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Business Analytics Interview Questions | Day 3

Welcome to the 2nd Day of Business Analytics Interview Questions Quiz.
You can go through the question and answer for
Day 1 Here
Day 2 Here
The best answer to the quiz was provided by Raahul for both the days
Business Analytics Interview Questions

In this series, all you need to do is to go through the questions and try to attempt it with whatever knowledge you have.

Before or after you attempt the questions, do go through the complete road map about what you need to study to crack an analytics role. We have covered from 3rd year college student to 8 years of analytics or non-analytic experience. Make sure you understand where to emphasize more(after all by the end of the day you want to crack an interview)

Complete Roadmap for cracking an Analytics Role in the next 30 days

Now, coming back to our questions. Remember, these are the most asked questions in any interview, if you are shy to answer the questions in the comment section, then do make sure to Google the answer and jot it down in your notebook.

Business Analytics Interview Questions

SQL

  1. How do you extract a value from column that has a data type of JSON?
  2. How to convert date from yyyy-mm-dd to dd-mm-yyyy
  3. Difference between internal and external table in Hive?

Python

  1. Print if a number/string is palindrome?
  2. Can we access values in a dictionary using index number ?

Case Study

  1. For a particular e-commerce business the number of supplier and user both have grown by 5% week over week, but the revenue has declined by 5 %, what could be the reason?

Machine Learning

  1. Explain multicollinearity ? And why should we avoid it?
  2. Explain null hypothesis?

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. At 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

23 E-book with ~2000 interview questions spread across AWS, SQL, Python, 10+ ML algorithms, MS Excel, and Case Studies – Complete Package for someone between 0 to 8 years of experience (The above 10 e-book bundle has a completely different set of e-books)

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

Thank you

About TheDataMonkGrand Master

I am the Co-Founder of The Data Monk. I have a total of 6+ years of analytics experience 3+ years at Mu Sigma 2 years at OYO 1 year and counting at The Data Monk I am an active trader and a logically sarcastic idiot :)

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Comments ( 2 )

  1. SQL
    1. I have not worked with JSON yet, but searching tells me JSON_VALUE() can be used to get values from JSON string.
    2. SELECT CONVERT(VARCHAR(10), GETDATE(), 105) AS [DD-MM-YYYY]

    Python
    1. checking if a string is a palindrome
    a = ‘hannah’
    print(a==””.join(reversed(a))) – True
    2. Yes
    d = {}
    d[‘a’] = 5
    d[‘b’] = 7
    d[‘c’] = 9
    values = list(d.values())
    print(values[2]) – 9

    Case Study
    Problem – number of supplier and user both have grown by 5% week over week, but the revenue has declined by 5 %, what could be the reason
    Question – what is the horizon of the decline? Have we made any updates to the app in recent times (related to UI etc.)
    1. Low conversion rate (people are not adding items to cart, possibly due to UI related or even pricing issues)
    2. High drop-off rates (people don’t buy after adding to cart)
    3. Bugs/Glitches in the app due to higher onboarding (simply looking out for technical issues, if any)
    4. Users find competition options better. Stickiness is low (we have one-time users, who do not buy again for very long).

    Machine Learning
    1. Multi-collinearity is when there are independent variables highly correlated to each other, which inflates the coefficients during linear regression. We should avoid it as it affects the interpretability and accuracy of the model. It can be looked out for by creating a correlation matrix and VIF values.
    2. Please explain null hypothesis to me in easier terms 🙂

    • Nice answer Raahul, one good point in case study is ‘Demand-Supply Mismatch’, there could be a possibility that the demand was more in the Northern part of India but supply was in Souther part, resulting in decline of revenue 🙂

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