Zomato Business Analyst Interview Questions
Zomato Business Analyst Interview Questions
Name of company – Zomato
Designation – Business Analyst
Salary – 15 to 20 LPA (including stocks)
Number of rounds – 4
Zomato Business Analyst Interview Questions
There were in total 4 rounds in Zomato for the post of Business Analyst post. The focus was mostly on SQL and case studies.
In order to apply for Zomato, you need to have a referral and then you have to upload a minute of video on any topic of your choice. It could be something like ‘ Why do you like Sachin Tendulkar?’
‘Why Black is my favorite color?’, ‘Which is your favorite team?’
You will get a call if your profile is strong, but once you get a call, you need to work on your SQL logic and case studies.
Zomato Business Analyst Interview Questions
There were in total 4 rounds
Round 1 – SQL
Round 2 – The programming language of your choice, mostly Python and SQL
Round 3 – Case Study and SQL
Round 4 – Hiring Manager Round
Below are some questions that were asked in these technical round
SQL Questions
1. What is the use of offset command?
The OFFSET command can contain scalar values or subqueries, basically the OFFSET argument is used to identify the starting point to return rows from a result set. It excludes the first set of records
– Can only be used with ORDER BY clause
-Must be greater than or equal to zero, cannot be (-ve) else returns error
2. What is the order of execution of SQL query?
Order of execution for an SQL query
1) FROM, including JOINs
2) WHERE
3) GROUP BY
4) HAVING
5) WINDOW Functions
6) SELECT
7) DISTINCT
8) UNION
9) ORDER BY
10) LIMIT AND OFFSET
3. Can we use HAVING without any aggregate function?
No, it’s not necessary for having to use aggregate functions and even without group by having can exist.
Eg: This query works well in PostgreSql
select 1 having 1 = 1;
4. Write a query to get all the student with name length 10, starting with K and ending with z
select name
from student
where length(name)=10 and lower(name) like ‘k%z’
5. We have the following values
10000
10000
20000
30000
30000
30000
What would be the result of row number, rank, and dense rank ?
A) Row_Number() assigns a sequential integer to each row within the partition of a result set.
Ans:
1000 1
1000 2
2000 3
3000 4
3000 5
3000 6
B) Rank() assigns a rank to each row within a partition of a result set.Rows in each partition receive the same ranks if they have the same values. But the ranks will be skipped here.
Ans:
1000 1
1000 1
2000 3
3000 4
3000 4
3000 4
C) Dense_Rank() differs from Rank() as it assigns consecutive ranks and ranks won’t be skipped.
Ans:
1000 1
1000 1
2000 2
3000 3
3000 3
3000 3
Statistics
1. What percentage of value lies between the Mean and one Standard deviation(both positive and negative)
~68%
2. Give the relation of Mean, median, and mode in a positively skewed distribution
Mean > Median > Mode
3. Negatively skewed distribution?
Mode > Median > Mean
4. What is the sum of squared deviation?
The Sum of Squared deviation is a measure of the total variability of a set of scores around a specific number
Case Study
If you have to recommend a product to a customer who has already filled his cart, then what data will you look for? Basically, how will you recommend a product to an e-commerce customer?
There could be multiple things that we can look for
a. If the customer has brought product A, then we should look in the data to find out the product that compliments that product. We can do this by looking into the purchase history of other customers who have brought the product A
b. We can get the cart information of the customer and look for those items which he has removed from the cart. At the check-out, you can again ask him if he wants to buy it
c. We can also look for a better product option for the customer. Suppose the customer is willing to pay $3 for soap, then we can show them ads or recommendations of a $5 soap with a better review
d. We can also look for the previous cart history of the customer to see if he is missing something which he used to buy regularly
Python
1.Why do we use the insert function in pandas ?
As we know whenever we want to add a column to the data frame , it is added to the last by default. But Pandas provides us the option that we can add a column at any position by using Insert Function.
We need to specify the position wherever we want to insert it. Let’s suppose we want to insert the column at 2nd Position.
new_column = np.random.randn(10)
#insert the new column at position 2
df.insert(2, ‘new_column’, new_column)
print(df)
2.How will you get the number of rows and columns of a Dataframe in pandas?
We can use the shape() method to finding the number of rows and columns in a data frame.
import pandas as pd
import numpy as np
raw_data = {‘name’: [‘Willard Morris’, ‘Al Jennings’, ‘Omar Mullins’, ‘Spencer McDaniel’],
‘age’: [20, 19, 22, 21],
‘favorite_color’: [‘blue’, ‘red’, ‘yellow’, “green”],
‘grade’: [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, columns = [‘name’, ‘age’, ‘favorite_color’, ‘grade’])
df
# get the row and column count of the df
df.shape()
The Data Monk Interview Books – Don’t Miss
Now we are also available on our website where you can directly download the PDF of the topic you are interested in. On Amazon, each book costs ~299, on our website we have put it at a 60-80% discount. There are ~4000 solved interview questions prepared for you.
10 e-book bundle with 1400 interview questions spread across SQL, Python, Statistics, Case Studies, and Machine Learning Algorithms – Ideal for 0-3 years experienced candidates
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12 E-books for 12 Machine Learning algorithms with 1000+ interview questions – For those candidates who want to include any Machine Learning Algorithm in their resume and to learn/revise the important concepts. These 12 e-books are a part of the 23 e-book package
Individual 50+ e-books on separate topics
Important Resources to crack interviews (Mostly Free)
There are a few things that might be very useful for your preparation
The Data Monk Youtube channel – Here you will get only those videos that are asked in interviews with Data Analysts, Data Scientists, Machine Learning Engineers, Business Intelligence Engineers, Analytics managers, etc.
Go through the watchlist which makes you uncomfortable:-
All the list of 200 videos
Complete Python Playlist for Data Science
Company-wise Data Science Interview Questions – Must Watch
All important Machine Learning Algorithm with code in Python
Complete Python Numpy Playlist
Complete Python Pandas Playlist
SQL Complete Playlist
Case Study and Guesstimates Complete Playlist
Complete Playlist of Statistics
Keep Learning !!
Thanks,