10 VisEra Technologies SQL Interview Questions (Updated 2024)
At VisEra Technologies, SQL is used across the company for analyzing customer behavior to optimize user experience, and managing complex data sets crucial to developing AI-powered visualization tools. Unsurprisingly this is why VisEra Technologies typically asks SQL problems during interviews for Data Science, Data Engineering and Data Analytics jobs.
Thus, to help you study for the VisEra Technologies SQL interview, here’s 10 VisEra Technologies SQL interview questions – able to solve them?
10 VisEra Technologies SQL Interview Questions
SQL Question 1: Identifying Power Users in VisEra Technologies
As a Data Analyst at VisEra Technologies, your task is to identify power users from the customer database. In the context of VisEra, a power user is considered to be a user who has used the most number of distinct products and provided the highest number of reviews in the last 6 months within our database.
Write a SQL query to find the top 3 power users, sorted by the number of distinct products used and the number of reviews given in descending order. In case of a tie, sort the users by user_id in ascending order.
Example Input:
| user_id | product_id | review_date |
|---|---|---|
| 1 | 1001 | 01/20/2022 |
| 1 | 1002 | 01/25/2022 |
| 1 | 1001 | 02/20/2022 |
| 2 | 1003 | 02/28/2022 |
| 2 | 1001 | 03/01/2022 |
| 2 | 1003 | 03/05/2022 |
| 3 | 1002 | 01/20/2022 |
| 3 | 1001 | 01/20/2022 |
| 3 | 1002 | 06/20/2022 |
Answer:
This query first filters for user activity within the last 6 months. It then counts the number of reviews and the number of distinct products that each user has reviewed during this period. The results are grouped by user_id, the number of distinct products, and the number of reviews to eliminate duplicates, and then sorted as required. The top 3 power users are then selected with the LIMIT clause.
To solve a related super-user data analysis question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question:
SQL Question 2: Calculate Monthly Average Ratings for Products
As an analyst at VisEra Technologies, you are given a table containing customer reviews for various products. Each review contains a product_id, submit_date and the stars given by the user. Your task is to write a SQL query that calculates the average star rating for each product on a monthly basis.
The table is structured as follows:
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-08-06 | 50001 | 4 |
| 7802 | 265 | 2022-10-06 | 69852 | 4 |
| 5293 | 362 | 2022-18-06 | 50001 | 3 |
| 6352 | 192 | 2022-26-07 | 69852 | 3 |
| 4517 | 981 | 2022-05-07 | 69852 | 2 |
Your output should return each product's monthly average star rating in the following format:
Example Output:
| month | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
This SQL query first extracts the month from the using the function. Then it calculates the average of using the function for each per month. The clause is used to organize the data into groups by month and product_id, and is used to sort the result by the month and average stars in descending order.
To practice a similar window function question on DataLemur's free online SQL code editor, solve this Google SQL Interview Question:
SQL Question 3: What does the constraint do?
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 VisEra Technologies 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 VisEra Technologies 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.
SQL Question 4: Database Design for Booking Management System
Given that VisEra Technologies is a versatile company that designs and produces field emission display (FED) related equipment and materials, imagine they want to diversify their portfolio by launching a new venture, a venue booking management system. This new system will allow users to book various venues for different types of events.
You are required to design a simple database schema to handle this system. The business requirements are as follows:
- Users should be able to create an account
- Venues need to be listed with attributes like address, capacity, and pricing
- Users can book a venue for a specific date and time span
- Users can rate and review the venues they have booked.
Using the above requirements, design the relevant tables, detail the relationships between these tables, and consider which columns belong to which tables. In addition, describe any database performance considerations one should have for this specific design.
Example Input:
| user_id | name | register_date |
|---|---|---|
| 1 | John Doe | 07/01/2022 |
| 2 | Jane Smith | 07/10/2022 |
| 3 | Alice Johnson | 07/15/2022 |
Example Input:
| venue_id | address | capacity | pricing |
|---|---|---|---|
| 1 | 123 Main St, City, Country | 200 | 3000 |
| 2 | 456 High St, City, Country | 100 | 2000 |
| 3 | 789 Low St, City, Country | 50 | 1000 |
Example Input:
| booking_id | user_id | venue_id | booking_date | time_span |
|---|---|---|---|---|
| 1 | 1 | 2 | 08/01/2022 | 14:00-18:00 |
| 2 | 2 | 3 | 08/05/2022 | 10:00-15:00 |
| 3 | 3 | 1 | 08/10/2022 | 09:00-13:00 |
Example Input:
| review_id | user_id | venue_id | rating | review |
|---|---|---|---|---|
| 1 | 1 | 2 | 4 | Great venue but quite expensive |
| 2 | 2 | 3 | 3 | Small but cozy |
| 3 | 3 | 1 | 5 | Spacious and well priced |
Answer:
The design of this system involves multiple tables where relationships exist between users, venues, bookings, and reviews. Here is an Query to get the average rating for each venue.
This query fetches the average rating of each venue by joining the and tables on , grouping the results by and , and ordering the results in descending order by the average rating.
In terms of performance considerations, indices should be created on and fields across tables as these would be commonly used fields for JOIN operations. Indexing these fields will significantly speed up these database operations. Additionally, keeping the table normalized will enhance performance when querying for average ratings, since the computation will occur on fewer rows.
SQL Question 5: Name the different types of joins in SQL. What does each one do?
Using a join in SQL, you can retrieve data from multiple tables and merge the results into a single table.
In SQL, there are four distinct types of JOINs. To demonstrate each kind, 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.
-
: An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
-
: A LEFT JOIN 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.
-
: A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
SQL Question 6: Filter Customers Based on Subscriptions and Activity
As a Data Analyst of VisEra Technologies, we've been tasked to develop a list of active customers who have a subscription to either 'Product X' or 'Product Y', but not both, and have placed at least one order within the last 6 months. A customer is considered an 'active' customer if they have logged in within the last 30 days.
Example Input:
| customer_id | customer_name | last_login_date |
|---|---|---|
| 1 | John Smith | 02/04/2022 |
| 2 | Jane Doe | 08/20/2022 |
| 3 | Mary Johnson | 09/01/2022 |
| 4 | James Brown | 05/30/2022 |
| 5 | Patricia Davis | 08/01/2022 |
Example Input:
| customer_id | product |
|---|---|
| 1 | Product X |
| 2 | Product Y |
| 3 | Product X |
| 3 | Product Y |
| 4 | Product Y |
| 5 | Product X |
Example Input:
| order_id | customer_id | order_date |
|---|---|---|
| 101 | 1 | 01/01/2022 |
| 102 | 2 | 07/27/2022 |
| 103 | 3 | 06/23/2022 |
| 104 | 4 | 05/06/2022 |
| 105 | 5 | 09/01/2022 |
Answer:
The above query first creates subquery that identifies any customers who have subscriptions to both 'Product X' and 'Product Y'. It then filters out those customers, in addition to any customers who haven't logged in within the past 30 days or haven't placed an order within the last 6 months. The remaining customers are those who fit all the conditions: active, have ordered in the last 6 months, and have a subscription to either 'Product X' or 'Product Y ', but not both.
SQL Question 7: In SQL, are blank spaces the same as a NULL?
A value represents a missing or unknown value. It is different from a zero or a blank space, which are actual values.
It's important to handle values properly in SQL because they can cause unexpected results if not treated correctly. For example, comparisons involving values always result in . Also values are not included in calculations. For example, will ignore values in the column.
SQL Question 8: Analyze Product Sales and Customer Age
As a Data Analyst at VisEra Technologies, you are given two tables and . The table has columns: (unique identifier for the sale), (identifier for the product sold), (identifier for the customer who bought the product), (number of products sold in the sale), and (date of the sale, in format 'yyyy-mm-dd').
The table has columns (unique identifier for customers), , and .
Write a SQL Query to find the average purchase quantities for each product, presenting the results separately for two age groups of customers: ‘Under 30’ and '30 and Above'. Assume today's date is '2022-09-10'.
Example Input:
| sale_id | product_id | customer_id | quantity | sale_date |
|---|---|---|---|---|
| 001 | 123 | 898 | 5 | 2022-05-17 |
| 002 | 123 | 545 | 3 | 2022-06-05 |
| 003 | 456 | 898 | 2 | 2022-06-10 |
| 004 | 123 | 789 | 2 | 2022-09-01 |
| 005 | 123 | 321 | 2 | 2022-06-18 |
Example Input:
| customer_id | first_name | last_name | date_of_birth |
|---|---|---|---|
| 898 | John | Doe | 1992-10-12 |
| 545 | Jane | Doe | 1982-04-25 |
| 789 | Joe | Bloggs | 1996-11-19 |
| 321 | Jill | Johnson | 1991-05-11 |
Answer:
The solution first calculates the age of each customer and categorizes them into age groups in the CTE named 'customer_age'. This CTE is then joined with table on to calculate the average purchase quantities for each in the different age groups.
Because joins come up routinely during SQL interviews, practice this Spotify JOIN SQL question:
SQL Question 9: Calculate Average Monthly Purchase Price After Discounts
VisEra Technologies, a tech product retailer, provides periodic discounts on its products. You need to write a SQL query which calculates the average purchase price after applying all discounts per product category for each month of the year 2022.
Assume we have two tables, and . The table keeps track of the , (e.g., 'Electronics', 'Furniture', etc.), and of each product. The table logs each purchase: , , , , and (how much the base price was discounted for this purchase).
Example Input:
| product_id | category | base_price |
|---|---|---|
| 1 | Electronics | $200 |
| 2 | Furniture | $800 |
| 3 | Office Supplies | $20 |
Example Input:
| purchase_id | customer_id | product_id | purchase_date | discount_percentage |
|---|---|---|---|---|
| 10 | 1001 | 1 | 01/15/2022 | 0.1 |
| 11 | 1002 | 3 | 02/20/2022 | 0.0 |
| 12 | 1001 | 2 | 03/10/2022 | 0.15 |
| 13 | 1003 | 1 | 04/30/2022 | 0.2 |
| 14 | 1002 | 3 | 05/25/2022 | 0.05 |
Example Output:
| mth | category | avg_discounted_price |
|---|---|---|
| 1 | Electronics | $180 |
| 2 | Office Supplies | $20 |
| 3 | Furniture | $680 |
| 4 | Electronics | $160 |
| 5 | Office Supplies | $19 |
Answer:
This SQL query first extracts the month from the purchase date, and computes the discounted price (base price times one minus the discount rate) for each purchase. It groups the purchases by month and product category, and calculates the average of the sales in each group. The results are ordered by month and then product category.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for requiring category-based aggregation or this Amazon Average Review Ratings Question which is similar for needing to calculate monthly averages.
SQL Question 10: When would you use the function?
The COALESCE() function can be used to replace NULL values with a specified value. For instance, if you are a Data Analyst at a company and are working on a customer analytics project to identify the most engaged customers, you may have access to the following data in the table:
| customer_id | email_engagement | sms_engagement |
|---|---|---|
| 101 | moderately_active | not_opted_in |
| 201 | un-subscribed | NULL |
| 301 | NULL | not_opted_in |
| 401 | not_active | very_active |
| 501 | very_active | very_active |
| 601 | NULL | NULL |
Before you could procede with your analysis, you would need to remove the NULLs, and replace them with the default value for email engagement (not_active), and the default sms_engagement level (not_opted_in).
To do this, you'd run the following query:
This would get you the following output:
| customer_id | email_engagement | sms_engagement |
|---|---|---|
| 101 | moderately_active | not_opted_in |
| 102 | un-subscribed | not_opted_in |
| 103 | not_active | not_opted_in |
| 104 | not_active | very_active |
| 105 | very_active | very_active |
| 106 | not_active | not_opted_in |
How To Prepare for the VisEra Technologies SQL Interview
The key to acing a VisEra Technologies SQL interview is to practice, practice, and then practice some more!
Beyond just solving the earlier VisEra Technologies SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Netflix, Google, and Amazon.
Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and best of all, there is an interactive coding environment so you can instantly run your SQL query and have it checked.
To prep for the VisEra Technologies SQL interview it is also a great idea to solve interview questions from other tech companies like:
However, if your SQL coding skills are weak, forget about diving straight into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers topics including filtering groups with HAVING and creating pairs via SELF-JOINs – both of which come up frequently during SQL job interviews at VisEra Technologies.
VisEra Technologies Data Science Interview Tips
What Do VisEra Technologies Data Science Interviews Cover?
Beyond writing SQL queries, the other types of problems to practice for the VisEra Technologies Data Science Interview are:
- Stats Interview Questions
- Python Pandas or R Coding Questions
- Product-Sense and Business Case Questions
- ML Interview Questions
- Behavioral Based Interview Questions
How To Prepare for VisEra Technologies Data Science Interviews?
To prepare for VisEra Technologies Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG & startups
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