# 9 BCG SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

At BCG, particularly within BCG X which focuses on tech & AI, Data Analysts and Data Scientists uses SQL to analyze large datasets, such as customer sentiment and market trends, to gain strategic insights. They also manage databases for different consulting clients by integrating data from various sources and ensuring data quality, which is why SQL interview questions are part of BCG’s data job interviews.

So, to help you practice, here's 9 Boston Consulting Group SQL interview questions – how many can you solve?

## 9 Boston Consulting Group SQL Interview Questions

### SQL Question 1: Find VIP Customers at BCG

Boston Consulting Group (BCG) is a global management consulting firm. For this question, we are going to find the VIP customers who have the highest total charges. A VIP customer is defined as the one who has total charges more than USD 10,000.

Assume that we have two tables, and , with the following schema:

##### Example Input:
customer_idfirst_namelast_nameemail
1JohnDoejohn.doe@gmail.com
2JaneSmithjane.smith@gmail.com
3RobertBrownrobert.brown@gmail.com
4MichealJohnsonmicheal.johnson@gmail.com
##### Example Input
charge_idcustomer_idcharge_amountcharge_date
1150002022-12-01
2160002022-12-02
3230002022-12-01
4220002022-12-03
5340002022-12-04
64120002022-12-05

#### Answer:

The above SQL query will join the and tables on , group the result by , , and fields, and filter the grouped result where total charge amount per customer is more than USD 10,000. The resulting table would contain the list of VIP customers who have the highest total charges.

To practice a related customer analytics question on DataLemur's free interactive SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:

### SQL Question 2: Well Paid Employees

Suppose you had a table of BCG employee salary data. Write a SQL query to find all employees who earn more than their direct manager.

#### BCG Example Input:

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns \$8,000, surpassing her manager, William Davis who earns 7,800.

Try this question directly within the browser on DataLemur:

#### Answer:

First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

If the code above is tough, you can find a step-by-step solution here: Employee Salaries Higher Than Their Manager.

### SQL Question 3: Why would you use the SQL constraint?

The 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. The CHECK constraint is often used with other constraints, such as NOT NULL or UNIQUE, to ensure that data meets certain conditions. You may want to use a CHECK constraint in your database if you want to maintain the quality and reliability of your data by ensuring that it meets specific criteria.

For example, you might use a CHECK constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.

### SQL Question 4: Average Ratings per Product per Month

The Boston Consulting Group (BCG) maintains a database of customer product reviews. Each product review record contains a unique review id, user id, date of submission, product id, and star rating (1-5). To analyze customer satisfaction for its different products over time, BCG needs you to write a SQL query that calculates the average star ratings for each product on a monthly basis.

In other words, for each product, calculate its average star rating for each month in the database.

##### Example Input:
review_iduser_idsubmit_dateproduct_idstars
6171123'2022-06-08'500014
7802265'2022-06-10'698524
5293362'2022-06-18'500013
6352192'2022-07-26'698523
4517981'2022-07-05'698522
##### Example Output:
monthproduct_idavg_stars
6500013.50
6698524.00
7698522.50

#### Answer:

In this PostgreSQL query, I am extracting the month from the column and grouping by both the and to get the average star ratings () for each product per month. I am then ordering the results by and to display the ratings in a clear manner.

To practice another window function question on DataLemur's free online SQL code editor, try this Amazon BI Engineer interview question:

### SQL Question 5: What is the difference between a primary key and a foreign key?

A primary key is a column (or set of columns) in a table that uniquely identifies each row in the table. It cannot contain null values and must be unique across all rows in the table.

A foreign key is a column (or set of columns) in a table that references the primary key of another table. It is used to establish a relationship between the two tables. A foreign key can contain null values, and multiple rows in the referencing table can reference the same row in the referenced table.

For example, consider a database with two tables: and . The BCG customers table might have a primary key column called , while the BCG orders table might have a foreign key column called that references the column in the table. This establishes a relationship between the two tables, such that each row in the orders table corresponds to a specific BCG customer.

### SQL Question 6: Average Consultation Duration at BCG

Boston Consulting Group or BCG, a management consulting firm, keeps track of all its consultation sessions with clients. In an effort to assess efficiency, you're asked to calculate the average duration of consultation sessions in minutes for each consultant at BCG.

The database has a table , with the session_id, consultant_id, start_time, and end_time of all sessions.

##### Example Input:
session_idconsultant_idstart_timeend_time
1111202023-06-08 10:30:002023-06-08 12:30:00
2222202023-07-15 09:00:002023-07-15 11:15:00
3333212023-08-18 13:45:002023-08-18 16:00:00
4444222023-09-26 10:30:002023-09-26 12:00:00
5555222023-10-05 14:00:002023-10-05 15:45:00

You will need to calculate the difference in start_time and end_time to get the duration of each session, then find the average duration for each consultant.

#### Answer:

Here's the SQL query to find out:

This query first calculates the duration of each session in minutes using EXTRACT(EPOCH FROM (end_time - start_time))/60. It then calculates the average duration for each consultant using the AVG function. The result is grouped by consultant_id to get separate averages for each consultant.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating duration or this Stripe Repeated Payments Question which is similar for < handling time-bound data.

### SQL Question 7: What does the SQL command do?

When using , only rows that are identical in both sets will be returned.

For a concrete example, say you were a Data Analyst supporting the Sales Analytics team at BCG, and data on potential sales leads lived in both Salesforce and Hubspot CRMs. To write a query to analyze leads created before 2023 started, that show up in BOTH CRMs, you would use the command:

### SQL Question 8: Analyzing Click-Through Rates

BCG (Boston Consulting Group) is conducting an internal study on the effectiveness of its in-house digital marketing campaigns. You are provided with two tables: and .

The table contains information about the different marketing campaigns such as the campaign_id, campaign name, and the date when the campaign started.

The table contains information about individuals who have clicked on the ads such as click_id, the user_id, the campaign_id that the ad was part of and the date and time when the click happened.

Your task is as follows: Determine the click-through rate for each campaign. The click-through rate is defined as the total number of clicks per campaign over the total number of campaigns.

##### Sample Input:
campaign_idcampaign_namestart_date
1Campaign A2021-12-01
2Campaign B2021-12-03
3Campaign C2021-12-05
##### Sample Input:
click_iduser_idcampaign_idclick_date
1100112021-12-02 08:00:00
2100212021-12-02 09:00:00
3100322021-12-03 08:00:00
4100422021-12-03 09:00:00
5100532021-12-06 08:00:00

#### Answer:

The above query first joins the and tables on . It then groups the result by and for each , it counts the number of click_ids i.e., the number of clicks that happened for that campaign. This gives us the total number of clicks for each campaign. To get the click through rate, we need to divide this count with the total number of campaigns. This will give us the click-through rate (CTR) for each campaign.

It's important to note that this query only provides the number of clicks for each campaign. If you also need to include the total number of campaigns to calculate the exact CTR, you would need an additional query or subquery to provide this denominator value. For simplicity in this question, we've not included those additional steps.

To practice another question about calculating rates, solve this TikTok SQL question within DataLemur's interactive SQL code editor:

### SQL Question 9: Average Consulting Project Rating by Year and Client

BCG manages various consulting projects. They are keen to understand how their clients have been rating the services provided over the years so they can pinpoint their strengths and weaknesses. Write a SQL query to find out the average rating BCG received for each client across different years. Assume the ratings are on a scale of 1 to 5 (5 being the highest).

##### Example Input:
project_idclient_idrating_daterating
4598ABC02/15/20195
7583XYZ06/04/20194
4665XYZ08/10/20203
4875ABC07/22/20204
6674DEF05/15/20202
##### Example Output:
yearclientavg_rating
2019ABC5.00
2019XYZ4.00
2020ABC4.00
2020XYZ3.00
2020DEF2.00

#### Answer:

In this query, we first extract the year from the rating_date column using the EXTRACT function. This gives us the year on which rating was made. We then group by the extracted year and client_id to get the average rating for each client across different years. The AVG function is used to calculate the average rating. The ORDER BY clause is used to order the result set by the year and client.

### BCG SQL Interview Tips

The key to acing a BCG SQL interview is to practice, practice, and then practice some more! Besides solving the above BCG SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Google, Facebook, Microsoft and Amazon.

Each SQL question has hints to guide you, step-by-step solutions and best of all, there's an interactive coding environment so you can instantly run your SQL query and have it graded.

Discover how BCG is harnessing the power of Artificial Intelligence to drive business growth and innovation!

To prep for the BCG SQL interview it is also wise to practice SQL questions from other management consulting companies like:

In case your SQL foundations are weak, don't worry about diving straight into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.

This tutorial covers things like how window functions work and manipulating date/time data – both of these pop up frequently in SQL interviews at BCG.

### Boston Consulting Group Data Science Interview Tips

#### What Do BCG Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories to practice for the BCG Data Science Interview include:

• Statistics and Probability Questions
• Python or R Programming Questions
• Open-Ended Data Case Studies
• ML Interview Questions
• Behavioral Interview Questions centered on BCG cultural values

#### How To Prepare for BCG Data Science Interviews?

To prepare for BCG Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from Google, Microsoft & tech startups
• a refresher covering SQL, Product-Sense & ML
• over 1000+ 5-star reviews on Amazon

Also focus on the behavioral interview – prepare for it with this guide on acing behavioral interviews.