11 Abbott SQL Interview Questions (Updated 2024)
Data Science, Data Engineering, and Data Analytics employees at Abbott write SQL queries to analyze clinical trial data to uncover medical breakthroughs that can lead to innovative treatments. They also rely on SQL to optimize supply chain efficiency, working with large datasets to make sure medical products are delivered where they are needed most, that is why Abbott includes SQL questions in interviews.
So, to help you practice, here’s 11 Abbott Laboratories SQL interview questions – can you solve them?
11 Abbott Laboratories SQL Interview Questions
SQL Question 1: Identifying Power Users of Abbott Products
Abbott is globally recognized for improving health and enhancing lives with a variety of healthcare products. Our primary goal is to make our customer's experience a delightful one, but we also want to understand who our 'power' users are. These are the users who buy our products the most frequently.
You are given a table with columns:
Assume that a 'power' user is someone who has made at least 10 purchases within the last 30 days.
Write a SQL query to identify the 'power' users and list out the top 10 users based on the total .
Example Input:
| sales_id | user_id | purchase_date | product_id | purchase_amount |
|---|---|---|---|---|
| 1015 | 308 | 2022-06-05 | 30010 | $50 |
| 1043 | 542 | 2022-06-18 | 37890 | $25 |
| 1069 | 601 | 2022-07-04 | 30010 | $65 |
| 1082 | 308 | 2022-07-05 | 37890 | $30 |
| 1095 | 542 | 2022-07-19 | 30010 | $50 |
Answer:
This query looks at the table and first filters for sales that have happened in the last 30 days (i.e., those having a between 30 days ago and today). This is done with the clause. Then, for every distinct , it counts the number of sales entries and sums up the total amount spent purchasing our products (). The clause restricts the data set to only include users who have made 10 or more purchases in that period. Lastly, we sort by the total purchase amount in descending order (i.e., highest first) and limit the output to the top 10 users, i.e., the 10 users who have spent the most.
To practice another SQL customer analytics question where you can solve it right in the browser and have your SQL solution automatically checked, try this Walmart Labs SQL Interview Question:
Discover Abbott's insights on the impact of big data in healthcare, showcasing how data analytics is revolutionizing patient care and operational efficiency! Learning about their approach can help you appreciate the role of data in enhancing healthcare delivery and decision-making.
SQL Question 2: Top 3 Salaries
Given a table of Abbott employee salaries, write a SQL query to find the top 3 highest earning employees in each department.
Abbott Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
Check your SQL query for this interview question and run your code right in DataLemur's online SQL environment:
Answer:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the solution above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.
SQL Question 3: What sets the 'BETWEEN' and 'IN' operators apart?
The operator is used to select rows that fall within a certain range of values, while the operator is used to select rows that match values in a specified list.
For example, suppose you are a data analyst at Abbott and have a table of advertising campaign data. To find campaigns with a spend between 5k, you could use BETWEEN:
To find advertising campaigns that were video and image based (as opposed to text or billboard ads), you could use the operator:
SQL Question 4: Calculate Monthly Average Ratings
Given the table which keeps records of product reviews, write a SQL query to calculate the average star rating for each product on a monthly basis.
Order the resulting data by year, month, and then product ID. Assume the date is in format.
Example Input:
|
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 01/15/2020 00:00:00 | 20001 | 4 |
| 7802 | 265 | 01/20/2020 00:00:00 | 10001 | 4 |
| 5293 | 362 | 02/22/2020 00:00:00 | 10001 | 3 |
| 6352 | 192 | 03/28/2020 00:00:00 | 30001 | 3 |
| 4517 | 981 | 03/30/2020 00:00:00 | 10001 | 2 |
Example Output:
| Year | Month | product_id | avg_stars |
|---|---|---|---|
| 2020 | 01 | 10001 | 4.00 |
| 2020 | 01 | 20001 | 4.00 |
| 2020 | 02 | 10001 | 3.00 |
| 2020 | 03 | 10001 | 2.00 |
| 2020 | 03 | 30001 | 3.00 |
Answer:
For every product in each month of a year, we calculate the average rating () by group by Year, Month, and . The function is used to obtain the month and year from the . The result is ordered by Year, Month, and product_id in ascending order.
To practice another window function question on DataLemur's free interactive coding environment, try this Google SQL Interview Question:
SQL Question 5: How do the window functions LEAD() and LAG() differ?
Both window functions are used to find rows at a given offset from the current row. However, will give you the rows AFTER the current row you. On the other hand, will give you the rows BEFORE the current row.
SQL Question 6: Tracking Inventory Replenishment Across Abbott's Distribution Centers
The company has several distribution centers across the country. Each distribution center stocks multiple products.
The company is interested in understanding how often each product gets replenished at each distribution center to help streamline their operations.
Abbott has shared the following tables:
:
| center_id | center_name | location |
|---|---|---|
| 1 | DC East | New York |
| 2 | DC West | California |
| 3 | DC North | Washington |
| 4 | DC South | Texas |
:
| product_id | product_name |
|---|---|
| 100 | Ensure Nutrition Shake |
| 200 | Pedialyte Rehydration Drink |
| 300 | Glucerna Shake |
:
| replenishment_id | center_id | product_id | replenishment_date | quantity_replenished |
|---|---|---|---|---|
| 5001 | 1 | 100 | 01/02/2022 | 500 |
| 5002 | 1 | 200 | 01/03/2022 | 300 |
| 5003 | 1 | 300 | 01/04/2022 | 400 |
| 5004 | 2 | 100 | 01/05/2022 | 600 |
| 5005 | 2 | 200 | 01/06/2022 | 800 |
Based on the data provided, write a SQL query to find the average number of each product replenished at each distribution center every month.
Answer:
This query uses the function to get the month part of the date from the column and the function to calculate the average quantity replenished for each product at each distribution center. It also uses to combine data from all three tables. The statement groups the result set by month, distribution center name, and product name. The final result is ordered by month, distribution center name, and product name.
SQL Question 7: Can you explain what SQL constraints are, and why they are useful?
SQL constraints are used to specify rules for the data in a table. They can be applied to single or multiple fields in a table when the table is created, or after the table has been created using the ALTER TABLE command.
For example, say you had a database that stores ad campaign data from Abbott's Google Analytics account.
Here's what some constraints could look like:
SQL Question 8: Filtering Customer's from Abbott's database
Abbott is a globally recognized health care company. Their customer database spans millions of records. Your task is to create a PostgreSQL query that denies access to customers under the age of 18 or those located outside the United States. Additionally, the output should only include customers who have been active in the past 6 months.
Consider a table with columns: , , , and :
Example Input:
| customer_id | age | country | last_active_date |
|---|---|---|---|
| 1 | 22 | USA | 2022-08-25 |
| 2 | 35 | Canada | 2022-06-20 |
| 3 | 17 | USA | 2022-02-15 |
| 4 | 45 | Mexico | 2021-11-10 |
| 5 | 31 | USA | 2022-09-01 |
The filtered output table should be:
Example Output:
| customer_id | age | country | last_active_date |
|---|---|---|---|
| 1 | 22 | USA | 2022-08-25 |
| 5 | 31 | USA | 2022-09-01 |
Answer:
The SQL query uses a WHERE clause to apply multiple conditions. The operator is used to ensure customers are at least 18 years old. The comparison operator checks if the customer is in the USA. Finally, the customer's should be within the last 6 months, which is accomplished by subtracting 6 months from the current date () and using the operator. The AND operator is used to combine these conditions, ensuring all must be true for a record to be included in the result.
SQL Question 9: Calculating Average Sold Units Per Product Category
Abbott is a global healthcare company that offers a diverse range of products such as medical devices, nutritional products, diagnostics, and generic pharmaceuticals. As a data analyst, you're asked to calculate the average number of units sold per product category each month.
Assume you have two tables, and , structured as follows:
Example Input:
| sale_id | product_id | sale_date | units_sold |
|---|---|---|---|
| 1 | A1 | 01/08/2021 | 100 |
| 2 | A2 | 01/08/2021 | 150 |
| 3 | B1 | 01/08/2021 | 200 |
| 4 | A1 | 01/09/2021 | 300 |
| 5 | B1 | 01/10/2021 | 400 |
Example Input:
| product_id | product_category |
|---|---|
| A1 | Nutrition |
| A2 | Nutrition |
| B1 | Diagnostics |
You are expected to provide the output in the following format:
Example Output:
| mth | category | avg_units |
|---|---|---|
| 8 | Nutrition | 125.00 |
| 8 | Diagnostics | 200.00 |
| 9 | Nutrition | 300.00 |
| 10 | Diagnostics | 400.00 |
Answer:
In PostgreSQL, you would write the following query to solve this problem:
This query first joins the and tables on . Then, it groups by month () and . Finally, it calculates the average for each group. The function is used to get the month part from .
SQL Question 10: What does do?
If you have two tables and want to retrieve only the rows that are present in both tables, just use the operator!
For example, let's use to find all of Abbott's Facebook video ads that are also being run on YouTube:
SQL Question 11: Filter Customer Records
As a data analyst at Abbott, one of your roles is to retrieve specific customer data from the database. There are times when the marketing team wants to target customers who have certain characteristics in their records. The task involves filtering customer records based on specific conditions.
Suppose the marketing team wants you to retrieve the data of customers whose first name begins with 'St' and whose addresses contain the word 'Street'.
Data in the table are as follows:
Example Input:
| customer_id | first_name | last_name | address |
|---|---|---|---|
| 1257 | John | Doe | 123 Maple Road |
| 8325 | Steve | Smith | 456 Oak Street |
| 4928 | Stacy | Johnson | 789 Pine Street |
| 6891 | Matt | Brown | 147 Willow Avenue |
Based on the given conditions, the filtered records should be as follows:
Example Output:
| customer_id | first_name | last_name | address |
|---|---|---|---|
| 8325 | Steve | Smith | 456 Oak Street |
| 4928 | Stacy | Johnson | 789 Pine Street |
Answer:
Here is a PostgreSQL query to find the required data:
This PostgreSQL query uses the SQL LIKE keyword to filter the data. It selects all the columns from the customers table where the first_name starts with 'St' and the address contains the word 'Street'. The '%' is a wildcard character in SQL that matches any sequence of characters. In the query, 'St%' will match any string that starts with 'St', and '%Street%' will match any string that contains 'Street'.
Preparing For The Abbott SQL Interview
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Beyond just solving the above Abbott SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Amazon, JP Morgan, and healthcare and pharmaceutical companies like Abbott.
Each DataLemur SQL question has hints to guide you, detailed solutions and best of all, there's an interactive SQL code editor so you can instantly run your SQL query answer and have it checked.
To prep for the Abbott SQL interview it is also a great idea to practice SQL problems from other healthcare and pharmaceutical companies like:
But if your SQL skills are weak, forget about jumping right into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers topics including LEFT vs. RIGHT JOIN and removing NULLs – both of which show up often during Abbott interviews.
Abbott Laboratories Data Science Interview Tips
What Do Abbott Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories to practice for the Abbott Data Science Interview are:
- Stats Interview Questions
- Python or R Coding Questions
- Product-Sense Questions
- ML Interview Questions
- Behavioral Questions based on Abbott culture and values
How To Prepare for Abbott Data Science Interviews?
To prepare for Abbott Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from Facebook, Google & startups
- a crash course on SQL, AB Testing & ML
- over 1000+ 5-star reviews on Amazon
Don't forget about the behavioral interview – prep for it using this guide on behavioral interview questions.