10 CACI SQL Interview Questions (Updated 2024)

CACI use SQL for analyzing intelligence data to counter threats, such as identifying patterns in terrorist communications, as well as managing databases for national defense systems, like tracking military equipment inventory. For this reason, CACI often uses SQL questions during interviews for Data Science and Data Engineering positions.

To help you practice for the CACI SQL interview, we've curated 10 CACI International SQL interview questions in this article.

10 CACI International SQL Interview Questions

SQL Interview Question 1: Identify Power Users based on their Purchases

Given the fact that CACI is primarily a technology and professional services company, power users may be defined in this case as customers who frequently acquire license renewals, purchase software, or contract services. Here is a SQL interview question related to that:

"Write a SQL query that lists out the customers who made the most purchases every month from the last 6 months. We consider these 'Power Users'."

Sample tables have the following schema:

customers Example Input:

purchases Example Input:

Answer

WITH monthly_purchases AS (
    SELECT DATE_TRUNC('month', purchase_date) AS purchase_month, customer_id, COUNT(*) AS num_of_purchases
    FROM purchases
    WHERE purchase_date >= NOW() - INTERVAL '6 months'
    GROUP BY DATE_TRUNC('month', purchase_date), customer_id
)
SELECT purchase_month, customer_id, num_of_purchases
FROM monthly_purchases
WHERE (purchase_month, num_of_purchases) IN (
    SELECT purchase_month, MAX(num_of_purchases)
    FROM monthly_purchases
    GROUP BY purchase_month
)
ORDER BY purchase_month DESC;

To interpret the results of this query, for each month in the past 6 months, we identify the customer (or customers in case of a tie) who made the most purchases.

To solve a similar VIP customer analysis question on DataLemur's free interactive SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:

SQL Question 2: Department Salaries

You're given a table of CACI employee and department salary data. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.

Write a SQL query for 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 here: Department vs. Company Salary.

SQL Question 3: Database transactions are supposed to be atomic, consistent, isolated, & durable. What does each term mean?

To ensure the reliability and integrity of data, a database management system (DBMS) strives to maintain the ACID properties: Atomicity, Consistency, Isolation, and Durability. To illustrate these concepts, consider the following examples of how ACID properties apply to banking transactions:

1. Atomicity: A transaction is either completed in full or not at all. For example, if a customer is transferring money between accounts, the transaction should either transfer the entire amount or none at all.

2. Consistency: A transaction is only allowed to complete if it follows all rules and constraints within the database. For example, if a customer is withdrawing money from an account, the transaction should only be allowed to proceed if there are sufficient funds available. Otherwise, the transaction is rejected.

3. Isolation: Concurrent transactions are kept separate from each other, so that the changes made by one transaction cannot be seen by another transaction until the first one is complete. This helps prevent conflicts, such as two customers attempting to withdraw money from the same account at the same time.

4. Durability: Once a transaction has been committed and completed, the changes made by the transaction are permanently stored in the database and will not be lost even if the database or system crashes. For example, if a customer makes a deposit, the transaction should be durable so that the deposit is not lost in the event of a system failure.

SQL Question 4: Calculate the Monthly Average Rating of Products

CACI has a large number of products that are constantly being reviewed by users. You have been provides a reviews table containing multiple reviews made by users over time. Your task is to write a SQL query that calculates the average review stars (avg_stars), for each product (product_id), for each month (mth). The month should be calculated from the submit_date column which expressed in the format MM/DD/YYYY HH:MI:SS.

Note: Use PostgreSQL syntax.

reviews Example Input:

Example Output:

Answer:

SELECT 
    EXTRACT(MONTH FROM submit_date) AS mth,
    product_id,
    AVG(stars) as avg_stars
FROM 
    reviews
GROUP BY 
    mth,
    product_id
ORDER BY 
    mth,
    avg_stars DESC;

The above query uses the GROUP BY clause to separate data into groups of rows that match on the mth and product_id column. The AVG function calculates the average stars for each group. Finally, the ORDER BY clause sorts the result set in ascending order by mth and descending order by avg_stars.

For more window function practice, try this Uber SQL Interview Question within DataLemur's online SQL code editor:

SQL Question 5: Can you give an example of a one-to-one relationship between two entities, vs. a one-to-many relationship?

In database schema design, a one-to-one relationship between two entities is characterized by each entity being related to a single instance of the other. An example of this is the relationship between a US citizen and their social-security number (SSN) - each citizen has one SSN, and each SSN belongs to one person.

On the other hand, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. A teacher's relationship with their classes is an example of this - a teacher can teach many classes, but each class is only associated with one teacher.

SQL Question 6: Employee Project Management

Assume you are a DB analyst at CACI, an IT Services company. The organization has multiple ongoing projects. Employees can be assigned to several projects, and each project has at least one employee working on it. The company is interested in tracking the hours logged by each employee on each project.

Design a database that can store this information and write a PostgreSQL query to determine how many total hours each employee logged each month.

Projects Example Input:

Employees Example Input:

HoursLogged Example Input:

Example Output:

Answer:

Your PostgreSQL query should look like this:

SELECT extract(month from date) AS mth, e.employee_name AS employee, SUM(h.hours) AS total_hours
FROM Employees e
JOIN HoursLogged h ON e.employee_id = h.employee_id
GROUP BY mth, employee
ORDER BY mth, total_hours DESC;

This SQL block groups together the date by month (mth) and employee and sums up the hours for these groupings. The result is then ordered by month and total hours in descending order.

SQL Question 7: What's the difference between a correlated and non-correlated sub-query?

A correlated sub-query is a sub-query that depends on the outer query and cannot be executed separately. It uses the outer query to filter or transform data by referencing a column from it, and the outer query uses the results of the inner query. In contrast, a non-correlated sub-query is independent of the outer query and can be executed on its own. It does not reference any columns from the outer query and is used to retrieve additional data needed by the outer query.

Here is an example of a correlated sub-query:

SELECT t1.customer_id, t1.total_sales
FROM caci_sales t1
WHERE t1.total_sales > (
  SELECT AVG(t2.total_sales)
  FROM caci_sales t2
  WHERE t2.customer_id = t1.customer_id
);

This query selects the customer_id and total sales of all CACI customers in the sales table whose total_sales are greater than the average total_sales of their own customer group. The sub-query in this case is correlated with the outer query, as it references the customer_id column from the outer query (t1.customer_id).

Here is an example of a non-correlated sub-query:

SELECT t1.customer_id, t1.total_sales
FROM caci_sales t1
WHERE t1.total_sales > (
  SELECT AVG(t2.total_sales)
  FROM caci_sales t2
);

The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.

Performance-wise, correlated sub-queries are generally slower to execute, as they have to be re-evaluated for each row of the outer query, while non-correlated sub-queries are faster, as they only have to be executed once.

SQL Question 8: Filtering Employee Records

Assume you are a human resources manager at CACI and you have the following employees table. You are interested to find all employees who are either 'Managers' or 'Software Engineers' and have been with the company for more than 5 years. Please write a SQL query to filter this data.

employees Example Input:

Answer:

You can use the WHERE statement to handle this filtering.

The SQL code would look like this:

SELECT *
FROM employees
WHERE (position = 'Manager' OR position = 'Software Engineer') AND years_at_CACI > 5;

This query first filters the employees based on their position. If their position is either 'Manager' or 'Software Engineer', it checks if their years at CACI is greater than 5. If both conditions meet, it includes those records in the output.

SQL Question 9: Analyzing Order Details

You have been provided with two tables: Customers and Orders. The Customers table contains information about the customers and the Orders table contains detailed orders placed by these customers.

Your task is to create a PostgreSQL query to retrieve the names of all customers and the total amount they have spent on their orders.

Please format your tables in the following way:

Customers Sample Input:

Orders Sample Input:

Answer:

SELECT c.Name, SUM(o.Amount) AS TotalSpent
FROM Customers c
JOIN Orders o
ON c.CustomerID = o.CustomerID
GROUP BY c.Name;

This query works by first joining the Customers and Orders tables on CustomerID. It then groups the results by Name. The sum of Amount for each Name is calculated and renamed as TotalSpent using the SUM() function.

Since join questions come up so often during SQL interviews, try this Snapchat Join SQL question:

SQL Question 10: Give a few ways in SQL that you can identify duplicate records in a table?

One creative way is to use the window function ROW_NUMBER() and partition by whichver columns you are loooking for duplicates in. If any row has a row_number() more than 1, then it's a duplicate!

SELECT *, ROW_NUMBER() OVER (PARTITION BY column1, column2 ORDER BY column1) as rn
FROM caci_table;

You could also use COUNT(DISTINCT col1) vs. COUNT(*) and see if they return different numbers, indicating the prescence of duplicates!

How To Prepare for the CACI SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the CACI SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the earlier CACI SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Google, Uber, and Microsoft.

Each interview question has hints to guide you, 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 online code up your query and have it executed.

To prep for the CACI SQL interview you can also be helpful to practice SQL questions from other consulting and professional service companies like:

• SAIC SQL questions
• Booz Allen SQL questions
• Insight Enterprises SQL questions
• Gartner SQL questions

Learn how Concentrix is harnessing the power of Generative AI to drive business growth and innovation!

Find out how CACI's data operations and analytics expertise is helping to drive better decision making and improve operational effectiveness!

In case your SQL foundations are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this free SQL tutorial.

This tutorial covers SQL concepts such as using ORDER BY and different types of joins – both of which come up routinely in CACI SQL assessments.

CACI International Data Science Interview Tips

What Do CACI Data Science Interviews Cover?

In addition to SQL interview questions, the other types of problems to practice for the CACI Data Science Interview include:

• AB Testing & Experimentation Questions
• Coding Questions in Python or R
• Product Data Science Interview Questions
• ML Modelling Questions
• Resume-Based Behavioral Questions

How To Prepare for CACI Data Science Interviews?

To prepare for the CACI Data Science interview have a firm understanding of the company's values and mission – this will be clutch for acing the behavioral interview. For technical interviews get ready by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from Microsoft, Amazon & startups
• A Crash Course on SQL, Product-Sense & ML
• Amazing Reviews (1000+ reviews, 4.5-star rating)