55 Must-Know SQL in ML Interview Questions and Answers 2024

Basic SQL Skills for Machine Learning

1.
What are the different types of JOIN operations in SQL?
Answer:
2.
Explain the difference between WHERE and HAVING clauses.
Answer:
3.
How would you write a SQL query to select distinct values from a column?
Answer:
4.
What does GROUP BY do in a SQL query?
Answer:
5.
How can you aggregate data in SQL (e.g., COUNT, AVG, SUM, MAX, MIN)?
Answer:
6.
Describe a subquery and its typical use case.
Answer:
7.
Can you explain the use of indexes in databases and how they relate to Machine Learning?
Answer:
8.
How would you optimize a SQL query that seems to be running slowly?
Answer:

Data Extraction and Transformation

9.
How do you handle missing values in a SQL dataset?
Answer:
10.
Write a SQL query that joins two tables and retrieves only the rows with matching keys.
Answer:
11.
How would you merge multiple result sets in SQL without duplicates?
Answer:
12.
Create a SQL query to pivot a table transforming rows into columns.
Answer:
13.
Explain the importance of data normalization in SQL and how it affects Machine Learning models.
Answer:
14.
How can you extract time-based features from a SQL datetime field for use in a Machine Learning model?
Answer:
15.
What are SQL Window Functions and how can they be used for Machine Learning feature engineering?
Answer:

Feature Engineering Using SQL

16.
Write a SQL query to calculate moving averages.
Answer:
17.
How can you create lagged features in SQL?
Answer:
18.
Describe how to compute a ratio feature within groups using SQL.
Answer:
19.
Explain how to discretize a continuous variable in SQL.
Answer:
20.
How do you join transactional data to a dimension table in such a way that features for Machine Learning can be extracted?
Answer:

Data Cleaning and Preprocessing

21.
Write a SQL query that identifies and removes duplicate records from a dataset.
Answer:
22.
How can you deal with outliers in a SQL database before passing data to Machine Learning algorithms?
Answer:
23.
In SQL, how would you format strings or concatenate columns for text-based Machine Learning features?
Answer:
24.
Explain how to perform binning of categorical variables in SQL for use in a Machine Learning model.
Answer:
25.
Describe SQL techniques to perform data sampling.
Answer:

SQL with Machine Learning Integrations

26.
How can you execute a Machine Learning model stored in a database (such as a SQL Server with R or Python integration)?
Answer:
27.
Write a SQL stored procedure that calls a Machine Learning scoring function.
Answer:
28.
Can you update a Machine Learning model directly from SQL? If so, how might you do it?
Answer:
29.
How does SQL play a role in ML model deployment?
Answer:
30.
What is the significance of in-database analytics for Machine Learning?
Answer:

Advanced SQL for Machine Learning

31.
Explain recursive SQL queries and how they can be used to prepare data for hierarchical Machine Learning algorithms.
Answer:
32.
Describe how graph-based features can be generated from SQL data.
Answer:
33.
What are SQL Common Table Expressions (CTEs) and how can they be used for feature generation?
Answer:
34.
How would you construct a complex SQL query to extract time series features for a Machine Learning model?
Answer:
35.
Discuss ways to implement regular expressions in SQL for natural language processing tasks.
Answer:

Coding Challenges

36.
Write a SQL script to identify and replace missing values with the column mean.
Answer:
37.
Create a SQL query that normalizes a column (scales between 0 and 1).
Answer:
38.
Generate a feature that is a count over a rolling time window using SQL.
Answer:
39.
Code an SQL function that categorizes continuous variables into bins.
Answer:
40.
Implement a SQL solution to compute the TF-IDF score for text data.
Answer:

Performance and Scalability

41.
How would you handle very large datasets in SQL for Machine Learning purposes?
Answer:
42.
Explain the role of partitioning in large-scale SQL databases.
Answer:
43.
What strategies can be used to efficiently update a large SQL-based Machine Learning model?
Answer:
44.
How do you ensure the consistency and reliability of SQL data used for Machine Learning?
Answer:
45.
Discuss how you would design a system to regularly feed a Machine Learning model with SQL data.
Answer:

Data Visualization and Reporting

46.
What SQL features are there for report generation that might be useful for analyzing Machine Learning model performance?
Answer:
47.
How can you use SQL to visualize the distribution of data points before feeding them into an ML algorithm?
Answer:
48.
Describe how you could use SQL to report the performance metrics of a Machine Learning model.
Answer:
49.
Can SQL be used to visualize false positives and false negatives in classification models? If so, how?
Answer:
50.
How would you extract and prepare a confusion matrix for a classification problem using SQL?
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Machine Learning Model Management

51.
Describe how you would version control the datasets used for building Machine Learning models in SQL.
Answer:
52.
What is Data Lineage, and how can you track it using SQL?
Answer:
53.
How would you log and track predictions made by a Machine Learning model within a SQL environment?
Answer:
54.
Discuss how to manage the entire lifecycle of a Machine Learning model using SQL tools.
Answer:
55.
What strategies might you use to automate the retraining and evaluation of Machine Learning models from within SQL?
Answer:

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55 SQL in ML interview questions

What are the different types of JOIN operations in SQL?

Explain the difference between WHERE and HAVING clauses.

How would you write a SQL query to select distinct values from a column?

What does GROUP BY do in a SQL query?

How can you aggregate data in SQL (e.g., COUNT, AVG, SUM, MAX, MIN)?

Describe a subquery and its typical use case.

Can you explain the use of indexes in databases and how they relate to Machine Learning?

How would you optimize a SQL query that seems to be running slowly?

How do you handle missing values in a SQL dataset?

Write a SQL query that joins two tables and retrieves only the rows with matching keys.

How would you merge multiple result sets in SQL without duplicates?

Create a SQL query to pivot a table transforming rows into columns.

Explain the importance of data normalization in SQL and how it affects Machine Learning models.

How can you extract time-based features from a SQL datetime field for use in a Machine Learning model?

What are SQL Window Functions and how can they be used for Machine Learning feature engineering?

Write a SQL query to calculate moving averages.

How can you create lagged features in SQL?

Describe how to compute a ratio feature within groups using SQL.

Explain how to discretize a continuous variable in SQL.

How do you join transactional data to a dimension table in such a way that features for Machine Learning can be extracted?

Write a SQL query that identifies and removes duplicate records from a dataset.

How can you deal with outliers in a SQL database before passing data to Machine Learning algorithms?

In SQL, how would you format strings or concatenate columns for text-based Machine Learning features?

Explain how to perform binning of categorical variables in SQL for use in a Machine Learning model.

Describe SQL techniques to perform data sampling.

How can you execute a Machine Learning model stored in a database (such as a SQL Server with R or Python integration)?

Write a SQL stored procedure that calls a Machine Learning scoring function.

Can you update a Machine Learning model directly from SQL? If so, how might you do it?

How does SQL play a role in ML model deployment?

What is the significance of in-database analytics for Machine Learning?

Explain recursive SQL queries and how they can be used to prepare data for hierarchical Machine Learning algorithms.

Describe how graph-based features can be generated from SQL data.

What are SQL Common Table Expressions (CTEs) and how can they be used for feature generation?

How would you construct a complex SQL query to extract time series features for a Machine Learning model?

Discuss ways to implement regular expressions in SQL for natural language processing tasks.

Write a SQL script to identify and replace missing values with the column mean.

Create a SQL query that normalizes a column (scales between 0 and 1).

Generate a feature that is a count over a rolling time window using SQL.

Code an SQL function that categorizes continuous variables into bins.

Implement a SQL solution to compute the TF-IDF score for text data.

How would you handle very large datasets in SQL for Machine Learning purposes?

Explain the role of partitioning in large-scale SQL databases.

What strategies can be used to efficiently update a large SQL-based Machine Learning model?

How do you ensure the consistency and reliability of SQL data used for Machine Learning?

Discuss how you would design a system to regularly feed a Machine Learning model with SQL data.

What SQL features are there for report generation that might be useful for analyzing Machine Learning model performance?

How can you use SQL to visualize the distribution of data points before feeding them into an ML algorithm?

Describe how you could use SQL to report the performance metrics of a Machine Learning model.

Can SQL be used to visualize false positives and false negatives in classification models? If so, how?

How would you extract and prepare a confusion matrix for a classification problem using SQL?

Describe how you would version control the datasets used for building Machine Learning models in SQL.

What is Data Lineage, and how can you track it using SQL?

How would you log and track predictions made by a Machine Learning model within a SQL environment?

Discuss how to manage the entire lifecycle of a Machine Learning model using SQL tools.

What strategies might you use to automate the retraining and evaluation of Machine Learning models from within SQL?

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