Being able to use SQL, or Structured Query Language, ranks among the most important skills for data analysts to have. As you prepare to interview for data analyst jobs, you can expect that SQL will come up during the job interview process.
With this guide, you’ll learn more about SQL technical screenings, what type of screening you might encounter, and some common types of questions that come up during these interviews. You’ll also find some example questions, a step-by-step guide for writing SQL code during your interview, and tips for success. Let’s get started.
Data analysts use SQL to communicate with relational databases to access, clean, and analyze data. At the time of writing, more than 230,000 jobs on LinkedIn included SQL in the listing.
Since it’s such a critical skill, it’s common for data analyst interviews to include a SQL technical screening. This portion of the interview tasks you with solving real-world problems using SQL. While you may be asked some definitional questions more typical of a standard interview, the real point here is for the interviewer to verify that you can actually use SQL, not just talk about it.
These screenings typically take one of three forms:
1. Whiteboard test: The most common type of SQL screening is the whiteboard interview. In this type of screening, you’re given a whiteboard and a marker to write out your queries by hand. Since you won’t have a computer alerting you to any syntax or logical errors in your code, this is more about demonstrating that you can think through a problem and know the right SQL concepts to solve it.
2. Live coding: With this type of screening, you’ll be given SQL problems to solve in a live coding environment. This allows you to run your queries and check your work as you go, but since you’re running your code, syntax will matter. Since different databases use different tools, this type of screening isn’t as common as the whiteboard screening.
3. Take-home assignment: With this less-common screening technique, you’ll be given a problem or series of problems to take home and solve within a given period of time. This lets you write your queries in the comfort of your home, without the pressure of an interviewer looking over your shoulder. On the other hand, the coding challenges are often more complex.
Related: 5 SQL Certifications for Your Data Career
Just as there are three formats technical screenings might take, there are also three broad categories of questions you’ll typically be asked during this portion of the interview. We’ve arranged them here from the most simple to the most complex. Generally speaking, the easier, definitional questions will be fewer and less important than the live coding questions—something to keep in mind as you prepare.
If you’re interviewing for a data analyst role, chances are you know what SQL is (and your interviewer assumes you know this). It’s possible you’d be asked what SQL is, but it’s more likely you’ll be asked to explain more technical concepts in SQL, the difference between two (or more) related concepts, or how a concept is used. This is not an exhaustive list, but here are some examples of terms you should be ready to explain:
Trigger: a procedure stored within a database, which automatically happens whenever a specific event occurs.
Index: a special lookup table within a database used to increase data retrieval speed.
Cursor: a pointer, or identifier, associated with a single or group of rows.
Constraints: rules used to limit the type of data allowed within a table. Common constraints include primary key, foreign key, unique key, and NOT NULL.
ETL (Extract, transform, and load): a data integration process used to combine multiple data sources into one data store, such as a data warehouse.
Primary key, foreign key, and unique key: constraints used to identify records within a table.
Normalization vs. denormalization: techniques used to either divide data into multiple tables to achieve integrity ("normalization") or combine data into a table to increase the speed of data retrieval ("denormalization").
RDBMS vs. DBMS: two types of database management systems. Within a relational database management system (RDBMS) data is stored as a table, while in a database management system (DBMS) its stored as a file.
Clustered vs. non-clustered index: two types of indices used to sort and store data. A clustered index sorts data based on their key values, while a non-clustered index stores data and their records in separate locations.
What is the purpose of an index in a table? Explain the different types.
What are the types of joins in SQL?
What is the difference between DROP, TRUNCATE, and DELETE statements?
How do you use a cursor?
What is the difference between a HAVING clause and a WHERE clause?
Read more: SQL vs. MySQL: Differences, Similarities, Uses, and Benefits
This second category gives you an SQL query and asks you a question about it. This tests your ability to read, interpret, analyze, and debug code written by others.
Given a query,
Put the clauses in order by how SQL would run them.
Identify the error and correct it.
Predict what the query will return.
Explain what problem the query is meant to solve.
The questions most commonly associated with the SQL technical screening ask you to solve a given problem by writing out a query in SQL. You’ll typically be given one or more tables and asked to write one or more queries to retrieve, edit, or remove data from those tables.
The difficulty of questions will likely vary based on the company and the role (entry-level vs. advanced). In general, you should be comfortable writing queries using the following concepts, statements, and clauses:
Categorization, aggregation, and ratio (CASE, COUNT, or SUM, numerator and denominator)
Joining two tables (JOIN inner vs. left or right)
Modifying a database (INSERT, UPDATE, and DELETE)
Comparison operators (Less than, greater than, equal to)
Organizing data (ORDER BY, GROUP BY, HAVING)
Given a table or tables with a few sample rows,
List the three stores with the highest number of customer transactions.
Extract employee IDs for all employees who earned a three or higher on their last performance review.
Calculate the average monthly sales by product displayed in descending order.
Find and remove duplicates in the table without creating another table.
Identify the common records between two tables.
In addition to the process above, here are some tips to keep in mind when you’re in your SQL interview.
Talk through your process out loud. Your interviewer may or may not know SQL themselves, so be sure to explain the what, how, and why of each step.
Include written comments as to what each step of your query is meant to accomplish. This can help you keep track of where you are in the problem, and it can make your code easier to understand. If you’re coding in a live environment, you can type comments using a double hash (--). On a whiteboard, write your comments off to the side.
Use correct formatting. While your ability to problem solve is more important than precise syntax, you can avoid confusing the interviewer (and yourself) by keeping your hand-written code organized.
Embrace the awkwardness. It’s okay if the room is silent while you think through a problem. As you’re thinking out loud, you may find yourself re-starting sentences with a better way to explain something. That’s okay too.
Read more: How to Prepare for an Interview
Sometimes the best way to keep nerves calm before an interview is to walk into the screening with a clear plan of action. No matter what type of query you’re asked to write, you can use this six-step process to organize your thoughts and guide you to a solution, even when you’re feeling nervous.
1. Restate the question to make sure you understand what you’re being asked to do.
2. Explore the data by asking questions. What data type is in each column? Do any columns contain unique data (such as user ID)?
3. Identify the columns you’ll need to solve the problem. This helps you focus on the data that matters so you’re not distracted by the data that is irrelevant to the query.
4. Think about what your answer should look like. Are you looking for a single value or a list? Will the answer be the result of a calculation? If so, should it be a float or an integer? Do you need to account for this in your code?
5. Write your code one step at a time. It can help to outline your approach first. By writing down the steps you plan to take, you’ll have a clear outline once you start writing your query (and you’ll give the interviewer a chance to correct you if there’s an issue with your approach).
Then code in increments, taking one step of your outline at a time. After you’re happy with your code for the first step, build onto that code with the second step.
6. Explain your solution as a whole. If there’s a more efficient way you could have written your code—using subqueries for example—explain that. And remember to answer the original question.
If you’re looking for more SQL interview prep, here are some free resources where you can practice writing queries.
HackerRank: This site lets you practice in many different coding languages, including SQL. Each challenge comes with a difficulty score and a success rate, so you can gradually move to more complex queries.
Codewars: When you practice on CodeWars, you can compare your solutions with other users to improve the efficiency of your queries.
LeetCode: Use the database problem sets to practice queries ranging from easy to hard, and track how many you’ve successfully solved.
TestDome: Practice on the same interview questions used by thousands of real companies.
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Data analysts use SQL to communicate with relational databases. As a data analyst, you can use SQL to access, read, change, delete, or analyze data to help generate business insights.
SQL is generally considered to be one of the easier coding languages to learn. The structure and syntax of SQL is based on the English language, so it’s relatively easy to read and understand. You can also do a lot by learning a few basic commands, like SELECT, UPDATE, INSERT, and DELETE. Read up on tips for rising to the challenge.
SQL is typically considered simpler and narrower in scope than Python. If you’re new to writing code, SQL makes an excellent, beginner-friendly first language. Having said that, it’s also totally fine to learn Python first, or learn the two languages simultaneously.
Read more: Python or R for Data Analysis: Which Should I Learn?
As you learn SQL, you’ll use five different types of commands:
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