11 Huntington Ingalls SQL Interview Questions (Updated 2024)
At Huntington Ingalls Industries, SQL is used often for analyzing naval shipbuilding process data and predicting construction timeframes using historical data. Unsurprisingly this is why Huntington Ingalls often tests SQL query questions during interviews for Data Science, Analytics, and & Data Engineering jobs.
In case you're studying for a SQL Assessment, we've curated 11 Huntington Ingalls Industries SQL interview questions to practice, which are similar to recently asked questions at Huntington Ingalls – able to answer them all?
11 Huntington Ingalls Industries SQL Interview Questions
SQL Question 1: Identify Top Purchasing Customers
Given the table for the company Huntington Ingalls, write a SQL query to identify the top 10 customers (user ids) who have the highest total purchases (in USD) during the last 12 months. Assume today's date is '2022-12-31'.
Example Input:
| purchase_id | user_id | purchase_date | amount_usd |
|---|---|---|---|
| 101 | 123 | 2021-12-22 | 5000 |
| 102 | 234 | 2022-02-14 | 4500 |
| 103 | 345 | 2022-06-19 | 5200 |
| 104 | 123 | 2022-10-01 | 3000 |
| 105 | 234 | 2022-10-22 | 8800 |
| 106 | 456 | 2022-08-05 | 2750 |
| 107 | 789 | 2021-12-28 | 6000 |
| 108 | 123 | 2022-12-15 | 4000 |
Example Output:
| user_id | total_purchases_usd |
|---|---|
| 234 | 13300 |
| 123 | 12000 |
| 345 | 5200 |
| 789 | 6000 |
| 456 | 2750 |
Answer:
This query first filters the table records to only those that fall within the past 12 months timeframe, i.e., between '2022-01-01' and '2022-12-31'. Then, it groups the filtered records by and calculates the total purchase amount for each user by summing up their values. Finally, it sorts these users in descending order based on their total purchase amount and selects the top 10 customers.
To work on another SQL customer analytics question where you can solve it interactively and have your SQL solution automatically checked, try this Walmart Labs SQL Interview Question:
SQL Question 2: Analyze Production Output for Different Shipyards
Huntington Ingalls wants to analyze the production output from its various shipyards over different months.
Consider the following tables, and , where includes monthly outputs, and provides more detailed information about each shipyard.
Example Input:
| production_id | shipyard_id | month | year | ships_produced |
|---|---|---|---|---|
| 1 | A | 6 | 2022 | 14 |
| 2 | A | 7 | 2022 | 15 |
| 3 | B | 6 | 2022 | 20 |
| 4 | B | 7 | 2022 | 18 |
| 5 | C | 6 | 2022 | 13 |
Example Input:
| shipyard_id | name | capacity | location |
|---|---|---|---|
| A | Newport News | 25 | Virginia |
| B | Ingalls | 30 | Mississippi |
| C | Universal Shipping | 20 | Alabama |
The SQL interview question is: Write a SQL query to rank the shipyards by the average number of ships produced per month in the year 2022, in descending order.
Answer:
The SQL query would be the following:
This SQL query first joins the and tables using an INNER JOIN on the field. The WHERE clause then restricts the analysis to the year 2022. Finally, it uses the GROUP BY clause to calculate the average number of ships produced at each shipyard, ordering the result by this average in descending order. The result shows each shipyard's name, location, and their average monthly ship production in 2022.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
SQL QUESTION 3: 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 Huntington Ingalls'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 INNER JOIN between the Sales table and the Customers table would retrieve only the rows where the customer_id in the Sales table matches the customer_id in the table.
- : retrieves all rows from the left table (in this case, the sales table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.
- : retrieves all rows from the right table (in this case, the customers table) and any matching rows from the left table (the sales table). If there is no match in the left table, NULL 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, NULL values will be returned for the columns of the non-matching table.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
SQL Question 4: Customer Data Filter based on Shipping Status and Geography
You are working as a Data Analyst at Huntington Ingalls Industries, a shipbuilding company. You are tasked to analyze their customer data. You need to write a SQL query that will return all customers who are based in Virginia (VA) and have at least one ship order that is in 'delivered' state.
Example Input:
| customer_id | customer_name | location_state |
|---|---|---|
| 101 | Corporate Inc | VA |
| 102 | Oceanic Business | CA |
| 103 | Marine Supplies | VA |
| 104 | Nautical Needs | FL |
| 105 | Aqua Corp | VA |
Example Input:
| order_id | customer_id | ship_status |
|---|---|---|
| 501 | 101 | delivered |
| 502 | 102 | delivered |
| 503 | 101 | in-progress |
| 504 | 103 | in-production |
| 505 | 105 | delivered |
Answer:
This query first performs an INNER JOIN on the customer and order tables based on the customer_id field. Then, it filters for records where customer's location state is Virginia ('VA') and their order ship status is 'delivered'. This will return all customers based in Virginia with at least one ship order that has 'delivered' status.
SQL QUESTION 5: What are the similarities and differences between a clustered and non-clustered index?
Both clustered and non-clustered indexes are used to improve query performance, but they have different characteristics.
A clustered index determines the physical order of the data rows in a table, while a non-clustered index does not.This means that a table can have only one clustered index, but it can have multiple non-clustered indexes.
In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.
SQL Question 6: Analyze Webpage Click-Through Rates
Huntington Ingalls has been running a digital ad campaign to promote its new line of commercial ships. As a data analyst, you are tasked to analyze the click-through rates of these ads. Specifically, you should calculate the click-through conversion rate: the ratio of the number of users who viewed the ad and then subsequently clicked it to the total number of users who viewed the ad.
The information is stored in two tables, and . The table logs the user_id and the timestamp each ad was viewed. The table logs the user_id and the timestamp each ad was clicked.
Note: a view is only considered converted if there is a corresponding click with a timestamp after the view's timestamp.
Example Input:
| view_id | user_id | view_timestamp |
|---|---|---|
| 501 | 325 | 07/01/2022 09:45:00 |
| 502 | 128 | 07/02/2022 13:34:00 |
| 503 | 325 | 07/03/2022 08:22:00 |
| 504 | 781 | 07/04/2022 16:45:00 |
| 505 | 128 | 07/05/2022 20:30:00 |
Example Input:
| click_id | user_id | click_timestamp |
|---|---|---|
| 101 | 325 | 07/01/2022 10:12:00 |
| 102 | 128 | 07/02/2022 13:45:00 |
| 103 | 781 | 07/06/2022 17:23:00 |
Answer:
This SQL query calculates the click-through conversion rate by first counting the number of distinct users who viewed and clicked the ad (using a LEFT JOIN on user_id and ensuring the click happened after the view), and then dividing it by the total number of distinct users who viewed the ad.
To solve a similar SQL interview question on DataLemur's free online SQL code editor, solve this Facebook SQL Interview question:
SQL QUESTION 7: What is a cross-join, and when would you use one?
A cross-join, also known as a cartesian join, is a type of join that returns the cross-product of two tables. In a cross-join, each row from the first table is paired with every row from the second table, resulting in a new table that has a row for each possible combination of rows from the two input tables.
For example, say you worked on the Marketing Analytics team at HII, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).
Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:
You could this query to generate all possible combinations of ad copy and ad creative to help you create more effective ads for Huntington Ingalls.
Just be careful: if you had 1,000 rows of ad copy and 1,000 different image creatives, the resulting cross-join would have 1 million rows!
To solve a similar SQL interview question on DataLemur's free online SQL code editor, solve this Facebook SQL Interview question:
SQL Question 8: Total Value of Ship Orders per Type
Huntington Ingalls is America's largest military shipbuilding company. Let's imagine they need to know the total value of each type of ship order for each year to make budgetary decisions.
Suppose we have a table where each record indicates a ship order. The amount represents the total contract value of the order in USD.
Example Input:
| order_id | order_date | ship_type | amount (USD) |
|---|---|---|---|
| 1001 | 01/15/2018 | Aircraft Carrier | 13000000000 |
| 1002 | 06/02/2019 | Submarine | 3000000000 |
| 1003 | 12/30/2018 | Destroyer | 1850000000 |
| 1004 | 05/15/2020 | Aircraft Carrier | 13500000000 |
| 1005 | 07/17/2021 | Submarine | 3150000000 |
We want to generate a report that shows the total value of ship orders for each type of ship per year.
Example Output:
| year | ship_type | total_order_value (USD) |
|---|---|---|
| 2018 | Aircraft Carrier | 13000000000 |
| 2018 | Destroyer | 1850000000 |
| 2019 | Submarine | 3000000000 |
| 2020 | Aircraft Carrier | 13500000000 |
| 2021 | Submarine | 3150000000 |
Answer:
This query groups the data by year and ship type, calculating the total value of the orders for each group. The function is used to obtain the YEAR part from the order date. The function calculates the total amount of orders for each group. Finally, the clause sorts the result by year and, within each year, orders them by total order value in descending order.
SQL Question 9: Filter Employee Records with SQL LIKE
Imagine you're a data analyst at Huntington Ingalls and your manager wants to find all employees who have been assigned to work with the US Navy. Employee tables store this information in the column in the form of text. For this task, any record that contains the string 'US Navy' anywhere in the field should be considered a match. Write a SQL query to filter out these employees.
Example Input:
| emp_id | first_name | last_name | assignment |
|---|---|---|---|
| 001 | John | Doe | US Navy - Aircraft Carrier |
| 002 | Jane | Smith | US Army - Tank Battalion |
| 003 | Bob | Johnson | US Navy - Submarine |
| 004 | Alice | Brown | Private Contractor - Supply Chain |
| 005 | Charlie | Davis | US Navy - Naval Base |
Example Output:
| emp_id | first_name | last_name | assignment |
|---|---|---|---|
| 001 | John | Doe | US Navy - Aircraft Carrier |
| 003 | Bob | Johnson | US Navy - Submarine |
| 005 | Charlie | Davis | US Navy - Naval Base |
Answer:
This SQL query uses the LIKE keyword, along with the wildcard character '%' to search for any records in the column that contain the string 'US Navy'. The '%' character is used to represent zero, one, or multiple characters. This allows the query to match records that contain 'US Navy' anywhere in the field.
SQL QUESTION 10: Do NULLs in SQL mean the same thing as a zero?
NULLs are NOT the same as zero or blank spaces in SQL. NULLs are used to represent a missing value or the abscence of a value, whereas zero and blank space are legitimate values.
It's important to handle NULLs carefully, because they can mess up your analysis very easily. For example, if you compare a NULL value using the = operator, the result will always be NULL (because just like Drake, nothing be dared compared to NULL). That's why many data analysis in SQL start with removing NULLs using the function.
SQL Question 11: Analyzing Customer and Order Tables with Join Statement
Huntington Ingalls wants to analyze their customer's ordering activity in relation to the products they purchased. Specifically, the company wants to find out the total quantity of each product purchased by each customer.
Sample Input:
| customer_id | first_name | last_name | city | state |
|---|---|---|---|---|
| 1 | John | Doe | Newport News | VA |
| 2 | Jane | Smith | Pascagoula | MS |
| 3 | Tom | Johnson | San Diego | CA |
| 4 | Sara | Davis | Baltimore | MD |
| 5 | Alex | Brown | Boston | MA |
Sample Input:
| order_id | product_id | quantity | customer_id |
|---|---|---|---|
| 1001 | 200 | 1 | 1 |
| 1002 | 201 | 2 | 1 |
| 1003 | 200 | 1 | 2 |
| 1004 | 202 | 1 | 3 |
| 1005 | 203 | 3 | 4 |
Answer:
This query will join the and tables on the field, and then group the results by customer name and product_id, summarizing the total quantity of each product purchased by each customer. For example, it will show that John Doe bought 1 unit of product 200 and 2 units of product 201.
Because joins come up frequently during SQL interviews, try an interactive SQL join question from Spotify:
How To Prepare for the Huntington Ingalls 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.
Besides solving the above Huntington Ingalls SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups.
Each DataLemur SQL question has multiple hints, full answers and best of all, there is an interactive SQL code editor so you can easily right in the browser your SQL query and have it executed.
To prep for the Huntington Ingalls SQL interview it is also useful to solve SQL problems from other defense & aerospace contractors like:
- Lockheed Martin SQL questions
- Boeing SQL questions
- TransDigm SQL questions
- Howmet Aerospace SQL questions
But if your SQL query skills are weak, don't worry about going right into solving questions – go learn SQL with this free SQL tutorial.
This tutorial covers SQL concepts such as Subqueries and HAVING – both of which pop up frequently during SQL job interviews at Huntington Ingalls.
Huntington Ingalls Industries Data Science Interview Tips
What Do Huntington Ingalls Data Science Interviews Cover?
For the Huntington Ingalls Data Science Interview, besides SQL questions, the other types of questions to practice:
- Probability & Stats Questions
- Python or R Coding Questions
- Product Analytics Questions
- Machine Learning Questions
- Behavioral Interview Questions
How To Prepare for Huntington Ingalls Data Science Interviews?
To prepare for Huntington Ingalls Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from tech companies like Netflix, Google, & Airbnb
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