8 Samsara SQL Interview Questions (Updated 2024)
At Samsara, SQL is used across the company for extracting real-time vehicle and fleet data for analysis and creating data pipelines to handle high-volume industrial IoT data. That's why Samsara almost always asks SQL questions during interviews for Data Science, Analytics, and & Data Engineering jobs.
So, to help you practice for the Samsara SQL interview, we've collected 8 Samsara SQL interview questions – able to answer them all?
8 Samsara SQL Interview Questions
SQL Question 1: Identify power users from Samsara
Samsara is an Internet of Things (IoT) company that provides sensors, software, and cloud services to connect commercial and industrial equipment. Often, the object is to identify power users, which are those who interact most frequently and heavily with these services.
For the purpose of this question, let's assume that a power user is defined as a user who interacts with Samsara's sensor data more than average. In this context, interaction would be generating data through the sensors or analyzing data delivered by the sensors, like dashboard access and data generation events.
Example Input:
| activity_id | user_id | activity_time | activity_type |
|---|---|---|---|
| 101 | 123 | 06/08/2022 00:00:00 | Data Generation |
| 102 | 265 | 06/10/2022 00:00:00 | Data Generation |
| 103 | 123 | 06/18/2022 00:00:00 | Dashboard Access |
| 104 | 192 | 07/26/2022 00:00:00 | Data Generation |
| 105 | 981 | 07/05/2022 00:00:00 | Dashboard Access |
| 106 | 192 | 07/26/2022 00:00:00 | Dashboard Access |
| 107 | 981 | 07/05/2022 00:00:00 | Data Generation |
| 108 | 192 | 07/26/2022 00:00:00 | Data Generation |
Design a SQL query that identifies these power users. Assume each 'activity_id' represents a unique interaction. The output should display the user_ids of every power user and the total number of interactions they've had.
Answer:
This query first groups the user_activity table by user_id and counts the number of their interactions. It then filters out those that interact less frequently than the average by using a subquery to calculate and compare against the average number of interactions per user. Finally, those who have above-average interactions are listed in order of most interactions to least.
To practice a similar customer analytics SQL question where you can code right in the browser and have your SQL code automatically checked, try this Walmart SQL Interview Question:
SQL Question 2: Fleet Analysis in Samsara
You are a Data Analyst at Samsara which is a company that creates products for fleet management. You've been provided with a table which comprises of details regarding different vehicles in your fleet. Each entry in this table signifies the status update from one vehicle.
The columns in the table are as follows:
- : a unique identifier of each status update.
- : identifier for the vehicle.
- : the location of the vehicle at the time of the status update.
- : the time when the status update was received.
You're requested to write a query which returns the latest location of each vehicle and also calculate the total number of status updates received from each vehicle.
Example Input:
| update_id | vehicle_id | location | update_time |
|---|---|---|---|
| 1240 | V101 | San Francisco | 2021-09-01 1:00:00 |
| 2401 | V102 | Los Angeles | 2021-09-01 1:30:00 |
| 1809 | V101 | San Jose | 2021-09-01 2:00:00 |
| 2103 | V102 | San Diego | 2021-09-01 3:00:00 |
| 3312 | V101 | Sacramento | 2021-09-01 4:00:00 |
Answer:
Considering the conditions given in the question, Window Function can be a well-suited option.
The subquery in the script will assign a unique row number starting from one to each row in the partition and in descending order of . The outer SELECT statement gets only the rows where as that row has the latest for each . The COUNT OVER function is then used to calculate the total updates received from each vehicle.
To practice another window function question on DataLemur's free interactive SQL code editor, try this Amazon SQL question asked in a BI Engineer interview:
SQL Question 3: Can you describe a cross-join and its purpose?
A cross-join, also referred to 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 with a row for each possible combination of rows from the two input tables.
For example, say you worked on the Marketing Analytics team at Samsara, and were tasked to understand what advertising copy (text) goes best with what advertising creative (the photo that gets used along with the text 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 Samsara. 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! As a result, it's important to use cross-joins judiciously, and make sure that you're not generating more data than you need to.
SQL Question 4: Analyze Product Purchases Per Customer Segment
Samsara is a company specialized in Industrial IoT. The company gathers data from various sensors and this data is analyzed in order to improve business operations efficiency. Let's say that you are given two tables. One called that contains information on each customer including customer , (the industry sector of the customer), and .
Another table is called and it contains information about each IoT sensor that a customer bought, including , , and .
Write a SQL query to analyze the total spending on IoT sensors in each sector for all customers from California.
Example Input:
| id | sector | location |
|---|---|---|
| 4987 | Manufacturing | California |
| 5362 | Construction | New York |
| 6735 | Transportation | California |
| 7920 | Agriculture | Texas |
Example Input:
| product_id | customer_id | purchase_date | price |
|---|---|---|---|
| 6351 | 4987 | 2022-06-08 | 500.00 |
| 7802 | 5362 | 2022-06-10 | 350.00 |
| 5293 | 6735 | 2022-06-18 | 200.00 |
| 6352 | 7920 | 2022-07-26 | 400.00 |
Answer:
In the SQL query above, we are joining the and tables on the in the table and in the table. We only consider rows where is 'California'. The in each sector is the sum of the of the products purchased in that sector.
Because joins come up frequently during SQL interviews, try an interactive Spotify JOIN SQL question:
SQL Question 5: What's the difference between a left and right join?
Both types of joins in SQL help you retrieve data from multiple tables and merge the results into a single table.
To demonstrate the difference between a left join versus a right join, imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
A retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
SQL Question 6: Calculate Device Average Uptime
The Samsara company needs to understand how reliable their devices have been over the past year. Each device sends a signal to the server every time it is turned on or off. Suppose the table captures these signals, having the , (a string can be 'ON' or 'OFF'), and the of each status change.
The company wants to know the average uptime (in minutes) of each device over the last year. The uptime is the period when a device is in ON status, and the average uptime is the total uptime over the total OFF periods. Assume that all devices were turned OFF at the start of the year (01-01-2022 00:00:00).
Example Input:
| log_id | device_id | status | timestamp |
|---|---|---|---|
| 1 | A1 | ON | 01-01-2022 01:20:00 |
| 2 | A1 | OFF | 01-01-2022 03:30:00 |
| 3 | A2 | ON | 01-01-2022 02:15:00 |
| 4 | A2 | OFF | 01-01-2022 05:15:00 |
| 5 | A1 | ON | 01-01-2022 08:00:00 |
| 6 | A1 | OFF | 01-01-2022 12:00:00 |
| 7 | A2 | ON | 01-01-2022 10:00:00 |
| 8 | A2 | OFF | 01-01-2022 14:00:00 |
Example Output:
| device_id | average_uptime(minutes) |
|---|---|
| A1 | 210.00 |
| A2 | 195.00 |
Answer:
In this query, we use the window function to get the previous timestamp of each OFF status, which represents the beginning of an uptime. The difference between the current timestamp and the lag timestamp gives us the uptime. Then we compute the average uptime for each device_id with arithmetic operation and aggregate function AVG. We also use to convert the interval uptime to seconds, and then divide by 60 to get the uptime in minutes. Finally, we use to make the result more readable.
The two most similar questions to the given SQL problem would be:
- "Server Utilization Time" from Amazon: It involves computing the total uptime of servers, similar to how the given problem involves calculating device uptime.
- "Odd and Even Measurements" from Google: This question also involves working with IoT device data and might require similar handling of timestamps and statuses.
Here's the generated markdown:
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for grappling with uptime calculations or this Google Odd and Even Measurements Question which is similar for working with device data and timestamps.
SQL Question 7: Can you explain the difference between the and window functions in SQL?
As the name implies, the window function ranks each row within your window/partition. If two rows have the same rank, the next number in the ranking will be the previous rank plus the number of duplicates. For example, if you've got three records tied for 5th place, they'll get the values 5, 6, and 7, and the next row after this 3-way tie will have a rank of 8.
The function assigns a distinct rank to each row within a partition based on the provided column value with no gaps. This function will assign the same rank to two rows if they have the same rank, and give the next row the next rank number. To make this more concrete, imagine you had three records at rank 5 – then, the next rank would be 6.
SQL Question 8: Trip Duration Analysis
As an analyst at Samsara, a company that provides services for connected operations in the physical world, you have access to the following tables of the company's vehicle database:
- table:
- table:
Can you write a query that will indicate the average trip duration (in minutes) for each vehicle type, only considering trips that occurred within a year of the vehicle's purchase date?
Answer:
In this query, we join the two tables on . The clause is used to include only the trips that occurred within one year of the vehicle's purchase date. The function is used to calculate average trip duration and is used to calculate trip length in minutes. Here, means the number of seconds since . We wrap this in the function to calculate the average duration across trips and group the results by .
Preparing For The Samsara SQL Interview
The key to acing a Samsara SQL interview is to practice, practice, and then practice some more!
In addition to solving the earlier Samsara SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like FAANG tech companies and tech startups.
Each problem on DataLemur has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there's an interactive SQL code editor so you can instantly run your SQL query answer and have it executed.
To prep for the Samsara SQL interview it is also a great idea to solve interview questions from other tech companies like:
However, if your SQL skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers SQL topics like CTE vs. Subquery and window functions like RANK() and ROW_NUMBER() – both of these pop up often during SQL job interviews at Samsara.
Samsara Data Science Interview Tips
What Do Samsara Data Science Interviews Cover?
Beyond writing SQL queries, the other types of problems to prepare for the Samsara Data Science Interview are:
- Stats Interview Questions
- Coding Questions in Python or R
- Product-Sense and Business Case Questions
- ML Interview Questions
- Resume-Based Behavioral Questions
How To Prepare for Samsara Data Science Interviews?
To prepare for Samsara Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG & startups
- a crash course covering Stats, ML, & Data Case Studies
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