11 SolarWinds SQL Interview Questions (Updated 2024)

At SolarWinds, SQL is used often for analyzing network performance data and managing databases. They also use SQL daily within their database performance monitoring organization. Thus, it shouldn't come as a surprise that SolarWinds often tests SQL coding questions in interviews for Data Analyst, Data Science, and BI jobs.

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

11 SolarWinds SQL Interview Questions

SQL Question 1: Identify Power Users of SolarWinds

SolarWinds is a company that sells IT infrastructure management software. Their products offer solutions for managing and monitoring networks, security, system management, and much more.

One of their key user metrics could be the number of 'Alerts' a user resolves in their systems. For this scenario, let's consider 'power users' to be individuals who have resolved more than 1000 alerts in the span of a month.

Given the table below, formulate a SQL query that will identify the 'power users' based on the criteria outlined above.

Example Input:

Answer:

The SQL query for this question in PostgreSQL would be something like:

This query works by first filtering out the resolved alerts. Then, it groups the remaining rows by user and month, and counts the number of resolved alerts for each group. Finally, it uses the clause to filter out the groups that have less than 1000 resolved alerts. The result is a list of 'power users' and the number of resolved alerts they have in each month.

Please check the real table and column-names since this is an assumption-based problem and the table, column-names and data used are just for reference.

To practice a related super-user data analysis question on DataLemur's free interactive SQL code editor, try this Microsoft Teams Power User SQL Interview Question:

SQL Question 2: Analyzing Product Performance Through User Review Ratings

Given a dataset that contains user reviews for different SolarWinds products, write a SQL query to analyze the average star rating for each product on a monthly basis. Use SQL window functions in your solution.

Assume you have access to a table that has the following structure:

Example Input:

The goal is to produce an output that shows the average star rating for each product per month from all reviews submitted during that month. The output should look something like this:

Example Output:

Answer:

Here's a PostgreSQL query that can solve the problem:

This query uses the function as a window function to calculate the average star rating for each product per month. The window is defined by the clause, which instructs PostgreSQL to divide the reviews table into partitions based on and the month of . Within each of these partitions, is calculated, giving us the average rating for each product per month. Finally, we order the output by month and .

To practice a similar window function interview problem which uses RANK() on DataLemur's free interactive coding environment, solve this Amazon SQL Interview Question:

SQL Question 3: Can you describe the concept of database denormalization in layman's terms?

Database denormalization is when you add redundancy to a database, and break typical normalization rules (codified by the 1st, 2nd, 3rd normal forms).

Denormalization is typically used to improve the performance of a database, particularly when the database is being for OLAP (Online Analytical Processing) purposes. By denormalizing a database, you can reduce the number of joins that are required to retrieve data, which can greatly improve the speed of queries since joins are costly and slow. However, denormalization can also introduce some problems, such as increased data redundancy and the need for more complex update and delete operations since data has been duplicated into multiple tables.

In general, denormalization should be used with caution and only after careful consideration of the trade-offs involved. It's typically better to start with a well-normalized database design then denormalize only if your database isn't scaling as well as you want.

SQL Question 4: Track Solar Panel Performances

As a technology company dealing with renewable energy like Solar Energy, SolarWinds needs to monitor, perform checks and balances on the performance output of their solar panels based in different locations.

Your task is to design the database and provide an SQL query that is able to extract average monthly energy output for a given location.

We have two tables: captures the performance of the solar panels i.e. their energy output, and which contains information about each solar panel, including its location.

Example Input:

Example Input:

The goal here is to determine the average energy output per month per location. You should return the month (as a number), the location, and average energy output.

Answer:

This query works by joining the and tables on their panel_id's, then grouping the joined data by month and location. It calculates the average energy output for each group and lists these averages along with their corresponding locations and months.

For example, problem with given sample data solved using this query would yield:

Example Output:

SQL Question 5: Can you explain the concept of a constraint in SQL?

Think of SQL constraints like the rules of a game. Just like a game needs rules to keep things fair and fun, a database needs constraints to keep things organized and accurate.

There are several types of SQL constraints like:

NOT NULL: This constraint is like a bouncer at a nightclub - it won't let anything NULL through the door. UNIQUE: This constraint is like a VIP list - only special, one-of-a-kind values get in. PRIMARY KEY: This constraint is like an elected official - it's made up of NOT NULL and UNIQUE values and helps identify each row in the table. FOREIGN KEY: This constraint is like a diplomatic ambassador - it helps establish relationships between tables. CHECK: This constraint is like a referee - it makes sure everything follows the rules. DEFAULT: This constraint is like a backup plan - it provides a default value if no other value is specified.

So, whether you're playing a game or organizing a database, constraints are an important part of the process!

SQL Question 6: Average Energy Produced by Each Solar Panel Per Day

You are an analyst at SolarWinds, a company that produces solar panels. The company monitors how much energy each solar panel produces each day, and the data is stored in a "production_logs" table. The table has three columns: log_id (int), panel_id (int), energy_produced(kWh).

Write a SQL query to find the average daily energy production per solar panel for the past 30 days.

Example Input:

Example Output:

Answer:

This query groups all records by their panel_id, and averages the energy production per group. The WHERE clause filters out only the logs from the past 30 days. Please note that this query assumes the existence of a 'log_date' column in the 'production_logs' table which contains the date when the log was created. If such a column does not exist in the actual table, this query would need to be modified accordingly.

SQL Question 7: What are the ACID properties in a DBMS?

A DBMS (database management system), in order to ensure transactions are relaible and don't ruin the integrity of the data, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability.

To make this concept more concrete, here is what each of the ACID properties would mean in the context of banking transactions:

• Atomicity: a transaction is either completed fully, or not complete at all. For example, if a customer is transferring money from one account to another, the transaction should either transfer the full amount or none at all.
• Consistency: a transaction will only be completed if it follows all database constraints and checks. For example, if a customer is withdrawing money from an account, the transaction should only be completed if the account has sufficient funds available, otherwise the transaction is rejected
• Isolation: ensures that concurrent transactions are isolated from each other, so that the changes made by one transaction cannot be seen by another transaction. This isolation prevents race conditions, like two customers trying to withdraw money from the same account at the same time.
• Durability: ensures that once a transaction has been committed and completed, the changes are permanent. A reset / shutdown of the database shouldn't erase someone's savings accounts!

SQL Question 8: Click-Through Rate on SolarWinds Ads

SolarWinds, a company in enterprise software solutions, has been running several digital advertising campaigns on different platforms. As a data analyst, you've been provided with two tables. The first table, , contains information about each time an advertisement was delivered. The second table, , contains records only for those ads that were actually clicked on by users.

The table is represented as:

Example Input:

The table is represented as:

Example Input:

Your task is to write a SQL query to provide the click-through rate (CTR) for each ad on each platform by month. The CTR is defined as (number of unique clicks / number of unique ad deliveries) * 100%. You may assume that in both tables corresponds to the same campaign.

Answer:

This query first creates two derived tables and each aggregating the number of ad events and clicks per month per ad respectively. Then it performs a LEFT JOIN using and as the join keys. The final SELECT statement calculates the CTR by dividing the number of clicks by the number of ad events, and multiplying the result by 100 to obtain the percentage.

To solve another question about calculating rates, solve this TikTok SQL question within DataLemur's online SQL code editor:

SQL Question 9: Find the Average Sales of Each Product Per Month

As a data analyst at SolarWinds, you have been asked to analyze the average sales of each product on a monthly basis. SolarWinds sells a range of software products, designed to help businesses manage their networks, systems, and IT infrastructure.

Here is a sample data of table depicting the sale records:

Example Input:

From this data, we want to find out the average sales per product per month. The result should be:

Example Output:

Answer:

In PostgreSQL, you can retrieve this information with the following query:

This query groups the sales data by months and product_id, then computes the average quantity of each group. The function is used to get the month from the column. The result is then ordered by month and product_id.

SQL Question 10: What are the three different normal forms?

The three levels of database normalization (also known as normal forms) are:

First Normal Form (1NF):

• Each column should contain the same type of data (no mixing strings vs. integers)
• Each column in a table contains a single value (no lists or containers of data)
• Each row in the table is unique

Second Normal Form (2NF)

• It's in 1st Normal Form
• All non-key attributes are dependent on the primary key

Said another way, to achieve 2NF, besides following the 1NF criteria, the columns should also be dependent only on that table's primary key.

Third normal form (3NF) if it meets the following criteria:

• It's in 2nd Normal Form
• There are no transitive dependencies in the table.

A transitive dependency means values in one column are derived from data in another column. For example, it wouldn't make sense to keep a column called ""vehicle's age"" and ""vehicle's manufacture date" (because the vehicle's age can be derived from the date it was manufactured).

Although there is a 4NF and 5NF, you probably don't need to know it for the SolarWinds interview.

SQL Question 11: Calculating Energy Production

You are a data analyst at SolarWinds, a company that produces solar panels. Every month, the company wants to calculate the total power produced by each model of their solar panels. They also want to calculate the monthly production over total yearly production to understand the percentage of power each model generates per month for a given year.

The company maintains a log of its solar panel units and the power they generate each day. The table contains the , the date (), the of the solar panel, and the on that day in watt-hours (Wh). The table stores and the .

Every day, the panel's generated power is inherently logged with a margin error of +/- 5%. While calculating monthly power, you need to round the daily value of power generated to the nearest integer.

Note: For this question, disregard leap years and assume all months have 30 days and all years have 360 days.

Example Input:

Example Input:

Answer:

First, aggregate the daily power generated by each model monthly, round the total, then calculate the yearly power generated by each model.

In this query, function truncates the date to the nearest month, making it easy to group by month. The function is used when calculating power to round to the nearest integer, and also when calculating the percentage to one decimal place. The output tells how each model performs each month in terms of total power generated and what proportion of its annual power generation it represents.

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating yearly metrics based on monthly data or this Verizon International Call Percentage Question which is similar for calculating a monthly percentage of a total.

SolarWinds SQL Interview Tips

The best way to prepare for a SolarWinds SQL interview is to practice, practice, practice. Besides solving the above SolarWinds SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Google, Microsoft and Silicon Valley startups.

Each SQL question has multiple hints, step-by-step solutions and crucially, there's an interactive coding environment so you can instantly run your query and have it checked.

To prep for the SolarWinds SQL interview you can also be helpful to solve SQL questions from other tech companies like:

• ManageEngine SQL questions

• Paessler SQL questions

• ConnectWise SQL questions

• Datadog SQL questions

In case your SQL query skills are weak, forget about jumping right into solving questions – go learn SQL with this SQL tutorial for Data Analytics.

This tutorial covers SQL concepts such as inner vs. outer JOIN and CTE vs. Subquery – both of which pop up frequently during SolarWinds SQL assessments.

SolarWinds Data Science Interview Tips

What Do SolarWinds Data Science Interviews Cover?

In addition to SQL query questions, the other types of questions to practice for the SolarWinds Data Science Interview are:

• Statistics & Probability Questions
• Coding Questions in Python or R
• Product Analytics Questions
• Machine Learning Questions
• Resume-Based Behavioral Questions

How To Prepare for SolarWinds Data Science Interviews?

The best way to prepare for SolarWinds Data Science interviews is by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from FAANG & startups
• A Crash Course covering Stats, ML, & Data Case Studies
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