10 Dana SQL Interview Questions (Updated 2024)
Data Analysts and Data Scientists at Dana write SQL queries for analyzing employee performance data, allowing them to identify areas for improvement and recognize top performers. They also manage HR databases for efficient information retrieval, making it easier to access important employee records, for this reason, Dana asks jobseekers with SQL coding interview questions.
Thus, to help you prepare, here's 10 Dana Incorporated HR SQL interview questions – can you solve them?
10 Dana Incorporated HR SQL Interview Questions
SQL Question 1: Identifying Top Purchasing Customers
For Dana, a company that sells various products, one of the most important activities for their business would be the purchasing of products. Specifically, they might be interested in identifying customers who frequently purchase high quantities, as these customers could be considered their VIPs or "whale users". Therefore, a relevant SQL interview question could be:
Write a SQL query that identifies the top 5 customers with the highest total quantity of purchases in the past 12 months.
Here is some sample data:
Example Input:
| purchase_id | customer_id | purchase_date | product_id | quantity |
|---|---|---|---|---|
| 2156 | 34 | 01/06/2021 | 982 | 5 |
| 8395 | 86 | 07/10/2021 | 1034 | 10 |
| 9384 | 34 | 02/08/2021 | 982 | 15 |
| 4639 | 220 | 07/20/2021 | 758 | 20 |
| 9682 | 315 | 12/15/2021 | 1034 | 25 |
Given this question, a possible solution query could be:
Answer:
In this query, we first filter the purchases for those that occurred within the past year. We then group by customer_id, and for each customer, we sum the quantities of their purchases. Finally, we order the results by the summed quantity in descending order and limit the number of results to 5. As a result, we obtain the top 5 customers who have purchased the highest quantities within the past year.
To practice a similar customer analytics SQL question where you can solve it interactively and have your SQL code automatically checked, try this Walmart Labs SQL Interview Question:
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SQL Question 2: Department Salaries
Suppose you had a table of Dana employee salary data, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary for March 2024. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
You can solve this interview question and run your code right in DataLemur's online SQL environment:
The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution here: Department vs. Company Salary.
SQL Question 3: How does the constraint function, and in what scenarios might it be useful?
The constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the constraint's rule, the operation will fail.
For example, say you had a database that stores ad campaign data from Dana's Google Analytics account.
Here's what some constraints could look like:
In this example, the constraint is used to ensure that the "budget" and "cost_per_click" fields have positive values. This helps to ensure that the data in the database is valid and makes sense in the context of ad campaigns.
You can also use the constraint to ensure that data meets other specific conditions. For example, you could use a constraint to ensure that the "start_date" is before the "end_date" for each ad campaign.
SQL Question 4: Calculate Monthly Average Rating per Product
Dana's company runs an e-commerce website where customers can buy products and write a review. Every product review includes a rating between 1-5 stars. The product and review data are stored in a single table called 'reviews'.
Your task is to write a SQL query that calculates the monthly average star rating per product, sorted by month in ascending order and then by product id in ascending order.
If a product has more than one review in a single month, the monthly average for that product should be the average of all reviews in that month.
Consider the following data in 'reviews' table:
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Example Output:
| month | product | avg_rating |
|---|---|---|
| June | 50001 | 3.50 |
| June | 69852 | 4.00 |
| July | 69852 | 2.50 |
Answer:
This PostgreSQL query first groups the reviews by the month of the and . The PostgreSQL function is used to convert the , which is of date type, to the textual name of the month. The function then calculates the average (or ratings) for each group (i.e., for each month per product). The resulting output is then ordered by the month (in ascending order) and then by (in ascending order).
To solve a similar window function question on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:
SQL Question 5: What distinguishes an inner join from a full outer join?
An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.
For example, suppose you had a table of Dana orders and Dana customers.
INNER JOIN: When there is a match in the shared key or keys, rows from both tables are retrieved. In this example, an between the Orders and Customers tables would retrieve rows where the in the Orders table matches the in the Customers table.
FULL OUTER JOIN: A retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.
SQL Question 6: Filter Customers with Certain Purchases
Dana is working with a database of customers' purchase history for her company. She needs to write a query that will filter down the customers who bought products from a certain "Toy" category or who made purchases worth more than $200 in total during January 2021.
Example Input:
| purchase_id | customer_id | purchase_date | product_category | purchase_value |
|---|---|---|---|---|
| 1001 | 569 | 01/15/2021 | Toys | 150 |
| 1002 | 265 | 01/20/2021 | Electronics | 500 |
| 1003 | 569 | 01/28/2021 | Groceries | 100 |
| 1004 | 117 | 01/31/2021 | Toys | 120 |
| 1005 | 265 | 02/10/2021 | Toys | 110 |
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 569 | John | Doe |
| 265 | Jane | Smith |
| 117 | Luke | Mann |
Use these tables to write your SQL query.
Answer:
Here is a PostgreSQL query for this problem.
This query first selects the customers who either bought 'Toys' or made purchases worth more than $200 in January 2021. Then it gets the first name and last name of these customers from the table.
SQL Question 7: What are the various types of joins used in SQL?
In SQL, a join is used to combine rows from different tables based on a shared key or set of keys, resulting in a single merged table of data.
There are four distinct types of JOINs: , , , and .
(INNER) JOIN: Retrieves records that have matching values in both tables involved in the join.
LEFT (OUTER) JOIN: Retrieves all the records/rows from the left and the matched records/rows from the right table.
RIGHT (OUTER) JOIN: Retrieves all the records/rows from the right and the matched records/rows from the left table.
FULL (OUTER) JOIN: Retrieves all the records where there is a match in either the left or right table.
SQL Question 8: Calculating Click-Through Rates for Dana's Digital Ads
Assume Dana, a digital product company, runs multiple ad campaigns on its website. It wants to measure the effectiveness of these campaigns by analyzing click-through rates and conversion rates for their products.
The following tables represent this scenario:
Example Input:
| ad_id | user_id | click_date |
|---|---|---|
| 111 | 123 | 06/08/2022 00:00:00 |
| 222 | 265 | 06/10/2022 00:00:00 |
| 111 | 362 | 06/18/2022 00:00:00 |
| 333 | 192 | 07/26/2022 00:00:00 |
| 222 | 981 | 07/05/2022 00:00:00 |
Example Input:
| product_id | user_id | view_date |
|---|---|---|
| 50001 | 123 | 06/08/2022 00:00:00 |
| 69852 | 265 | 06/10/2022 00:00:00 |
| 50001 | 362 | 06/18/2022 00:00:00 |
| 69852 | 192 | 07/26/2022 00:00:00 |
| 69852 | 981 | 07/05/2022 00:00:00 |
Example Input:
| product_id | user_id | add_to_cart_date |
|---|---|---|
| 50001 | 123 | 06/08/2022 00:00:00 |
| 69852 | 265 | 06/11/2022 00:00:00 |
| 50001 | 362 | 06/19/2022 00:00:00 |
| 69852 | 192 | 07/26/2022 00:00:00 |
Assuming, we want to calculate the click-through rate and conversion rates for ad_id 111 in the month of June 2022. 'Click-through rate' is the proportion of users who clicked an ad (from the table) and viewed a product (from the table), while 'conversion rate' is the proportion of those users who further added a product to the cart (from the table).
Answer:
Assuming that dates in , and are of timestamp data type, the following query calculates the click-through rate and conversion rate for the ad_id 111 for the month June 2022:
In the above SQL block, 3 CTEs (, , and ) are used to generate necessary counts used in the main query to calculate required rates by dividing relevant counts with the total count of clicks for ad_id 111. This query returns a single row, containing the click-through rate and conversion rate for June 2022.
To solve a similar problem about calculating rates, try this SQL interview question from TikTok on DataLemur's interactive coding environment:
SQL Question 9: Filter Customer Records in the Database
Dana Inc., a multinational company, maintains a database of their customers. You have been given the task to extract customers whose last name starts with 'Smith'. Create an SQL query to accomplish this task.
Example Input:
| customer_id | first_name | last_name | phone | country | |
|---|---|---|---|---|---|
| 101 | John | Smith | john.smith@email.com | 1234567890 | USA |
| 102 | Jane | Jones | jane.jones@email.com | 2345678901 | USA |
| 103 | Adam | Smithy | adam.smithy@email.com | 3456789012 | USA |
| 104 | Sarah | Smith | sarah.smith@email.com | 4567890123 | USA |
| 105 | Jack | Jacobs | jack.jacobs@email.com | 5678901234 | USA |
Answer:
Here is a PostgreSQL query which can return customers whose last name starts with 'Smith':
This query uses the LIKE operator to filter customer records based on the pattern. The '%' sign is a wildcard character that represents zero, one, or multiple characters. In this case, it will match any last name that starts with 'Smith'.
Example Output:
| customer_id | first_name | last_name | phone | country | |
|---|---|---|---|---|---|
| 101 | John | Smith | john.smith@email.com | 1234567890 | USA |
| 104 | Sarah | Smith | sarah.smith@email.com | 4567890123 | USA |
SQL Question 10: What sets relational and NoSQL databases apart?
A non-relational (NoSQL) database is any database that does not use the typical tabular format of rows and columns like in relational databases.
While knowing the four different types of NoSQL databases is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Dana should vaguely refresh these concepts:
- Document Databases – this database is designed for storing and querying retrieving document data (where each key is associated with a flexible document)
- Key-Value Stores – these databases uses keys where each key is associated with only one value in a collection (similar to a Python dictionary data structure!)
- Wide-Column Stores – this database uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row within the same table. Remember: "-With great flexibility comes great responsiblity-" – Batman if he was learning about NoSQL databases!
- Graph Stores – represents data in terms of the graph data structure, with nodes and edges between entities
Dana SQL Interview Tips
The key to acing a Dana SQL interview is to practice, practice, and then practice some more! Besides solving the above Dana SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Microsoft, Google, and Meta.
Each exercise has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an interactive SQL code editor so you can right in the browser run your query and have it checked.
To prep for the Dana SQL interview you can also be helpful to solve interview questions from other healthcare and pharmaceutical companies like:
In case your SQL coding skills are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers SQL topics like filtering strings based on patterns and using ORDER BY – both of which come up frequently during Dana interviews.
Dana Incorporated HR Data Science Interview Tips
What Do Dana Data Science Interviews Cover?
In addition to SQL query questions, the other question categories to practice for the Dana Data Science Interview include:
- AB Testing Questions
- Python or R Coding Questions
- Business Sense and Product-Sense Questions
- ML Modelling Questions
- Behavioral Questions focussed on Dana cultural values
How To Prepare for Dana Data Science Interviews?
To prepare for Dana Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from companies like Microsoft, Google & Amazon
- a crash course on SQL, Product-Sense & ML
- over 1000+ 5-star reviews on Amazon
Don't forget about the behavioral interview – prepare for that with this guide on behavioral interview questions.