11 HPE SQL Interview Questions (Updated 2024)

At HP Enterprise, SQL does the heavy lifting to support their Data Management customers. That's why HPE frequently asks SQL coding questions in interviews for Data Analyst, Data Science, and BI jobs.

To help you practice for the HPE SQL interview, we've collected 11 HP Enterprise SQL interview questions – able to answer them all?

11 HP Enterprise SQL Interview Questions

SQL Question 1: Employee Salary Ranking

In Hewlett Packard Enterprise (HPE), there exists an employee table that contains data about employees ID, department ID, and their salaries.

The goal is to analyze employee salary ranks within their respective departments. Write the SQL query which will add a new column to the result set showing the rank of that employee’s salary within the department they belong to. If there's a tie in salary, they should have the same ranking. Assume the higher the salary, the higher the rank.

Consider the following table for your task:

Example Input:

Expected output should contain the named columns with salary rank within each department.

Expected Output:

Answer:

In PostgreSQL, we can utilize the window function to achieve this. Here's the corresponding SQL query:

Writeup:

In the above SQL query, is a window function that gives you the rank of rows within the window of your result set. The clause breaks up the dataset into groups (in our case ) and is computed within these groups. The clause within the function determines the order of the ranks (here we're sorting salaries in descending order). The function gives the same rank to identical values which handles ties gracefully. So, for each department, it assigns a rank to each employee based on their salary in descending order.

p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur

SQL Question 2: Analyzing Server Log Data

HPE is a major provider of server technology, so understanding server usage is a key part of their business. Imagine you've been given access to a database that contains log data for their deployed servers. This data includes information on when the server was used, how long it was used for, and which client accessed it.

The company would like to understand the usage pattern of their servers. Specifically, they're interested in identifying the top 5 clients who have used the servers for the longest duration in the past month.

The two main tables of interest are and .

Example Input:

Example Input:

Answer:

Here's a PostgreSQL query that selects the top 5 clients based on total server usage duration in the past month:

This query first joins the and tables on the field. It then filters for log entries from the past month. The resulting data is grouped by , and the total duration of server usage is calculated for each client. The results are then ordered in descending order of total duration, and the top 5 results are returned.

SQL Question 3: What do the / operators do, and can you give an example?

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 HPE should be lenient!).

Here's a PostgreSQL example of using EXCEPT to find all of HPE's Facebook video ads with more than 10k views that aren't also being run on YouTube:

If you want to retain duplicates, you can use the EXCEPT ALL operator instead of EXCEPT. The EXCEPT ALL operator will return all rows, including duplicates.

SQL Question 4: Filter customer records based on multiple conditions

As an analyst at Hewlett Packard Enterprise (HPE), you have been tasked with filtering active customers who have made purchases in the last month in the United States region, from the customer database. You need to filter down the records of customers who have the 'active' status, are based in 'United States' and whose 'last_purchase_date' is within the last 30 days.

Example Input:

Answer:

The SQL command above selects all columns (*) from the 'customer' table, and uses WHERE clause with three conditions joined with AND operators.

• ensures that the customer is currently active.
• filters the customers who are based in the United States.
• ensures that the customer has made a purchase within the last 30 days. gets the date 30 days ago from today.

This command will return all active customers from United States who have made a purchase in the last 30 days.

SQL Question 5: What's the SQL command do, and can you give an example?

The SQL command merges the results of multiple statements and keeps only those rows that are present in all sets.

For example, say you were doing an HR Analytics project for HPE, and had access to HPE's employees and contractors 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 also show up in the employees table:

SQL Question 6: Calculate Click-Through-Rates for HPE Digital Ads.

Consider a hypothetical scenario where Hewlett Packard Enterprise (HPE) is conducting a wide variety of marketing campaigns for various digital products. They are interested in finding out the click-through rates (CTRs) of their digital ads.

CTR is calculated as the number of users who clicked on an ad divided by the number of total users who viewed the ad. Also, they are interested in click-through conversion rates, which is the number of users added a product to their cart after viewing it divided by the total number of users who viewed the product.

Here are two tables that will assist in this investigation:

Write a PostgreSQL Query to find the CTR and click-through-conversion rate for each product.

Answer:

The SQL query could perform a JOIN on 'views' and 'clicks' table based on common 'product_id', count the total views and total clicks, and calculate the CTR as follows:

This query first combines data from both 'views' and 'clicks' table based on 'product_id'. Then we calculate the total number of click events and view events for each 'product_id'. After that, we compute the CTR for each 'product_id' by simply dividing the total clicks by total views. Similarly, we check the action of each click event; if it is 'added_to_cart' then we count them for conversion rate calculation.

Please note that rate calculations are done using 'float' data type to ensure accurate calculations.

To solve a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's interactive SQL code editor:

SQL Question 7: How do foreign and primary keys differ?

To better understand the difference between a primary key and a foreign key, let's use an example from HPE's marketing analytics database, which holds data on Google Ads campaigns:

:

+------------+------------+------------+------------+ | ad_id | campaign_id| keyword | click_count| +------------+------------+------------+------------+ | 1 | 100 | HPE pricing | 10 | | 2 | 100 | HPE reviews | 15 | | 3 | 101 | HPE alternatives | 7 | | 4 | 101 | buy HPE | 12 | +------------+------------+------------+------------+

In this table, serves as the primary key. It uniquely identifies each ad and cannot be null.

is a foreign key that connects to the of the corresponding Google Ads campaign. This establishes a relationship between the ads and their campaigns, enabling easy querying to find which ads belong to a specific campaign or which campaigns a specific ad belongs to.

The table may also have multiple foreign keys that reference primary keys in other tables. For example, and foreign keys could be used to link each ad to its ad group and the Google Ads account that the campaigns belong to, respectively.

SQL Question 8: Maximum Sales of HPE Products

As an HPE (Hewlett Packard Enterprise) data analyst, find out which product category has gathered the most revenue for each year. HPE sells a variety of technical products such as servers, storage, and networking equipment.

Example Input:

Example Input:

Example Output:

Answer:

The query is joining the sales and products tables on the product_id field. It extracts the year from the sale_date field and groups the data by year and product category. It then sums the price of the sales for each category per year and sorts the results by the revenue, in descending order. This will provide the maximum revenue for each product category for each year.

SQL Question 9: Filtering Customer Records

HPE (Hewlett Packard Enterprise) is trying to analyze their customer records to understand their customer base better. They want to filter down the customer details whose email domain is '@hp.com' and who are located in the California region.

To do this, Your task is to write a SQL query that selects all customers whose email address ends in '@hp.com' and whose location is 'California'.

The following table represents a sample of the customer data you would need to work with:

Example Input:

Answer:

The PostgreSQL query to solve this problem is:

This query uses the keyword in conjunction with the wildcard to match any customers whose email address ends in '@hp.com'. It also filters down the data to only include those customers who are located in 'California', as specified in the problem statement.

Thus, the query would return customers with IDs 1 and 4 based on the sample input provided.

SQL Question 10: Could you explain what a self-join is and provide examples of when it might be used?

A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

One common use case for self-joins is to compare data within a single table. For example, you might use a self-join to compare the salaries of employees within the same department, or to identify pairs of products that are frequently purchased together (like in this real Walmart SQL interview question)[https://datalemur.com/questions/frequently-purchased-pairs].

For a more concrete example, imagine you had website visitor data for HPE, exported from the company's Google Analytics account. To help the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to produce all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair.

You could use the following self-join:

This query retrieves the url of each page () along with the url of the page that referred to it (). The self-join is performed using the , which identifies the id of the page that referred the visitor to the current page, and excludes any pages that referred to themselves (i.e., data anomalies since pages shouldn't refer to themself).

SQL Question 11: Calculate Salesperson Quarterly Performance

The company HPE wants to calculate the quarterly average selling price of computers sold by its salesperson, rounded to 2 decimal places. They also want to find out the absolute difference between the maximum and minimum selling prices in each quarter, and the square root of the total quantity sold in the quarter.

Here are a sample of their sales records:

Example Input:

The output should contain the quarter number (based on the sale_date), salesperson id, average selling price (rounded to two decimal points), the absolute difference between max and min selling price in that quarter, and the square root of total quantity sold in the quarter.

Example Output:

Answer:

The above query will segregate the sales data into quarters and calculate the desired metrics for each salesperson for each quarter. The use of the AVG, MAX, MIN, and SUM functions help calculate the average price, the price difference, and the total quantity, respectively. The ABS function helps find the absolute price difference, and the SQRT function finds the square root of the total quantity sold. All results are grouped by quarter and salesperson id.

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating sales rates or this Amazon Average Review Ratings Question which is similar for calculating average values.

Preparing For The HPE SQL Interview

The key to acing a HPE SQL interview is to practice, practice, and then practice some more! Besides solving the above HPE SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Microsoft and Silicon Valley startups.

Each exercise has multiple hints, detailed solutions and best of all, there's an interactive coding environment so you can instantly run your SQL query and have it checked.

To prep for the HPE SQL interview it is also helpful to solve SQL questions from other tech companies like:

• Dell SQL questions

• IBM SQL questions

• Cisco SQL questions

• NetApp SQL questions

In case your SQL query skills are weak, forget about diving straight into solving questions – improve your SQL foundations with this SQL tutorial for Data Analytics.

This tutorial covers topics including filtering with LIKE and filtering data with boolean operators – both of these pop up often during SQL job interviews at HPE.

HP Enterprise Data Science Interview Tips

What Do HPE Data Science Interviews Cover?

Besides SQL interview questions, the other question categories to practice for the HPE Data Science Interview are:

• Statistics and Probability Questions
• Python or R Programming Questions
• Product-Sense and Business Case Questions
• Machine Learning and Predictive Modeling Questions
• Behavioral Interview Questions

How To Prepare for HPE Data Science Interviews?

To prepare for HPE Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions sourced from companies like Google, Tesla, & Goldman Sachs
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