Structured Query Language (SQL) remains a pivotal tool for data scientists, enabling them to interact seamlessly with relational databases. Given its significance, SQL proficiency is a common area of assessment during Data Science interviews. In this expanded guide, we delve deeper into some of the top SQL interview questions tailored for data scientists, complete with detailed answers and thorough explanations.

1. What is the difference between INNER JOIN and LEFT JOIN?

Answer: An INNER JOIN retrieves rows from both tables that satisfy the given condition, excluding rows that don't match in either table. Conversely, a LEFT JOIN fetches all rows from the left table and the matching rows from the right table. If no match exists, the result is NULL for the right table's columns. In real-world scenarios, understanding which join to use can significantly affect the data you retrieve, potentially impacting subsequent analyses.

2. How would you retrieve the second highest salary from a table named 'Employees'?

Answer: To fetch the second highest salary:

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SELECT DISTINCT salary FROM Employees ORDER BY salary DESC LIMIT 1 OFFSET 1;

Understanding this query is pivotal as it tests the ability to filter data based on order and limits, which is a frequent requirement when analyzing large datasets.

3. Explain the difference between HAVING and WHERE clauses.

Answer: The WHERE clause filters rows before any aggregation, while the HAVING clause filters after aggregation. Essentially, WHERE precedes GROUP BY, and HAVING follows it. This distinction is crucial as misplacing these clauses can yield incorrect data aggregations, leading to potentially misleading insights.

4. What is a subquery, and how is it different from a JOIN?

Answer: A subquery is a query nested within another, used to fetch data for the primary query. In contrast, JOIN combines rows from two or more tables based on related columns. While both methods can yield similar results, subqueries might be slower due to repeated table reads. The choice between them often hinges on the specific data retrieval needs and the database's optimization.

5. Write a SQL query to find all customers who purchased more than two items on a single day.

Answer: Given a table 'Purchases' with 'customer_id', 'purchase_date', and 'item_id':

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SELECT customer_id, purchase_date FROM Purchases GROUP BY customer_id, purchase_date HAVING COUNT(item_id) > 2;

This question emphasizes understanding groupings and conditional aggregations, vital for segmenting datasets effectively.

6. How can you avoid duplicate rows in a query result?

Answer: The DISTINCT keyword at the start of the SELECT statement ensures unique rows in the result set. Eliminating duplicates is fundamental in data preprocessing, ensuring the integrity and accuracy of analyses.

7. Explain the difference between UNION and UNION ALL.

Answer: Both UNION and UNION ALL merge the result sets of multiple queries. However, UNION removes duplicate rows, while UNION ALL retains them. Knowing when to use each can impact the comprehensiveness and size of your retrieved dataset.

8. How would you determine the total number of rows in a table?

Answer: Using the COUNT function yields this information:

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SELECT COUNT(*) FROM table_name;

Grasping basic aggregation functions like COUNT is foundational in data exploration, helping gauge dataset sizes and characteristics.

9. What is an index, and why is it implemented?

Answer: An index, akin to a book's index, expedites data retrieval operations on a database table. By minimizing the data sections read, it enhances query performance. However, while indexes speed up data retrieval, they can slow data insertion, updating, and deletion. Thus, understanding their trade-offs is crucial.

10. How can you fetch all columns from a table except one?

Answer: Standard SQL mandates explicitly listing desired columns in the SELECT statement, as there's no direct method to exclude one column. However, some database systems might offer shortcuts or tools to facilitate this.

Delving Deeper: Advanced SQL Concepts

11. What are SQL Views, and how do they differ from tables?

Answer: A SQL View is a virtual table derived from one or more tables. Unlike actual tables, views don't store data but represent it based on the underlying table data. They're pivotal for data security, simplification, and encapsulating complex queries.

12. Explain SQL Transactions.

Answer: Transactions are sequences of SQL operations executed as a single unit. They follow the ACID properties (Atomicity, Consistency, Isolation, Durability) ensuring data reliability, especially during failures.

13. How does a FULL JOIN operate?

Answer: A FULL JOIN returns all rows when there's a match in one of the tables. Hence, it combines the results of both LEFT and RIGHT JOINs.

14. Describe the role of primary and foreign keys in relational databases.

Answer: A primary key uniquely identifies each record in a table, while a foreign key in one table points to the primary key in another table. Together, they maintain relational integrity, ensuring data consistency and structure.

Final Thoughts: SQL remains the bedrock of data operations, with its concepts frequently explored in interviews. From basic operations to advanced functionalities, mastering SQL is indispensable for aspiring data scientists. By preparing for these and similar questions, candidates can confidently demonstrate their SQL acumen, paving the way for successful roles in data-driven domains.