10 Wolters Kluwer SQL Interview Questions (Updated 2024)
At Wolters Kluwer, SQL is used across the company for extracting and analyzing healthcare and legal data sets, and managing the underlying data behind their Legal Research platform. Because of this, Wolters Kluwer frequently asks SQL query questions during interviews for Data Science and Data Engineering positions.
To help you prepare for the Wolters Kluwer SQL interview, we've collected 10 Wolters Kluwer SQL interview questions – how many can you solve?
10 Wolters Kluwer SQL Interview Questions
SQL Question 1: Identify top invoicing customers
You are provided with two tables: and . The table records all issued invoices for customers, with a field for the customer_id, the invoice amount, and the date of issue. The table catalogues all customers, their customer_id, and their relevant profile information.
Your task is to identify the top 5 customers who have the highest total invoiced amount in the last 365 days.
Example Input:
| invoice_id | customer_id | issue_date | amount |
|---|---|---|---|
| 1382 | 1 | 2019-06-08 | 1200.00 |
| 5002 | 2 | 2019-11-26 | 3000.00 |
| 9303 | 1 | 2020-02-18 | 4500.00 |
| 6475 | 3 | 2020-05-26 | 800.00 |
| 2781 | 5 | 2020-07-15 | 6000.00 |
Example Input:
| customer_id | first_name | last_name | join_date |
|---|---|---|---|
| 1 | John | Doe | 2019-01-01 |
| 2 | Jane | Smith | 2019-03-15 |
| 3 | Bob | Brown | 2019-05-18 |
| 4 | Alice | Johnson | 2019-07-22 |
| 5 | Charlie | Black | 2019-09-27 |
Answer:
This query first joins the and tables on the field, ensuring that we have the relevant customer information available. It then filters the table for only the entries from the last 365 days. The query then aggregates the invoicing data by customer, calculating the total invoiced amount. Finally, it orders the resulting dataset by in a descending order and returns only the top 5 entries.
To practice a super-customer analysis question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:
SQL Question 2: Calculate Monthly Average Rating Per Product
For Wolters Kluwer, you manage a product review platform. You are required to analyze product performance monthly based on the average rating they receive each month. Write a SQL query to calculate an average rating of each product for each month.
Sample Table:
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 01/15/2022 | 50001 | 4 |
| 7802 | 265 | 01/29/2022 | 69852 | 4 |
| 5293 | 362 | 02/18/2022 | 50001 | 3 |
| 6352 | 192 | 03/26/2022 | 69852 | 3 |
| 4517 | 981 | 02/05/2022 | 69852 | 2 |
| 5326 | 555 | 03/30/2022 | 50001 | 4 |
| 7819 | 789 | 02/06/2022 | 50001 | 5 |
Expected Output:
| mth | product | avg_stars |
|---|---|---|
| 1 | 50001 | 4.00 |
| 1 | 69852 | 4.00 |
| 2 | 50001 | 4.00 |
| 2 | 69852 | 2.00 |
| 3 | 50001 | 4.00 |
| 3 | 69852 | 3.00 |
Answer:
This query will extract the month from the submit_date and group by it with product_id to calculate the average ratings each month for each product. The is used to format the average stars output into having two decimal places.
To practice another window function question on DataLemur's free online SQL coding environment, solve this Google SQL Interview Question:
SQL Question 3: What's a primary key?
The primary key of a table is a column or set of columns that serves as a unique identifier for each row. It ensures that all rows are distinct and does not allow null values.
For example, say you had stored some Facebook ad campaign data that Wolters Kluwer ran:
The column uniquely identifies each row in the table, and the PRIMARY KEY constraint ensures that no two rows have the same . This helps to maintain the integrity of the data in the table by preventing duplicate rows.
The primary key is also an important part of the table because it allows you to easily identify and reference specific campaigns in your Facebook Ad data. You can use it to join to other tables in the database, such as a table containing data on the results of the campaigns.
SQL Question 4: Filter Customers Based on Subscription and Location Details
Wolters Kluwer has a global customer base for its various information services. The sales team wants to focus on a specific customer segment for a new marketing campaign. They aim at targeting individual customers in Europe who are subscribed to any health service and are not subscribed to any tax service.
You need to filter the customer records database to meet these conditions:
- equals to 'Europe'
- is true
- is false
Given the customer records in the table, write a query that provides the following output: the customer's name, country, subscription to health service, and subscription to tax service.
Example Input:
| customer_id | customer_name | country | geography | subscription_health | subscription_tax |
|---|---|---|---|---|---|
| C101 | John Doe | UK | Europe | True | False |
| C102 | Lisa Smith | US | North America | True | False |
| C103 | Boris Chernov | Russia | Europe | True | True |
| C104 | Hang Lee | China | Asia | True | False |
| C105 | Claire Brown | France | Europe | True | False |
Example Output:
| customer_name | country | subscription_health | subscription_tax |
|---|---|---|---|
| John Doe | UK | True | False |
| Claire Brown | France | True | False |
Answer:
This query will scan the table and filter the rows to return only the records where the customers are based in Europe, subscribed to a health service, and are not subscribed to a tax service.
SQL Question 5: Why is normalizing a database helpful?
There are several advantages to normalizing a database, including less redundancy, more flexibility, and better performance.
-
Less Redundancy: Normalization reduces redundancy by breaking down a larger, more general table into smaller, more specific tables. This reduces the amount of data that needs to be accessed for queries.
-
More Flexibility: Normalization makes it easier to modify the structure of the database, as there is less redundancy, so it allows you to make changes to one table without affecting others. This makes it easier to adapt the database to changing business needs (a very real reality at Wolters Kluwer!)
-
Better Performance: Normalization can improve the performance of the database by reducing the amount of data that needs to be stored and accessed in a single table. This can result in faster query times and better overall performance.
SQL Question 6: Analyze Click-Through-Rate for Digital Products
As part of Wolters Kluwer's data science team, you are asked to analyze the click-through conversion rates for their digital legal products. Specifically, the team is interested in understanding the ratio of users who viewed a product to those who added the product to their cart in a week. Assume all views and additions occur within the same week.
Example Input:
| view_id | user_id | product_id | view_date |
|---|---|---|---|
| 101 | 123 | 5001 | 2022-07-01 |
| 102 | 265 | 5001 | 2022-07-02 |
| 103 | 123 | 6001 | 2022-07-03 |
| 104 | 362 | 5001 | 2022-07-04 |
Example Input:
| add_id | user_id | product_id | add_date |
|---|---|---|---|
| 201 | 123 | 5001 | 2022-07-01 |
| 202 | 362 | 5001 | 2022-07-02 |
Answer:
In the above query, we first count the distinct number of views and additions for each product. We then calculate the ratio of additions to views, and then multiply by 100 to present this as a percentage. To avoid dividing by zero, we use the function. We also ensure that an addition has happened on the same day or after the view date.
To practice a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's interactive SQL code editor:
SQL Question 7: What are the similarities and differences between a clustered index and non-clustered index?
Clustered indexes have a special characteristic in that the order of the rows in the database corresponds to the order of the rows in the index. This is why a table can only have one clustered index, but it can have multiple non-clustered indexes.
The main difference between clustered and non-clustered indexes is that the database tries to maintain the order of the data in the database to match the order of the corresponding keys in the clustered index. This can improve query performance as it provides a linear-access path to the data stored in the database.
SQL Question 8: Average Revenue per Client
Wolters Kluwer is a global provider of professional information, software solutions, and services for clinicians, accountants, lawyers, and tax, finance, audit, risk, and regulatory sectors. In this scenario, let's consider a simplified version of their business where they sell different professional software solutions to multiple clients. The goal of this question is to find the average revenue per client for each product sold by Wolters Kluwer.
Here's your dataset, named :
Example Input:
| sale_id | client_id | sale_date | product_id | revenue |
|---|---|---|---|---|
| 3452 | 754 | 01/10/2022 00:00:00 | 50001 | 5000 |
| 6894 | 108 | 01/15/2022 00:00:00 | 50001 | 2600 |
| 2803 | 754 | 02/25/2022 00:00:00 | 69852 | 7000 |
| 1375 | 108 | 02/10/2022 00:00:00 | 69852 | 4000 |
| 4876 | 456 | 02/15/2022 00:00:00 | 50001 | 4500 |
Let's write an SQL query to solve this:
Answer:
This SQL query groups the sales data by product id and month, then, for each group, it calculates the average revenue by using the AVG aggregate function. The ORDER BY statement helps in sorting the output based on the product_id and month in ascending order.
Example Output:
| product_id | month | avg_revenue |
|---|---|---|
| 50001 | 1 | 3800 |
| 50001 | 2 | 4500 |
| 69852 | 2 | 5500 |
SQL Question 9: Finding Customers in a Specific Geographic Region
Candidates are expected to write a SQL query to filter down the table in such a way that it only displays the customer records who are located in a region (given its prefix). For this exercise, let's assume that you are asked to find all customers who live in any area that has the zip code prefix "10", for instance, 10001, 10002, 10003, etc.
Example Input:
| cust_id | first_name | last_name | zip_code | |
|---|---|---|---|---|
| 1001 | John | Doe | johndoe@example.com | 10001 |
| 1002 | Jane | Smith | janesmith@example.com | 20002 |
| 1003 | Sam | Klein | samklein@example.com | 10003 |
| 1004 | Lisa | Taylor | lisataylor@example.com | 30004 |
| 1005 | Harry | Potter | harrypotter@example.com | 10005 |
Your task is to write a PostgreSQL query to find all customers who live in the region with the "100" prefix in their zip code.
Answer:
The above SQL statement will display all customers in the database that are located in a region that starts with the zip code prefix "100". The keyword is used in the clause to search for a specified wildcard pattern. In this problem, is the wildcard string pattern where "100" is the prefix to match and "%" represents any sequence of zero or more characters.
Example Output:
| cust_id | first_name | last_name | zip_code | |
|---|---|---|---|---|
| 1001 | John | Doe | johndoe@example.com | 10001 |
| 1003 | Sam | Klein | samklein@example.com | 10003 |
| 1005 | Harry | Potter | harrypotter@example.com | 10005 |
The returned table includes all customers who live in a region with the zip code prefix "100".
SQL Question 10: Database transactions are supposed to be atomic, consistent, isolated, & durable. What does each term mean?
ACID refers to the four key properties that are essential to the reliable and correct execution of database transactions. These properties are:
Atomicity: ensures that a transaction is treated as a single operation, and either all of the changes are made or none of them are! Basically, the database version of a "-FULL SEND-"
Consistency: ensures that the data is in a consistent state before and after a transaction is completed. For example, if wiring money to a friendly Nigerian prince whose fallen on hard times, consistency ensures that the total value of funds lost in my account is the same amount that's gained in the prince's account!
Isolation: ensures that the intermediate state of a transaction is invisible to other transactions. Back to the wiring-the-prince-some-money example, isolation ensures that another transaction sees the transferred funds in my account OR the princes, but not in both accounts at the same time
Durability: ensures that once a transaction has been completed successfully, the changes made by the transaction are permanent and cannot be undone, even in the event of a system failure. Basically, no taksies backsies (even if your system has a meltdown!).
Wolters Kluwer SQL Interview Tips
The best way to prepare for a Wolters Kluwer SQL interview is to practice, practice, practice.
In addition to solving the earlier Wolters Kluwer SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Google, Uber, and Microsoft.
Each problem on DataLemur has multiple hints, full answers and crucially, there's an interactive SQL code editor so you can right in the browser run your query and have it checked.
To prep for the Wolters Kluwer SQL interview it is also helpful to solve interview questions from other tech companies like:
But if your SQL query skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this SQL tutorial for Data Analytics.
This tutorial covers things like UNION vs. joins and filtering data with WHERE – both of these come up routinely in SQL job interviews at Wolters Kluwer.
Wolters Kluwer Data Science Interview Tips
What Do Wolters Kluwer Data Science Interviews Cover?
In addition to SQL query questions, the other types of problems to prepare for the Wolters Kluwer Data Science Interview are:
- Probability & Statistics Questions
- Python or R Programming Questions
- Product Data Science Interview Questions
- ML Interview Questions
- Behavioral Interview Questions
How To Prepare for Wolters Kluwer Data Science Interviews?
The best way to prepare for Wolters Kluwer Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from tech companies like Netflix, Google, & Airbnb
- A Crash Course on SQL, Product-Sense & ML
- Amazing Reviews (900+ reviews, 4.5-star rating)