW_NUMBER() assigns a unique, sequential integer to each row. Even if values in the ORDER BY clause are identical, ROW_NUMBER() will provide a different number for each row, ensuring no ties.

Wrong Answers Explanation:

• Option 1: RANK() assigns the same rank to ties and skips the next available rank (e.g., 1, 2, 2, 4).

• Option 2: DENSE_RANK() assigns the same rank to ties but does not skip any ranks (e.g., 1, 2, 2, 3).

• Option 3: NTILE() divides the result set into a specified number of ranked groups or buckets rather than individual ranks.

• Option 5: PERCENT_RANK() calculates the relative rank of a row within a partition as a percentage, which does not provide a unique integer per row.

Enroll With Confidence

We are committed to your success. When you join this course, you gain access to a premium learning environment:

• You can retake the exams as many times as you want to achieve perfection.

• This is a huge original question bank updated for 2026 standards.

• You get support from instructors if you have questions regarding any logic or syntax.

• Each question has a detailed explanation to ensure you learn from your mistakes.

• Mobile-compatible with the Udemy app for learning on the go.

• 30-days money-back guarantee if you are not satisfied with the quality.

We hope that by now you are convinced! There are a lot more questions inside the course waiting to challenge you.