11 Synaptics SQL Interview Questions (Updated 2024)

Updated on

March 2, 2024

At Synaptics, SQL is used frequently for analyzing complex datasets for product performance optimization, and managing customer data to enhance client-specific touch and display solutions. Unsurprisingly this is why Synaptics LOVES to ask SQL questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.

Thus, to help you practice for the Synaptics SQL interview, this blog covers 11 Synaptics SQL interview questions – can you solve them?

11 Synaptics SQL Interview Questions

SQL Question 1: Identifying VIP Users at Synaptics

Imagine you work at Synaptics, a company that specializes in human interface solutions. One critical aspect for the business is the purchase frequency of a product category (like "sensor" or "touchpad"). Synaptics considers users who purchase over 200 units per month in any product category as their VIP (or power) users.

Given the below tables, write a SQL query that identifies these power users. The output of your query should provide the user id, month, product category, and the total number of units purchased in that month.

Example Input:
Example Input:


This query works by first joining the and tables on the column. It then groups the data by user id, user name, purchase month, and product category. Within each group, it sums the number of units purchased. The clause filters out rows where the total units purchased are not over 200. The clause sorts the result in descending order according to the field indicating the user with highest purchase first.

To practice a similar customer analytics SQL question where you can solve it right in the browser and have your SQL code instantly graded, try this Walmart SQL Interview Question: Walmart SQL Interview Question

SQL Question 2: Analyzing Synaptics Product Reviews

As a data analyst in Synaptics, you're tasked with analyzing product reviews. Synaptics has a large number of products and is getting reviews from customers all around the world everyday. Your job is to create a SQL query that will provide a monthly average review rating per product, ordered by month. Write a PostgreSQL query using a window function to solve this.

Example Input:

61711232022-06-08 00:00:00500014
78022652022-06-10 00:00:00698524
52933622022-06-18 00:00:00500013
63521922022-07-26 00:00:00698523
45179812022-07-05 00:00:00698522


The provided SQL query will truncate the date to Month-Year format for easier readability and then calculates the average number of stars for each product per month. The clause combined with produces a calculation window that is defined per month for each product. The clause then arranges the result set by month and product ID.

Example Output:

2022-06-01 00:00:00500013.50
2022-06-01 00:00:00698524.00
2022-07-01 00:00:00698522.50

Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur

DataLemur SQL Questions

SQL Question 3: What are some different ways you can identify duplicate rows in a table?

"One creative way is to use the window function ROW_NUMBER() and partition by whichver columns you are loooking for duplicates in. If any row has a row_number() more than 1, then it's a duplicate!

You could also use COUNT(DISTINCT col1) vs. COUNT(*) and see if they return different numbers, indicating the prescence of duplicates!

Synaptics SQL Interview Questions

SQL Question 4: Filter customers based on product orders and location

Imagine that you are a data analyst at Synaptics. The company would like to run a special marketing campaign targeted at customers who have made more than five orders in the last month and are located in California. They also want to know if these customers have ordered the product with the id 'prod_123'. Write a SQL query that filters customers based on these requirements.

Here is your customer orders table:

Example Input:

And here is your customer information table:

Example Input:
487Adam SmithCalifornia
284Eve JohnsonTexas


This SQL query selects the customer id and name, counts the number of orders, and checks if any of the orders included the product with the id 'prod_123'. The join is done on the customer id field common to both tables. The filter conditions (state is California, and orders in the last month) are applied to the appropriate columns. The HAVING clause is used to filter groups by the count of orders. The CASE statement is used to check if 'prod_123' was ordered, and it returns 'Yes' if true, 'No' otherwise.

SQL Question 5: What does adding 'DISTINCT' to a SQL query do?

The keyword removes duplicates from a query.

Suppose you had a table of Synaptics customers, and wanted to figure out which cities the customers lived in, but didn't want duplicate results.



You could write a query like this to filter out the repeated cities:

Your result would be:


SQL Question 6: Find the average touch points per device type

As a SQL analyst at Synaptics, a company specializing in human interface hardware and software including touchpads for computer laptops, you are asked to track the performance of various device types. Can you write a SQL query to find the average touch points per device type?

Example Input:
Example Input:
Example Output:


This query first joins the and tables on the field. Then it groups by and calculates the average for each group of device type

To practice a very similar question try this interactive New York Times Laptop vs. Mobile Viewership Question which is similar for tracking device usage or this Amazon Server Utilization Time Question which is similar for performing device usage calculations.

SQL Question 7: What does it mean to denormalize a database?

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

Denormalization is done to improve the performance of the database when it is being used for online analytics processing (OLAP), rather than online transaction processing (OLTP) use cases.

For these OLAP use cases, you're bottleneck frequently is joining multiple tables, but de-normalizing your database cuts these outs.

Denormalization can improve query performance by reducing the number of expensive joins required to retrieve data, but it comes with its own drawbacks too. By adding redundant columns, you incur more data storage costs, and there's need for more complex update and delete operations in order to maintain data integrity across all the duplicated data. Thus, it's important to carefully consider the trade-offs involved before implementing denormalization.

SQL Question 8: Analyze Click-Through Conversion Rate

Synaptics needs to understand the overall traffic flow from viewing a product page to adding that product into the cart. From given data, calculate the total number of viewers, total number of click-through (clicked on 'add to cart') and the conversion rate (click-through/ viewers in percentage).

Example Input:
600111107/01/2022 00:00:0040001
650222207/02/2022 00:00:0040001
750333307/03/2022 00:00:0040002
700444407/04/2022 00:00:0040001
800555507/05/2022 00:00:0040002
Example Input:
100111107/01/2022 00:01:0040001
150222207/02/2022 00:01:0040001
250333307/03/2022 00:01:0040002


This sql query first joins the product views table and the product clicks table on product_id and user_id. Then it calculates the total number of unique views and unique clicks for each product_id. The conversion rate is calculated as the number of unique clicks divided by the number of unique views for each product multiplied by 100. A left join is used to include all products that have been viewed but may not have been clicked on.

To practice a similar SQL interview question on DataLemur's free online SQL code editor, attempt this Facebook SQL Interview question: Facebook Click-through-rate SQL Question

SQL Question 9: Determine Highest Selling Products

As a Data Analyst at Synaptics, a leading global technology company widely known for developing human interface solutions such as touchpads for laptop computers, and mobile touchscreen interfaces, you're tasked with understanding the sales trend for different products.

Specifically, for each product category, find the product with the maximum total sales amount for each year. Consider the table which contains the following fields: , , , , and .

Example Input:

Example Output:


The query first extracts the year from the sale date. It then calculates the total sales amount for each product by multiplying the quantity by the price. The clause groups the results by the year, product category, and the product id. The function is used to select the product with the highest total sales for each product category for each year. Results are ordered to display the earliest year first, and within each year, products with higher total sales are displayed first.

SQL Question 10: Could you describe the function of UNION in SQL?


The UNION operator combines the results from multiple SELECT statements into a single result set.

Here's an example of using the UNION operator to combine the results of two SELECT statements that retrieve data from tables of Synaptics's Facebook ads and their Google ads:

This statement would return a combined result set of both Facebook and Google ads that have a spend greater than $200. The result set would include the following columns: ad_id, ad_name, ad_type, impressions, clicks, and spend.

Note that the two SELECT statements within the UNION must have the same number of columns and the columns must have similar data types. In this example, both SELECT statements have the same number of columns and the data types of the columns are all compatible.

SQL Question 11: Finding Customer Records

As a data analyst for Synaptics, you are often required to filter through the company's customer records to find relevant information. Using the 'customers' and 'products' tables, can you write a query to find all the customers who have purchased a product with a product name containing the word 'Touch'?

Example Input:


Example Input:

0002Non-Touch Keyboard49.994256
0003TouchScreen Monitor149.997890
0004Non-Touch Mouse29.993698


This SQL query would generate a table showing all the customers who have bought a product with 'Touch' in the product name. The query joins the 'customers' table with the 'products' table on the 'customer_id' field, and then uses the LIKE operator with the wildcard character '%' to find any products that have 'Touch' in the product name. The output would be a list of customers (first name, last name, and email) along with the 'Touch' product they purchased.

Synaptics SQL Interview Tips

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Synaptics SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the earlier Synaptics SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies. DataLemur Question Bank

Each interview question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there is an online SQL code editor so you can right in the browser run your SQL query answer and have it executed.

To prep for the Synaptics SQL interview you can also be a great idea to solve SQL questions from other tech companies like:

But if your SQL skills are weak, forget about jumping right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.

DataLemur SQL Course

This tutorial covers SQL concepts such as handling missing data (NULLs) and CASE/WHEN statements – both of these pop up routinely during Synaptics SQL interviews.

Synaptics Data Science Interview Tips

What Do Synaptics Data Science Interviews Cover?

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

Synaptics Data Scientist

How To Prepare for Synaptics Data Science Interviews?

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