Data Analysts and Data Engineers at Align Technology write SQL queries for analyzing patient dental data to identify trends that can result to product improvements. They also use SQL for managing databases related to dental product development, ensuring that innovations meet patient needs, for this reason, Align Technology asks SQL interview questions during interviews.
Thus, to help you prep, we've curated 10 Align Technology SQL interview questions – can you solve them?
Assume that Align Technology, the company known for the Invisalign system, collects product reviews from their users regularly. Each product review contains a star rating (from 1 to 5), the user ID, review ID, product ID, and the date when the review was submitted.
Please write a SQL query to find the average rating of each product per month. Specifically, the result should contain three columns: the year and month (YYYY-MM) when the reviews were submitted, product ID, and the average rating for the product in that month.
review_id | user_id | submit_date | product_id | stars |
---|---|---|---|---|
6171 | 123 | 2022-04-06 | 50001 | 3 |
7802 | 265 | 2022-04-10 | 69852 | 4 |
5293 | 362 | 2022-04-01 | 50001 | 5 |
6352 | 192 | 2022-05-26 | 69852 | 5 |
4517 | 981 | 2022-05-01 | 69852 | 3 |
month_review | product_id | avg_stars |
---|---|---|
2022-04 | 50001 | 4.00 |
2022-04 | 69852 | 4.00 |
2022-05 | 69852 | 4.00 |
This SQL query first converts the to a string of format 'YYYY-MM', then groups the reviews by this newly created and . After that, it calculates the average star rating for each group and sorts the result by and .
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
Learn about Align Technology's innovative Invisalign system and how it is transforming orthodontic treatment! This knowledge can help you understand the advancements in dental technology and their impact on patient care.
Suppose you had a table of Align Technology employee salary data. Write a SQL query to find the top 3 highest paid employees within each department.
employee_id | name | salary | department_id |
---|---|---|---|
1 | Emma Thompson | 3800 | 1 |
2 | Daniel Rodriguez | 2230 | 1 |
3 | Olivia Smith | 2000 | 1 |
4 | Noah Johnson | 6800 | 2 |
5 | Sophia Martinez | 1750 | 1 |
8 | William Davis | 6800 | 2 |
10 | James Anderson | 4000 | 1 |
department_id | department_name |
---|---|
1 | Data Analytics |
2 | Data Science |
department_name | name | salary |
---|---|---|
Data Analytics | James Anderson | 4000 |
Data Analytics | Emma Thompson | 3800 |
Data Analytics | Daniel Rodriguez | 2230 |
Data Science | Noah Johnson | 6800 |
Data Science | William Davis | 6800 |
Code your solution to this problem interactively on DataLemur:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the solution above is hard to understand, you can find a detailed solution here: Top 3 Department Salaries.
A self-join is a type of where a table is joined to itself. To execute a self-join, you must include the table name twice in the clause and assign a different alias to each instance. You can then join the two copies of the table using a clause, and use a clause to specify the relationship between the rows.
One common use case for self-joins is to compare data within a single table. For example, you might use a self-join to compare the salaries of employees within the same department, or to identify pairs of products that are frequently purchased together (like in this real Walmart SQL interview question)[https://datalemur.com/questions/frequently-purchased-pairs].
For a more concrete example, imagine you had website visitor data for Align Technology, exported from the company's Google Analytics account. To help the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to produce all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair.
You could use the following self-join:
This query retrieves the url of each page () along with the url of the page that referred to it (). The self-join is performed using the , which identifies the id of the page that referred the visitor to the current page, and excludes any pages that referred to themselves (i.e., data anomalies since pages shouldn't refer to themself).
Align Technology, Inc. is a medical device company. It is known for creating the Invisalign system, which are a series of clear aligners used as an alternative to traditional braces. Suppose we have customer, product (Invisalign different versions), and customer's Invisalign usage details. Design a database schema to store this information.
You also need to consider a few questions while designing the schema:
For this scenario, please:
After the design, write a PostgreSQL query to find out what was the most popular Invisalign version in August 2022.
customer_id | first_name | last_name |
---|---|---|
1 | John | Doe |
2 | Jane | Smith |
3 | Alex | Johnson |
product_id | product_version |
---|---|
1 | InvisalignV1 |
2 | InvisalignV2 |
3 | InvisalignV3 |
usage_id | customer_id | product_id | purchase_date | start_date | end_date |
---|---|---|---|---|---|
1 | 1 | 2 | 06/12/2022 | 07/12/2022 | 08/28/2022 |
2 | 2 | 1 | 07/14/2022 | 08/01/2022 | 09/15/2022 |
3 | 1 | 3 | 08/10/2022 | 08/21/2022 | 09/30/2022 |
4 | 3 | 1 | 06/15/2022 | 07/15/2022 | 10/15/2022 |
5 | 3 | 2 | 08/16/2022 | 09/08/2022 | 10/20/2022 |
This query counts the usage of each product version during August 2022, and orders them in descending order, returning the most popular version and its count. Please note that this approach considers products used any time during August, not just those that started in August.
In database schema design, a one-to-one relationship between two entities is where each entity is associated with only one instance of the other entity. For example, the relationship between a US citizen and their social-security number (SSN) is one-to-one, because each citizen can only have one SSN, and each SSN belongs to exactly one person.
On the other hand, a one-to-many relationship is where one entity can be associated with multiple instances of the 2nd entity. For example, each person can be associated with multiple email addresses, but each email address only relates back to one person.
As a data analyst at Align Technology, a company well-known for its Invisalign clear aligner treatment, you are asked to compute the average duration of treatment per patient based on the records available in the patient treatment history table.
Let's consider the following table as an example:
treatment_id | patient_id | start_date | end_date |
---|---|---|---|
0001 | 1001 | 01/01/2022 | 04/01/2022 |
0002 | 1002 | 02/15/2022 | 05/30/2022 |
0003 | 1001 | 06/15/2022 | 09/10/2022 |
0004 | 1003 | 01/01/2022 | 06/30/2022 |
0005 | 1003 | 08/01/2022 | 12/31/2022 |
You are expected to find the average duration of treatment in days for each patient.
Here is the SQL query to solve this problem:
This query simply calculates the average duration of treatment per patient, by subtracting the from the for each treatment record per patient. The clause is used to perform this calculation separately for each patient. The function then calculates the average for these individual durations.
Note: PostgreSQL interprets the substraction between two date fields as the number of days between these dates. Hence, the average treatment duration is expressed in days.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating top averages or this Uber User's Third Transaction Question which is similar for analysis based on user history.
Normalization can reduce redundancy and improve performance and flexibility in a database.
By dividing larger tables into smaller, more specific ones linked by foreign keys, it is often possible to improve query speed. Note: it is not always the case that query speed will be improved due to costly nature of joins. Still, we think normalization is a good idea because it can also increase flexibility by making it easier to alter individual tables without affecting others, which can be useful for adapting Align Technology's database to ever-changing business needs.
Given a table recording the treatments provided by Align Technology, with columns indicating the , , , and , can you find the average duration of treatments, day-wise, for each product?
The and columns both use the format , and the duration of a treatment is the difference between these two dates.
Please use the following data as an example:
treatment_id | product_id | patient_id | start_date | end_date |
---|---|---|---|---|
1091 | 102 | 456 | 2021-02-01 | 2021-04-15 |
5382 | 305 | 689 | 2022-01-10 | 2022-02-20 |
2983 | 102 | 305 | 2021-08-05 | 2021-11-02 |
9052 | 698 | 1292 | 2020-04-18 | 2020-06-02 |
3751 | 698 | 974 | 2022-03-03 | 2022-04-02 |
Here is an SQL query that you can use:
In this query, we subtract the from the for each treatment to find its duration, then take the average of these durations grouped by .
product_id | avg_duration |
---|---|
102 | 103 |
305 | 41 |
698 | 38 |
This output table means that the average treatment duration for product 102 is 103 days, for product 305 it's 41 days, and for product 698 it's 38 days.
In the context of Align Technology, a company specialized in creating medical devices to straighten teeth, you'll often receive customer feedback. This feedback sometimes includes names of the cities they are residing in when giving feedback. For this task, you are expected to filter out all customer records that are from cities with names that begin with 'San'.
The company records customer information in the table structured as follows:
customer_id | name | city | country | feedback_submitted |
---|---|---|---|---|
12001 | John Doe | San Francisco | USA | Yes |
12005 | Jane Smith | Chicago | USA | Yes |
12010 | Carlos Mendoza | San Diego | USA | Yes |
12015 | Samantha Johnson | New York | USA | No |
12020 | Fernando Pacheco | San Jose | Costa Rica | Yes |
Write a PostgreSQL query that returns all records of customers from cities with names that begin with 'San'. Your result should return the , , , and .
This query will return all customer records where the city field starts with 'San'. The '%' after 'San' is a wildcard that matches any following characters. Therefore, this query will match cities like 'San Francisco', 'San Diego' or 'San Jose'.
A DBMS (database management system), in order to ensure transactions are relaible and correct, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability
Here is what each of the ACID properties stands for:
Atomicity: ensures that a transaction is either completed in its entirety, or not completed at all. If a transaction fails halfway, the database does a rollback on the commit.
Consistency: ensures that a transaction will only be completed if adheres to the constraints defined in the database of the DB.
Isolation: ensures that concurrent transactions are isolated from each one another, so that the changes made by one transaction cannot be seen by a 2nd transaction until the 1st transaction is done.
**Durability: ** ensures that once a transaction has been committed, the database permanently stores the results in the DB.
As you can see, it's pretty important for Align Technology's data systems to be ACID compliant, else they'll be a big problem for their customers!
The best way to prepare for a Align Technology SQL interview is to practice, practice, practice. In addition to solving the earlier Align Technology SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Netflix, Google, and Amazon.
Each problem on DataLemur has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive coding environment so you can right online code up your query and have it checked.
To prep for the Align Technology SQL interview you can also be a great idea to practice interview questions from other healthcare and pharmaceutical companies like:
But if your SQL query skills are weak, don't worry about jumping right into solving questions – go learn SQL with this interactive SQL tutorial.
This tutorial covers SQL topics like HAVING and filtering strings using LIKE – both of these show up often during Align Technology SQL interviews.
Beyond writing SQL queries, the other types of problems to practice for the Align Technology Data Science Interview are:
To prepare for the Align Technology Data Science interview make sure you have a firm understanding of the company's culture and values – this will be key to acing the behavioral interview. For the technical Data Science interviews, prepare by reading Ace the Data Science Interview. The book's got: