11 Conagra Brands SQL Interview Questions (Updated 2024)
Conagra Brands employees use SQL to analyze consumer behavior patterns, helping them understand which products are popular and when customers are most likely to buy. It also allows them to optimize their supply chain, ensuring that in-demand items are always in stock, this is why Conagra Brands uses SQL problems during interviews for Data Analytics, Data Science, and Data Engineering jobs.
So, to help you study, we've collected 11 Conagra Brands SQL interview questions – able to solve them?
11 Conagra Brands SQL Interview Questions
SQL Question 1: Find the VIP users for Conagra Brands.
Conagra Brands is a packaged foods company. Let's assume that they have a reward membership system and they categorize their power users or VIP users based on the purchase history within a specific time duration, in this case, let's say, last 6 months.
We would focus on customers who spent the most money and made the most purchases, as these would be the most valuable customers for Conagra Brands.
Example Input:
| user_id | name | membership_date |
|---|---|---|
| 123 | Alice | 01/03/2021 |
| 265 | Bob | 05/10/2020 |
| 362 | Charlie | 06/10/2021 |
Example Input:
| purchase_id | user_id | purchase_date | product_id | amount_spent |
|---|---|---|---|---|
| 9082 | 123 | 05/01/2022 | 511 | 250.5 |
| 6785 | 123 | 05/03/2022 | 511 | 300.75 |
| 2894 | 265 | 05/06/2022 | 520 | 100.25 |
| 3920 | 362 | 05/09/2022 | 511 | 500.85 |
| 4502 | 123 | 05/11/2022 | 515 | 200.95 |
Answer:
This SQL query joins the and tables on . The clause filters out the purchases made in the last 6 months. The clause groups the result set by and , and it calculates the sum of and the total number of made by each user. The clause sorts the result set in descending order first by the total , and then by the total number of . The clause restricts the result set to the top 10 users, giving us the top 10 power users.
To practice a similar VIP customer analysis question on DataLemur's free interactive coding environment, try this Microsoft SQL Interview problem:
Discover how Conagra Brands is enhancing its artificial intelligence capabilities with a human-centered approach in their latest news release! Understanding Conagra's focus on technology can help you appreciate the role of innovation in improving food products and services.
SQL Question 2: Department vs. Company Salary
Assume you had a table of Conagra Brands employee salary data, along with which department they belonged to. Write a query to compare the average salary of employees in each department to the company's average salary. 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.
Code your solution to this interview question and run your code right in DataLemur's online SQL environment:
The answer is LONG – 30+ lines of SQL. You can find a step-by-step solution with hints here: Department Salaries.
SQL Question 3: How is a foreign key different from a primary key in a database?
To explain the difference between a primary key and foreign key, let's start with some data from Conagra Brands's marketing analytics database which stores data from Google Ads campaigns:
:
| ad_id | campaign_id | keyword | click_count |
|---|---|---|---|
| 1 | 100 | Conagra Brands pricing | 10 |
| 2 | 100 | Conagra Brands reviews | 15 |
| 3 | 101 | Conagra Brands alternatives | 7 |
| 4 | 101 | buy Conagra Brands | 12 |
In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.
could be a foreign key. It references the of the Google Ads campaign that each ad belongs to, establishing a relationship between the ads and their campaigns. This foreign key allows you to easily query the table to find out which ads belong to a specific campaign, or to find out which campaigns a specific ad belongs to.
It is also possible for a table to have multiple foreign keys that reference different primary keys in other tables. For example, the table could have additional foreign keys for the of the ad group that each ad belongs to, and the of the Google Ads account that the campaigns belong to.
SQL Question 4: Analyzing Product Reviews Over Time at Conagra Brands
As an analyst at Conagra Brands, one of your tasks is to analyze the user reviews of various products over time. You are given a data set containing product reviews from different users at different times. Your task is to write a SQL query to compute the following:
- For each month, calculate the average rating (stars) each product has received. Take note that some products may not have received any reviews in certain months.
Here is the schema of the 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 |
The expected output is:
Example Output:
| mth | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
This query first groups records by product_id and the month of the review submission. It then computes the average star rating for each group using an window function that is partitioned by the same columns. The result is a list of average product ratings for each month. Note that PostgreSQL's function is used to derive the month of the review from the submit_date.
To practice a related window function SQL problem on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:
SQL Question 5: Name the different types of joins in SQL. What does each one do?
Joins in SQL allow you to combine data from different tables based on a shared key or set of keys.
Four JOIN types are available in SQL. For an example of each one, say you had sales data exported from Conagra Brands's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .
- : retrieves rows from both tables where there is a match in the shared key or keys. For example, an between the table and the table would retrieve only the rows where the in the table matches the in the table.
- : retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the table). If there is no match in the right table, values will be returned for the right table's columns.
- : retrieves all rows from the right table (in this case, the table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
- : retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
SQL Question 6: Analyzing Sales for Conagra Brands
Conagra Brands is a leading branded food company that wants to analyze its sales data. The company sells multiple products across various categories in different stores throughout the U.S. They would like to understand sales trends across different stores and products.
Specifically, they want to know which store sold the highest number of each product in the most recent month. In cases of a tie, the store with the earliest sales date for that specific product should be chosen.
For this exercise, assume that we have a sales table and a products table structured as below:
Example Input:
| product_id | product_name | category |
|---|---|---|
| 345 | Lamb Weston | Frozen |
| 1345 | Healthy Choice | Packaged |
| 2012 | Orville Redenbacher | Snacks |
| 5065 | Slim Jim | Snacks |
| 1250 | Banquet | Frozen |
Example Input:
| sale_id | store | product_id | sale_date | quantity |
|---|---|---|---|---|
| 1121 | Walmart | 345 | 06/01/2022 | 12 |
| 2436 | Costco | 345 | 06/02/2022 | 14 |
| 5432 | Walmart | 1345 | 06/08/2022 | 10 |
| 8654 | Target | 2012 | 06/01/2022 | 16 |
| 7531 | Costco | 5065 | 06/15/2022 | 14 |
Your task is to write a SQL query using PostgreSQL syntax that returns the product name, the store that sold the maximum quantity of each product, and the quantity sold of each product in the most recent month.
Answer:
This query first creates a monthly_sales CTE that calculates the total sales for each product in each store for the most recent month, and assigns a rank for each product based on the total sales and earliest sale date.
The main query then joins the monthly_sales CTE with the products table on product_id, and selects the records where rank is 1, i.e., the store that sold the maximum quantity of each product. The result is the product name, the store, and the quantity sold of each product for the top selling store.
SQL Question 7: What is denormalization?
Database denormalization is when you add redundancy to a database, and break typical normalization rules (codified by the 1st, 2nd, 3rd normal forms).
Denormalization is typically used to improve the performance of a database, particularly when the database is being for OLAP (Online Analytical Processing) purposes. By denormalizing a database, you can reduce the number of joins that are required to retrieve data, which can greatly improve the speed of queries since joins are costly and slow. However, denormalization can also introduce some problems, such as increased data redundancy and the need for more complex update and delete operations since data has been duplicated into multiple tables.
In general, denormalization should be used with caution and only after careful consideration of the trade-offs involved. It's typically better to start with a well-normalized database design then denormalize only if your database isn't scaling as well as you want.
SQL Question 8: Calculate the Average Quantity of Products Shipped per Month
Conagra Brands, Inc. is an American packaged foods company. Its headquarters is located in Chicago, Illinois. Conagra produces and markets packaged food products for retail consumers, restaurants, and institutions.
Given a database table , where each row corresponds to a specific shipment containing a product id, the quantity, and the date of the shipment; can you write a SQL query to find the average quantity of each product shipped per month?
Example Input:
| shipment_id | product_id | date | quantity |
|---|---|---|---|
| 101 | 9782 | 01/02/2022 | 200 |
| 102 | 6452 | 01/15/2022 | 150 |
| 103 | 9782 | 02/04/2022 | 250 |
| 104 | 6452 | 02/20/2022 | 300 |
| 105 | 9782 | 03/01/2022 | 100 |
Example Output:
| month | product_id | avg_quantity |
|---|---|---|
| 1 | 9782 | 200.00 |
| 1 | 6452 | 150.00 |
| 2 | 9782 | 250.00 |
| 2 | 6452 | 300.00 |
| 3 | 9782 | 100.00 |
Answer:
In the above SQL query, the function is used to extract the month from the shipment date. It then groups the result by and , calculates the average quantity using function. Finally, sorts the result by and .
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for analyzing product quantities or this Walmart Histogram of Users and Purchases Question which is similar for handling transactional data.
SQL Question 9: Calculate product click-through conversion rate for Conagra Brands.
Conagra Brands wants to analyze their digital marketing performance. Their marketing team has been running multiple campaigns online and they want to track how effective these campaigns are in driving potential customers to click on their ads (click-through rate) and eventually adding the products to the cart (conversion rate).
Given the following sample data, write a SQL query to calculate the click-through conversion rate for each product. For simplicity, let's assume that a campaign_id pertains to a single product. The click-through conversion rate can be calculated as the total number of products added to cart divided by the total number of ad clicks, multiply by 100 to get the rate in percentage.
Here are the tables:
Example Input
| click_id | user_id | click_date | campaign_id |
|---|---|---|---|
| 6457 | 123 | 06/07/2022 00:00:00 | 40001 |
| 9375 | 265 | 06/10/2022 00:00:00 | 40001 |
| 4325 | 362 | 06/18/2022 00:00:00 | 50001 |
| 6543 | 192 | 07/26/2022 00:00:00 | 50001 |
| 5327 | 981 | 07/05/2022 00:00:00 | 40001 |
Example Input
| action_id | user_id | product_id | campaign_id | action | action_date |
|---|---|---|---|---|---|
| 9623 | 123 | 60001 | 40001 | 'add_to_cart' | 06/09/2022 00:00:00 |
| 9842 | 265 | 60001 | 40001 | 'remove_from_cart' | 06/11/2022 00:00:00 |
| 8723 | 362 | 70001 | 50001 | 'add_to_cart' | 06/20/2022 00:00:00 |
| 7642 | 192 | 70001 | 50001 | 'add_to_cart' | 07/28/2022 00:00:00 |
| 9427 | 981 | 60001 | 40001 | 'remove_from_cart' | 07/06/2022 00:00:00 |
Answer:
This query calculates the click-through conversion rate for each product by joining the and tables on and . It filters for actions and divides the total by the total number of , then multiplies by 100 to get the rate in percentage. The results are grouped by and .
To practice a similar problem about calculating rates, try this TikTok SQL question on DataLemur's online SQL code editor:
SQL Question 10: What's an index, and what are the different types?
A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.
There are several types of indexes that can be used in a database:
- Primary index: a unique identifier is used to access the row directly.
- Unique index: used to enforce the uniqueness of the indexed columns in a table.
- Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
- Clustered index: determines the physical order of the data in a table
For a concrete example, say you had a table of Conagra Brands customer payments with the following columns: , , , and .
Here's what a clustered index on the column would look like:
A clustered index on the column would determine the physical order of the records in the table based on the . This means that the records with the earliest values would be stored together physically in the table, followed by records with later values.
Having a clustered index on the column can speed up queries that filter or sort the data based on the , as the records are already physically sorted in the table. For example, if you want to retrieve all the payments made in the month of January, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.
SQL Question 11: Analyzing Sales by Product Per Month
For Conagra Brands, which is a packaged foods company, an important analysis could be understanding the average sales by product per month. Assume you are given a table, which contains transactional data including sale date, product ID, and sale amount. Create an SQL query to calculate the average sales amount of each product for each month based on the data from 2022.
Here's the sample table for sales:
Example Input:
| transaction_id | product_id | sale_date | sale_amount |
|---|---|---|---|
| 74720 | PRD123 | 01/25/2022 | 29.99 |
| 76852 | PRD234 | 01/26/2022 | 35.50 |
| 58937 | PRD123 | 02/28/2022 | 29.99 |
| 63428 | PRD345 | 02/02/2022 | 22.99 |
| 41528 | PRD234 | 03/01/2022 | 35.50 |
Answer:
The PostgreSQL query to calculate the average sales amount per product for each month would look something like this:
This query groups the sales row by month and product ID, computes the average sale amount for every group, and then sorts the result by month and average sale amount in descending order. Remember to replace 'sales' with your actual table name. Added WHERE condition will ensure that only 2022 year sales data are considered.
The output to the question would be something like this:
Example Output:
| month | product_id | avg_sale_amount |
|---|---|---|
| 1 | PRD123 | 29.99 |
| 1 | PRD234 | 35.50 |
| 2 | PRD123 | 29.99 |
| 2 | PRD345 | 22.99 |
| 3 | PRD234 | 35.50 |
Conagra Brands SQL Interview Tips
The key to acing a Conagra Brands SQL interview is to practice, practice, and then practice some more! In addition to solving the earlier Conagra Brands SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Netflix, Google, and Amazon.
Each interview question has hints to guide you, step-by-step solutions and best of all, there's an online SQL coding environment so you can easily right in the browser your SQL query and have it executed.
To prep for the Conagra Brands SQL interview it is also wise to practice interview questions from other food and facilities companies like:
- Hormel Foods SQL questions
- Keurig Dr Pepper SQL questions
- Andersons SQL questions
- Sanderson Farms SQL questions
However, if your SQL coding skills are weak, forget about jumping right into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers topics including handling timestamps and math functions – both of these pop up often in Conagra Brands interviews.
Conagra Brands Data Science Interview Tips
What Do Conagra Brands Data Science Interviews Cover?
Besides SQL interview questions, the other types of problems to practice for the Conagra Brands Data Science Interview are:
- Probability & Statistics Questions
- Python or R Coding Questions
- Product & Business Analytics Questions
- ML Modelling Questions
- Behavioral Interview Questions centered on Conagra Brands cultural values
How To Prepare for Conagra Brands Data Science Interviews?
To prepare for Conagra Brands Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Microsoft, Amazon & startups
- a crash course on Product Analytics, SQL & ML
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Don't ignore the behavioral interview – prepare for that with this guide on behavioral interview questions.