# 9 Symbotic SQL Interview Questions (Updated 2024)

Updated on

March 3, 2024

At Symbotic, SQL is used quite frequently for analyzing warehouse robotics data, and generating detailed reports regarding material handling automation efficiency. Unsurprisingly this is why Symbotic LOVES to ask SQL problems in interviews for Data Science, Data Engineering and Data Analytics jobs.

To help you study for the Symbotic SQL interview, we've curated 9 Symbotic SQL interview questions – can you solve them?

## 9 Symbotic SQL Interview Questions

### SQL Question 1: Analyze the Equipment's Operational Time

Symbotic uses advanced autonomous robots and an innovative system to automate warehouse operations. Consider these operations involve various equipment that each has an operation start time and end time. Your task is to analyze the operational time per equipment each day and rank them based on their total operating time (from longest to shortest). If they have the same total operating time, order them by their earliest start_time in a day.

For this exercise, you have two tables:

##### Example Input:
equipment_idequipment_type
101Autonomous Robot
102Conveyor
103Sorter
104Palletizer

and

##### Example Input:
log_idequipment_idstart_timeend_time
100110102/01/2023 08:00:0002/01/2023 12:00:00
100210102/01/2023 13:00:0002/01/2023 18:00:00
100310202/01/2023 08:00:0002/01/2023 16:00:00
100410302/01/2023 09:00:0002/01/2023 14:00:00
100510402/01/2023 09:45:0002/01/2023 15:45:00

The following SQL query will solve the task:

The above query first generates a temporary table () consisting of each equipment's , , operational , , and . It then ranks them based on and within each using a window function.

To solve a similar window function interview problem which uses RANK() on DataLemur's free online SQL coding environment, try this Amazon SQL question asked in a BI Engineer interview:

### SQL Question 2: Determine the Average Time for Each Robot to Complete a Task

Symbotic is well known for its advanced autonomous mobile robots. There might be an interest in determining how efficiently these robots are operating on average. Therefore, your task for the interview is to write a SQL query that finds the average time each robot takes to complete a task, in order to help Symbotic track and improve its robots' performance.

Here is some sample data.

##### Example Input:
101108/30/2022 09:00:0008/30/2022 09:15:00
102108/30/2022 09:30:0008/30/2022 09:45:00
103208/30/2022 10:00:0008/30/2022 10:20:00
104208/30/2022 10:30:0008/30/2022 10:55:00
105308/30/2022 11:00:0008/30/2022 11:15:00

We are looking for output that shows the average time each robot takes to complete a task.

##### Example Output:
robot_idavg_time_in_minutes
115.00
222.50
315.00

This query works by first calculating the time difference between the start and end times of each task for each robot, converting the difference to minutes using PostgreSQL's function and , and then taking the average of these times for each distinct robot. It does this using grouping and aggregate functions, which are common SQL tools for summarizing data.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total time utilizing resources or this Tesla Unfinished Parts Question which is similar for determining status of tasks in progress.

### SQL Question 3: What is database denormalization, and when is it a good idea to consider it?

Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).

Here's 3 reasons to de-normalize a database at Symbotic:

1. Improved performance: Denormalization can often improve performance by reducing the number of expensive join operations required to retrieve data. This is particularly useful when the database is being used for online analytical processing (OLAP) as frequent joins across multiple tables can be slow and costly.

2. Scalability: Denormalization can increase the scalability of a database by requiring less data to be read and processed when executing a query. This can be beneficial when the database is expected to handle a high volume of queries.

3. Simplification: One way to simplify the design of a database is by using denormalization to reduce the number of tables and relationships that need to be managed. This can make the database easier to understand and maintain.

### SQL Question 4: Analyze the Click-Through-Rates for Symbotic's Digital Ads

Symbotic is a robotics company that often uses digital marketing campaigns to promote its products. A common metric they use to measure the effectiveness of their campaigns is the click-through rate (CTR), which is the proportion of users who clicked on a particular ad after viewing it. Recently, they launched a new product and they would like to know its CTR.

We have two tables. The table records each time a user views an ad.

##### Sample Input:
10179992022-08-01 00:00:0066
10897772022-08-01 00:00:0066
16255552022-08-02 00:00:0066
20393332022-08-03 00:00:0066
29711112022-08-04 00:00:0066

The table records each time a user clicks an ad.

##### Sample Input:
59019992022-08-01 00:00:0066
65475552022-08-02 00:00:0066
71051112022-08-04 00:00:0066

They want to know the daily CTR for their new product. The CTR is calculated as the number of unique clicks divided by the number of unique views.

In our sample data for product_id 66, on 2022-08-01, there were 2 unique views and 1 unique click. Therefore, the click-through rate for this product on this date is 1/2, or 50.00%. Similarly, we calculate the click-through rate for the rest of the dates.

Following this method, Symbotic would be able to track the effectiveness of their product ads' click-through rates over time.

To solve a similar problem about calculating rates, try this TikTok SQL question on DataLemur's online SQL coding environment:

### SQL Question 5: Can you describe the difference between a unique and a non-unique index?

Unique indexes help ensure that there are no duplicate key values in a table, maintaining data integrity. They enforce uniqueness whenever keys are added or changed within the index.

To define a unique index in PostgreSQL, you can use the following syntax:

To define a non-unique index in PostgreSQL, you can use the following syntax:

Non-unique indexes on the other hand, are used to improve query performance by maintaining a sorted order of frequently used data values, but they do not enforce constraints on the associated table.

### SQL Question 6: Highest Stock Occupancy Rate

Symbotic is a company that provides intelligent robotic systems for warehouses to enhance storage density and order picking efficiency. For a company like Symbotic, we can ask a question like:

What was the maximum occupancy rate by warehouse each month in the last year? The occupancy rate can be defined as items stored per unit space.

To find the solution, we need two tables: and .

##### Example Input:
warehouse_idcapacity
W12000
W23000
W32500
##### Example Input:
datewarehouse_iditems_stored
2022-01-15W11500
2022-01-30W22500
2022-01-30W32000
2022-02-10W11900
2022-02-15W22900
2022-02-20W32250

We want the output to look something like this:

##### Example Output:
year_monthwarehouse_idoccupancy_rate
2022-01W10.75
2022-01W20.83
2022-01W30.80
2022-02W10.95
2022-02W20.97
2022-02W30.90

The SQL query to generate the output would look something like this:

This query first joins the and tables on warehouse_id. Using the clause we collect data per month for each warehouse (DATE_TRUNC('month', stocks.date)::date being used to extract the month and year from the column). We calculate the occupancy rate as the maximum number of items stored in a month divided by the warehouse capacity. This query provides the maximum occupancy rate by month for each warehouse. Finally, we order the results by the year and month, and by the occupancy rate in descending order.

### SQL Question 7: What does do?

is used to combine the output of multiple statements into one big result!

For a concrete example, say you were doing an HR Analytics project for Symbotic and needed to analyze both Symbotic's employees and contractors who were hired after 2022 started. You could use in the following way:

### SQL Question 8: Analyze Customer Database and Join with Associated Tables

Consider the following hypothetical situation for Symbotic: we have a customer database and an order details database for the company. The customer database includes information such as , , , , and . The order details database includes , , , , and .

In your role as a data analyst, you are asked to generate a report that displays each , the , and they purchased.

Sample tables:

##### Example Input
customer_idfirst_namelast_nameemailzip_code
101DavidJonesdavid.jones@email.com00001
102SarahMillersarah.miller@email.com00002
##### Example Input
order_idcustomer_idproduct_idquantityorder_date
5001101400222021-08-15
5002102300112021-08-15
5003102400232021-08-15
5004103200312021-08-15
5005101100422021-08-16

The SQL query above combines the table and the table using an INNER JOIN, merging them based on the . It then counts the total number of orders (using ) and the total quantity of products (using ) per customer, and finally groups the data by each customer's full name (constructed by concatenating and ).

Because joins come up frequently during SQL interviews, try an interactive Spotify JOIN SQL question:

### SQL Question 9: Symbotic Robot Usage Analysis

As an analyst at Symbotic, which provides autonomous robots for warehouse automation, you are interested in understanding the robot usage patterns. Specifically, you want to know the Robotics System Usage by Day.

Given a table called , each row of which represents an activity made by a certain robot on a certain day, write a SQL query to find the total number of activities created by each robot per day.

The table:

activity_idrobot_idactivity_timestampactivity_type
1ROB12022-03-01 08:05:00Pick
2ROB12022-03-01 08:15:00Transfer
3ROB22022-03-01 09:10:00Pick
4ROB12022-03-02 08:05:00Transfer
5ROB22022-03-02 08:45:00Pick
6ROB22022-03-02 08:55:00Transfer
7ROB22022-03-02 09:05:00Pick
8ROB12022-03-03 08:10:00Transfer
9ROB12022-03-03 08:20:00Pick
10ROB22022-03-03 09:05:00Transfer

This SQL query groups the activities by robot id and the date (ignoring the time) of the activity timestamp, and then counts the total number of rows for each group, which corresponds to the total number of activities per robot per day. The results are then ordered by robot id and date for easy readability.

### Symbotic SQL Interview Tips

The key to acing a Symbotic SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Symbotic SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).

Each SQL question has multiple hints, detailed solutions and best of all, there's an interactive SQL code editor so you can easily right in the browser your query and have it executed.

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

But if your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this SQL interview tutorial.

This tutorial covers topics including filtering with LIKE and CTE vs. Subquery – both of these come up often during SQL interviews at Symbotic.

### Symbotic Data Science Interview Tips

#### What Do Symbotic Data Science Interviews Cover?

In addition to SQL query questions, the other types of questions covered in the Symbotic Data Science Interview are:

#### How To Prepare for Symbotic Data Science Interviews?

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

• 201 Interview Questions from FAANG tech companies
• A Refresher on Python, SQL & ML
• Amazing Reviews (900+ reviews, 4.5-star rating)