(Ex-Facebook & Best-Selling Data Science Author)
February 6, 2024
At Analog Devices, SQL does the heavy lifting for analyzing manufacturing process data for improving product quality, and managing inventory records to optimize supply chain effectiveness. That's why Analog Devices asks SQL query questions during interviews for Data Analyst, Data Science, and BI jobs.
In case you're stressed about an upcoming SQL Interview, we've curated 8 Analog Devices SQL interview questions to practice, which are similar to recently asked questions at Analog Devices – able to answer them all?
Analog Devices sells a variety of electronic products. Let’s imagine that you have a table with sales data, and your task is to find the highest selling product (in terms of quantity) for each month.
The SQL query to solve this question would be:
This SQL query works in two parts:
p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur
Analog Devices would like to target a specific group of customers for their upcoming product marketing campaign. Your task is to write a SQL query which filters down the customer records database to only include customers who are located in New York, have purchased more than 5 times from Analog Devices in the past year, and have spent a cumulative amount of over $1000.
The relevant databases available are: 'customers', 'orders', and 'order_details'.
Here's the sample data presented in markdown-formatted tables:
order_id customer_id order_date 101 1 2022-06-08 102 1 2022-07-10 103 2 2022-08-18 104 3 2022-10-26 105 1 2022-12-05
id order_id product_id quantity price 1 101 1 3 $100 2 102 2 2 $200 3 103 3 1 $300 4 104 4 6 $50 5 105 1 2 $100
This query joins the 'customers', 'orders', and 'order_details' tables on the appropriate fields. It then filters for customers who are based in 'New York'. It further filters to only include customers who have more than 5 orders and have spent more than $1000 cumulatively. It results in the first and last names of the customers who meet these criteria. undefined
The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail.
For example, say you had a database that stores ad campaign data from Analog Devices's Google Analytics account.
Here's what some constraints could look like:
In this example, the constraint is used to ensure that the "budget" and "cost_per_click" fields have positive values. This helps to ensure that the data in the database is valid and makes sense in the context of ad campaigns.
You can also use the constraint to ensure that data meets other specific conditions. For example, you could use a constraint to ensure that the "start_date" is before the "end_date" for each ad campaign.
Analog Devices is a multinational semiconductor company specializing in data conversion, signal processing and power management technology. As a data analyst for Analog Devices, your task is to find out the average sales for each product in the past year.
For the purpose of this problem, let's consider only the sales table, which records every sale made in the store.
Here is an example of how the 'sales' table might look:
In the 'sales' table, each row represents a sale. 'sale_id' is the ID of the sale, 'product_id' is the ID of the product sold, 'units_sold' is the number of units of the product sold in that sale, and 'sale_date' is the date of the sale.
Your task is to write a SQL query to find the average sales (in terms of units sold) of each product for the past year.
Here is the PostgreSQL solution:
In this SQL query, we first filter out the sales that occurred in the past year using a WHERE clause. The BETWEEN operator is used to select sales that occurred between '2021-01-01' and '2021-12-31'.
Next, we use the GROUP BY statement to group the sales by 'product_id'. This allows us to calculate the average sales for each product separately.
Finally, we use the AVG function to calculate the average sales for each product. This function takes the 'units_sold' column and calculates the average. This average is then selected in the SELECT statement under the alias 'average_sales'.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating sales data or this Amazon Highest-Grossing Items Question which is similar for examining product sales.
A is a field in a table that references the of another table. It creates a link between the two tables and ensures that the data in the field is valid.
For example, if you have a table of Analog Devices customers and an orders table, the customer_id column in the orders table could be a that references the id column (which is the primary key) in the Analog Devices customers table.
The constraint helps maintain the integrity of the data in the database by preventing the insertion of rows in the table that do not have corresponding entries in the table. It also enforces the relationship between the two tables and prevents data from being deleted from the table if it is still being referenced in the table.
Analog Devices is a multinational semiconductor company. It has plenty of devices across the globe. Each device consumes power to function and the consumption is different for different devices. We regularly log all power usage data in our system.
You need to write an SQL query that can provide the power consumption rounded to nearest integer for each device in January. Also, the query should return the absolute difference between the maximum power used and the square root of the minimum power used by the device for the month.
This SQL query first filters the records to only include those from January. It then groups the results by , and calculates the total power consumption, rounded to the nearest whole number, for each device. Additionally, it finds the absolute difference between the maximum power used and the square root of the minimum power used by each device.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total device usage time or this Google Odd and Even Measurements Question which is similar for handling different device measurements.
is used to combine the results of multiple statements into a single result set.
Suppose you were doing an HR Analytics project for Analog Devices, and needed to analyze both Analog Devices's contractors and employees. You could use in the following way:
This statement would return a combined result set of Analog Devices contractors and employees who were hired after the start of the year 2023.
As a Data Analyst at Analog Devices, you work with data coming from various devices that record the temperature. Each device periodically records temperature readings and the timestamp for each reading. The management wants an overview of the average temperature reported by each device per month for the year 2022.
Consider the following table, , which contains all the temperature data:
The management is interested in a report that looks like this:
You can use the following SQL block to answer this question:
The SQL code groups temperature readings by month and device, then calculates the average temperature. The WHERE clause filters for readings from the year 2022. Finally, it orders the result by month, then by device id. Note that the TO_CHAR function is used to extract the month from the timestamp, and the AVG function calculates the average temperature. undefined
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Analog Devices SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the above Analog Devices SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like FAANG tech companies and tech startups.
Each DataLemur SQL question has hints to guide you, full answers and crucially, there's an interactive coding environment so you can instantly run your SQL query and have it checked.
To prep for the Analog Devices SQL interview you can also be wise to solve SQL questions from other tech companies like:
However, if your SQL query skills are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
For the Analog Devices Data Science Interview, besides SQL questions, the other types of questions which are covered:
To prepare for Analog Devices Data Science interviews read the book Ace the Data Science Interview because it's got: