At Xerox, SQL is used day-to-day for generating insights into the printing and hardware business lines, to improve printer efficiency and automate document management. Because of this, Xerox Holdings LOVES to ask SQL questions in interviews for Data Science and Data Engineering positions.
Thus, to help you prepare for the Xerox Holdings SQL interview, we've collected 11 Xerox SQL interview questions – how many can you solve?
As a Database Analyst at Xerox Holdings, they require an analysis of your printer usage. You are presented with two tables:
Write an SQL query to find the total number of print jobs each printer completed in the previous month, ranked by the number of print jobs in descending order.
The table is structured as follows:
job_id | printer_id | print_date |
---|---|---|
5623 | 876 | 2022-06-15 |
5431 | 876 | 2022-06-28 |
6982 | 908 | 2022-06-15 |
7179 | 250 | 2022-05-22 |
7621 | 908 | 2022-07-01 |
The table is structured as follows:
printer_id | printer_model | location |
---|---|---|
876 | Multifunction Printer 1234X | New York |
908 | LaserJet Printer 5678Y | Los Angeles |
250 | Inkjet Printer 9012Z | Chicago |
printer_id | printer_model | location | total_print_jobs_previous_month | rank |
---|---|---|---|---|
876 | Multifunction Printer 1234X | New York | 2 | 1 |
908 | LaserJet Printer 5678Y | Los Angeles | 1 | 2 |
The PostgreSQL query involves creating a window function "RANK() OVER(ORDER BY count(job_id) DESC)":
The above SQL query first creates a CTE (Common Table Expressions) "monthly_stats", which calculates the total print jobs for each printer in the previous month. It then joins "monthly_stats" with the original "printers" table and ranks them according to the number of print jobs they completed in the previous month in descending order.
For more window function practice, try this Uber SQL problem within DataLemur's interactive coding environment:
Xerox Holdings is a print technology and intelligent work solutions company that handles different print jobs from various clients. Given the nature of their services, it's vital that the company efficiently manages all print jobs to ensure client satisfaction.
Assume Xerox Holdings uses a relational database system to track all their incoming print jobs. There are two tables: and .
The table has columns for (unique identifier for the client), and .
The table has columns for (unique identifier for the print job), , (On Hold, In Progress, Completed), , and .
The company wants to identify the total number of pages printed per for completed jobs over the past month.
client_id | client_name | client_location |
---|---|---|
1 | ABC Corp | New York |
2 | XYZ Co. | Florida |
3 | Tech Corp | California |
job_id | client_id | job_status | start_time | end_time | pages_printed |
---|---|---|---|---|---|
1 | 1 | Completed | 06/01/2022 09:00:00 | 06/01/2022 10:00:00 | 500 |
2 | 2 | In Progress | 06/02/2022 10:00:00 | NULL | NULL |
3 | 3 | Completed | 06/30/2022 11:00:00 | 06/30/2022 12:10:00 | 1000 |
4 | 1 | On Hold | 07/01/2022 08:00:00 | NULL | NULL |
5 | 2 | Completed | 07/10/2022 02:30:00 | 07/10/2022 03:00:00 | 1200 |
This SQL query first creates a common table expression (CTE) named 'completed_jobs' to filter only the completed jobs over the past month. Then it joins the CTE with the 'clients' table on . The statement is used to aggregate the results by and function is used to calculate the total number of pages printed for each location.
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 is an example using two tables, Xerox Holdings employees and Xerox Holdings managers:
This will return all rows from Xerox Holdings 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 retrieve all rows from employees that do not appear in managers. The operator works by retreivingthe rows that are returned by the first query, but not by the second.
Please note that is not supported by all DBMS systems, such as MySQL and Oracle (however, you can use the operator to achieve a similar outcome).
As a data analyst at Xerox Holdings, your team wants to analyze patterns among customers who have made more than one purchase in the last year. Your task is to write a PostgreSQL query that identifies customers who have made more than one purchase, the total amount spent, and their last purchase date.
customer_id | name |
---|---|
7162 | John Doe |
2175 | Jane Smith |
3812 | Bob Johnson |
9123 | Larry David |
purchase_id | customer_id | purchase_date | product_id | total_amount |
---|---|---|---|---|
9171 | 7162 | 06/09/2021 00:00:00 | 11001 | 250.00 |
7808 | 2175 | 06/12/2021 00:00:00 | 12058 | 150.00 |
5291 | 7162 | 07/08/2021 00:00:00 | 13001 | 300.00 |
6350 | 3812 | 07/26/2021 00:00:00 | 11001 | 250.00 |
4515 | 9123 | 07/05/2021 00:00:00 | 12058 | 150.00 |
4516 | 9123 | 07/20/2021 00:00:00 | 11001 | 250.00 |
This query starts by joining the table with on the field. In the SELECT clause, several aggregate functions are used: COUNT to get the total number of purchases, SUM to get the total amount spent, and MAX to find the last purchase date. The HAVING clause finally filters the results to only include customers with more than one purchase.
A self-join is a operation in which a single table is joined to itself. To perform a self-join, you must specify the table name twice in the clause, giving each instance a different alias. You can then join the two instances of the table using a clause, and specify the relationship between the rows in a clause.
Think of using a self-joins whenever your data analysis involves analyzie pairs of the same things, like comparing the salaries of employees within the same department, or identifying pairs of products that are frequently purchased together (which you can do in this real SQL question from a Walmart interview).
For another self-join example, suppose you were conducting an HR analytics project and needed to examine how frequently employees within the same department at Xerox Holdings interact with one another, you could use a self-join query like the following to retrieve all pairs of Xerox Holdings employees who work in the same department:
This query returns all pairs of Xerox Holdings employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same Xerox Holdings employee being paired with themselves).
At Xerox Holdings, which is widely known for its printer services. Imagine you work in the sales department and you need to get some data for your monthly report. Your task is to make a SQL Query to get a report of the total number of each printer type sold and their average price for each month in the year 2022.
Given the tables below:
sale_id | printer_type | sale_date | printer_price |
---|---|---|---|
1001 | LaserJet | 05/01/2022 00:00:00 | 450 |
1002 | OfficeJet | 05/02/2022 00:00:00 | 350 |
1003 | LaserJet | 05/10/2022 00:00:00 | 450 |
1004 | OfficeJet | 06/02/2022 00:00:00 | 349 |
1005 | LaserJet | 06/05/2022 00:00:00 | 452 |
Here's a PostgreSQL query that can solve this problem:
This query groups the sales data by month and printer type, and calculates the total number of each printer type sold as well as their average price for each month in 2022. The 'EXTRACT' function is used to retrieve the year and the month from the 'sale_date' and the 'AVG' function is used to calculate the average price. The results are sorted by the month and printer type.
While knowing this answer is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Xerox Holdings should be at least aware of SQL vs. NoSQL databases.
Relational databases and non-relational (NoSQL) databases have some key differences, particularly in terms of how data is stored. Whereas relational databases have tables, made up of rows and columns, NoSQL databases use various data models like:
This added flexibility makes NoSQL databases well-suited for handling non-tabular data or data with a constantly changing format. However, this flexibility comes at the cost of ACID compliance, which is a set of properties (atomic, consistent, isolated, and durable) that ensure the reliability and integrity of data in a database. While most relational databases are ACID-compliant, NoSQL databases may not provide the same level of guarantees.
As a database manager at Xerox Holdings, we often need to filter out customer data that matches specific patterns. For instance, we might want to retrieve all customer records where the email domain is 'xerox.com'. This would help us better understand and assist customers who are also employees.
To simulate such a scenario, consider the following table 'Customers':
customer_id | first_name | last_name | |
---|---|---|---|
234 | John | Doe | john.doe@xerox.com |
345 | Jane | Doe | jane.doe@gmail.com |
456 | Peter | Parker | peter.parker@xerox.com |
567 | Tony | Stark | tony.stark@hotmail.com |
678 | Bruce | Wayne | bruce.wayne@xerox.com |
This query looks at the 'email' column of the 'Customers' table and retrieves all records where the email domain is 'xerox.com'. The '%' symbol is a wildcard operator in SQL that matches any string of characters. Therefore, '%@xerox.com' matches any string that ends with '@xerox.com'.
customer_id | first_name | last_name | |
---|---|---|---|
234 | John | Doe | john.doe@xerox.com |
456 | Peter | Parker | peter.parker@xerox.com |
678 | Bruce | Wayne | bruce.wayne@xerox.com |
Only the customers with email domain 'xerox.com' are returned by the query, helping us to identify customers who are also employees.
Xerox Holdings Corporation needs you to perform a deep analysis on its customer database. Your task is to write a SQL query that returns the count of all purchased products for each customer and the total amount spent by the customer.
Assume we have two tables: and .
The table has the following columns:
customer_id | first_name | last_name |
---|---|---|
1 | James | Smith |
2 | Maria | Garcia |
3 | Michael | Johnson |
The table has the following columns:
purchase_id | customer_id | product_id | price |
---|---|---|---|
5000 | 1 | 100 | 25.00 |
5001 | 2 | 102 | 39.99 |
5002 | 2 | 101 | 10.00 |
5003 | 1 | 101 | 10.00 |
5004 | 3 | 100 | 25.00 |
The output of your query should return each customer’s full name (first name concatenated with last name), the count of purchased products by $customer_id and the total amount spent by each customer.
full_name | product_count | total_spent |
---|---|---|
James Smith | 2 | 35.00 |
Maria Garcia | 2 | 49.99 |
Michael Johnson | 1 | 25.00 |
Our SQL query joins the customers and purchases tables on the "customer_id" field. This yields a table that includes all purchases along with the information of the customers who made them. We then group by customer_id in order to return results for each customer, count the number of purchased products and sum the total amount spent by each customer on purchases. The result is a table that lists each customer’s full name (concatenated from the first and last names), the count of purchased products, and the total amount spent.
Because join questions come up frequently during SQL interviews, take a stab at this Spotify JOIN SQL question:
If you want to return records with no duplicates, you can use the keyword in your statement.
For example, if you had a table of Xerox Holdings employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:
If had the following data:
f_name | job_title |
---|---|
Akash | Data Analyst |
Brittany | Data Scientist |
Carlos | Data Engineer |
Diego | Data Engineer |
Eva | Data Analyst |
Then the output from the query would be:
job_title |
---|
Data Analyst |
Data Scientist |
Data Engineer |
Xerox Holdings sells multiple products. Each product has a different price and price variability. The Finance team needs a report that calculates the monthly weighted average percentage price change for each product sold. The weight of each price change is the absolute quantity sold in the month.
Consider rounding to two decimal places and calculate percentage changes using the following formula: ((new_price - old_price) / old_price) * 100
product_id | product_name |
---|---|
1 | Printer 3000 |
2 | Scanner Q2 |
3 | Photocopier XYZ |
sale_id | product_id | sale_date | quantity | sale_price |
---|---|---|---|---|
1 | 1 | 07/01/2022 | 10 | 500 |
2 | 1 | 07/10/2022 | 5 | 510 |
3 | 2 | 07/15/2022 | 8 | 250 |
4 | 2 | 07/20/2022 | 15 | 240 |
5 | 3 | 07/25/2022 | 20 | 1000 |
6 | 3 | 07/28/2022 | 50 | 1020 |
product_id | product_name | month | weighted_avg_price_change |
---|---|---|---|
1 | Printer 3000 | 7 | 1.00 |
2 | Scanner Q2 | 7 | -4.00 |
3 | Photocopier XYZ | 7 | 2.00 |
In the given dataset, each product has multiple sales records within the month. For each product, we calculate the percent change in price from the previous transaction, and weight it by the quantity sold in the new transaction. We then aggregate this by product and month to get the weighted average price change per product per month.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for requiring calculations using percentage change or this Amazon Average Review Ratings Question which is similar for requiring an average calculation and grouping by product.
The key to acing a Xerox Holdings SQL interview is to practice, practice, and then practice some more! Beyond just solving the earlier Xerox Holdings SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Netflix, Google, and Amazon.
Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an interactive coding environment so you can instantly run your SQL query answer and have it graded.
To prep for the Xerox Holdings SQL interview you can also be a great idea to practice SQL problems from other tech companies like:
However, if your SQL foundations are weak, don't worry about going right into solving questions – go learn SQL with this SQL tutorial for Data Analytics.
This tutorial covers SQL concepts such as filtering strings based on patterns and handling NULLs in SQL – both of which pop up often during SQL interviews at Xerox Holdings.
In addition to SQL interview questions, the other question categories to prepare for the Xerox Holdings Data Science Interview are:
To prepare for Xerox Holdings Data Science interviews read the book Ace the Data Science Interview because it's got: