Jabil employees use SQL for analyzing manufacturing processes, identifying inefficiencies, and managing supply chain data for improved logistics. It is also used for product quality control, such as monitoring inventory levels and shipment schedules, which is why Jabil asks SQL problems during interviews for Data Analytics, Data Science, and Data Engineering jobs.
So, to help you prep for the Jabil SQL interview, we've curated 11 Jabil SQL interview questions in this article.
Jabil is a manufacturing solutions provider with a lot of clients ordering products very often. For this SQL interview question, the goal is to write a query that identifies the top consumers who have placed the most frequent orders within a certain period (e.g., past 6 months or 1 year). This will help Jabil understand who its top customers (or power users / VIP users) are.
For this problem, we will assume that there are two tables: and .
customer_id | name | register_date |
---|---|---|
101 | Alice | 08/10/2021 |
102 | Bob | 06/15/2021 |
103 | Carol | 04/20/2021 |
104 | David | 01/01/2022 |
105 | Ethan | 12/20/2021 |
order_id | customer_id | product_id | quantity | order_date |
---|---|---|---|---|
2010 | 101 | IND1 | 5 | 09/01/2021 |
2020 | 102 | IND2 | 2 | 08/20/2021 |
2030 | 103 | IND3 | 3 | 06/15/2021 |
2040 | 101 | IND2 | 6 | 09/05/2021 |
2050 | 101 | IND1 | 7 | 09/20/2021 |
customer_id | name | total_orders |
---|---|---|
101 | Alice | 3 |
In this SQL query, we first join the and tables using the column as the key. After this, we filter out the orders placed within a desired date range. Then, we perform an aggregation () based on and to get the count of orders each customer has placed. Finally, we order the resulting rows by in descending order, and limit the result to the top 5. This gives us the top 5 customers who placed the most orders within the specified time period.
To solve a super-customer analysis question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:
Assume you had a table of Jabil 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.
Code your solution to this question directly within the browser on DataLemur:
The solution is LONG – 30+ lines of SQL. You can find a detailed solution here: Department vs. Company Salary.
A join in SQL combines rows from two or more tables based on a shared column or set of columns. To demonstrate the difference between a and , say you had a table of Jabil orders and Jabil customers.
LEFT JOIN: A retrieves all rows from the left table (in this case, the Orders table) and any matching rows from the right table (the Customers table). If there is no match in the right table, NULL values will be returned for the right table's columns.
RIGHT JOIN: A retrieves all rows from the right table (in this case, the Customers table) and any matching rows from the left table (the Orders table). If there is no match in the left table, NULL values will be returned for the left table's columns.
You are given a dataset that stores the information of all the products sold by Jabil in a given period. The attribute of the dataset include the sales id, date, product id and the quantity that has been sold. Write a SQL query to create a new table that shows the average quantity of the each product sold in each month.
sales_id | date | product_id | quantity |
---|---|---|---|
101 | 2022-06-01 | 1001 | 200 |
102 | 2022-06-05 | 1002 | 100 |
103 | 2022-06-20 | 1001 | 400 |
104 | 2022-07-15 | 1002 | 150 |
105 | 2022-07-19 | 1001 | 300 |
month | product_id | avg_quantity |
---|---|---|
6 | 1001 | 300.00 |
6 | 1002 | 100.00 |
7 | 1001 | 300.00 |
7 | 1002 | 150.00 |
This query uses the window function in combination with to calculate the average quantity sold for each product in each month. The is used to get the month from the date column. We partition by both the month and the product_id, and finally order the result by month and product_id.
For more window function practice, try this Uber SQL Interview Question within DataLemur's interactive SQL code editor:
To find records in one table that aren't in another, you can use a and check for values in the right-side table.
Here's an example using two tables, Jabil employees and Jabil managers:
This query returns all rows from Jabil employees where there is no matching row in managers based on the column.
You can also use the operator in PostgreSQL and Microsoft SQL Server to return the records that are in the first table but not in the second. Here is an example:
This will return all rows from employees that are not in managers. The operator works by returning the rows that are returned by the first query, but not by the second.
Note that isn't supported by all DBMS systems, like in MySQL and Oracle (but have no fear, since you can use the operator to achieve a similar result).
Jabil, a leading electronics manufacturing company, has been facing challenges in maintaining its inventory. They wish to setup a new database to efficiently track their different products across various branches globally. Create a database model observing the following:
product_id | product_name | purchase_price | selling_price | manufacturer_name |
---|---|---|---|---|
1 | Product A | 10 | 15 | Manufacturer X |
2 | Product B | 20 | 30 | Manufacturer Y |
3 | Product C | 35 | 50 | Manufacturer Z |
branch_id | branch_name | location |
---|---|---|
1 | Branch A | Location X |
2 | Branch B | Location Y |
3 | Branch C | Location Z |
branch_id | product_id | units |
---|---|---|
1 | 1 | 100 |
2 | 1 | 45 |
2 | 2 | 30 |
3 | 3 | 80 |
This query joins the relevant tables and filters out records where the number of units is less than 50. The output will list the product's name, the branch's name, and its location where any product has less than 50 units. This is essential data for strategic restocking, enabling Jabil to maintain optimal inventory levels across various global branches.
While both types of databases are used to store data (no duh!), relational databases and non-relational (also known as NoSQL databases) differ in a few important ways:
Data model: Relational databases use a data model consisting of tables and rows, while NoSQL databases use a variety of data models, including document, key-value, columnar, and graph storage formats.
Data integrity: Relational databases use structured query language (SQL) and enforce strict data integrity rules through the use of foreign keys and transactions. NoSQL databases may not use SQL and may have more relaxed data integrity rules.
Structure: Relational databases store data in a fixed, structured format, while NoSQL databases allow for more flexibility in terms of data structure.
ACID compliance: Relational databases are typically into shrooms and are ACID-compliant (atomic, consistent, isolated, and durable), while NoSQL databases may not be fully ACID-compliant (but they try their best... and it's effort that counts...or at least that's what my gym teacher told me!)
As an analyst at Jabil corporation, you have been given access to the customer records database. Your task is to write an SQL query for filtering the data to find all customers from the U.S. who have purchased electronic products more than five times in the last six months.
Here are relevant portions of the and tables:
customer_id | first_name | last_name | country |
---|---|---|---|
101 | Jane | Doe | USA |
102 | John | Smith | UK |
103 | Emily | Johnson | USA |
104 | Robert | Jones | Canada |
purchase_id | customer_id | product_category | purchase_date |
---|---|---|---|
2001 | 101 | Electronics | 2022-01-01 |
2002 | 101 | Electronics | 2022-02-01 |
2003 | 101 | Electronics | 2022-03-01 |
2004 | 101 | Electronics | 2022-04-01 |
2005 | 101 | Electronics | 2022-05-01 |
2006 | 102 | Electronics | 2022-05-01 |
2007 | 103 | Fashion | 2022-06-01 |
2008 | 104 | Electronics | 2022-06-01 |
This query joins the and tables on , and then filters to only include records where the country is 'USA', the product category is 'Electronics', and the purchase date is within the last six months. It then groups by the customer ID and counts the number of purchases per customer, only returning the results where the count is greater than 5.
You are a data analyst at Jabil, a leading tech company. The marketing team runs several digital advertising campaigns to attract potential customers. They are interested in understanding the click-through rates (CTR) of their campaigns to optimize their performance.
For simplicity, let's assume the following:
You are provided with the two tables outlined below:
ad_click_id | user_id | click_time | ad_id |
---|---|---|---|
101 | 301 | 2023-01-10 21:13:00 | 1 |
102 | 302 | 2023-01-11 20:30:00 | 1 |
103 | 303 | 2023-01-12 15:23:00 | 1 |
104 | 304 | 2023-01-13 12:23:00 | 2 |
105 | 305 | 2023-01-13 14:25:00 | 2 |
conversion_id | user_id | conversion_time | ad_id |
---|---|---|---|
201 | 301 | 2023-01-10 21:23:00 | 1 |
202 | 303 | 2023-01-12 16:01:00 | 1 |
203 | 305 | 2023-01-13 14:31:00 | 2 |
The marketing team wants to know the Click-through Conversion Rate (CTR) for each ad campaign. CTR is calculated as .
This query joins the conversions table to the ad_clicks table by user_id and ad_id, and calculates the desired CTR. For each ad_id, it counts the number of clicks from the ad_clicks table and the number of conversions from the conversions table. Then it divides the number of conversions by the number of clicks to obtain the conversion rate or CTR.
To practice a similar SQL interview question on DataLemur's free online SQL code editor, try this SQL interview question asked by Facebook:
The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.
Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at Jabil should be lenient!).
For a tangible example in PostgreSQL, suppose you were doing an HR Analytics project for Jabil, and had access to Jabil's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who never were a employee using this query:
Jabil is a global manufacturing services company. For a company like Jabil which is involved in manufacturing, we can ask a question related to their products and sales:
"Generate a report that shows the average monthly sales of each product for the year 2022. Include the product name, product id, month, and the average sales."
The sample tables could be:
product_id | product_name |
---|---|
1 | Product A |
2 | Product B |
3 | Product C |
sale_id | product_id | sale_date | quantity |
---|---|---|---|
201 | 1 | 01/01/2022 | 50 |
202 | 1 | 01/15/2022 | 30 |
203 | 2 | 01/03/2022 | 40 |
204 | 3 | 02/12/2022 | 80 |
205 | 1 | 02/20/2022 | 60 |
206 | 2 | 03/05/2022 | 70 |
product_id | product_name | month | avg_sales |
---|---|---|---|
1 | Product A | 1 | 40 |
1 | Product A | 2 | 60 |
2 | Product B | 1 | 40 |
2 | Product B | 3 | 70 |
3 | Product C | 2 | 80 |
This query joins and on . It filters out sales that were made in the year 2022. It groups the result by , and , and calculates the average (which represents sales) for each grouping.
The key to acing a Jabil SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Jabil SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Google, Microsoft and Silicon Valley startups.
Each SQL question has hints to guide you, detailed solutions and most importantly, there is an online SQL coding environment so you can right online code up your SQL query answer and have it graded.
To prep for the Jabil SQL interview it is also wise to solve interview questions from other enterprise service and solution companies like:
Learn how Jabil is harnessing the power of AI to drive innovation and efficiency in manufacturing!
However, if your SQL skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this free SQL tutorial.
This tutorial covers topics including CTE vs. Subquery and aggreage functions like MIN()/MAX() – both of these show up routinely during Jabil interviews.
In addition to SQL query questions, the other types of questions covered in the Jabil Data Science Interview are:
To prepare for Jabil Data Science interviews read the book Ace the Data Science Interview because it's got:
Also focus on the behavioral interview – prep for that with this Behavioral Interview Guide for Data Scientists.