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100 Questions to Crack Business Analyst Interview

What is the difference between data science and business analysis?

What is the profile for you which you are appearing for the interview next week ? 

Data science is dealing with the data, to get insights from the data and change the way your client has been using this data, Business analysis is about understanding the data and the business. As a business analyst you are supposed to take a more holistic view of the problem to solve the bigger picture.

Both data science and business analytics job profile might look the same, but it’s actually a lot different.

100 Questions To Crack Business Interview contains exact 100 question which you should try to master before going through any Business Analyst, Big Data, Data Science interview. This book contains question in random order, so you have to cover the complete 30 page without chucking any page. This book will be a great help to prepare for any related topic interview.

Know the difference between the two – Here


The Data Monk

100 Questions to crack Data Science Interview

Stuck in IT job ?

Looking to switch to Data Science ?

You are planning to appear for Data Science job and you don’t have any idea about the question which are going to be asked in the interview?

Here at The Data Monk we will help you with all sort of questions which might appear in your interview. TDM is a group of 15+ domain experts in Data science, business analysis, HRs and Big Data.

There are candidates who are asked basic questions like difference between data, information, knowledge and wisdom. And believe me, people fall for these questions.

Link to the book is Here 

This book targets on questions which helps one to crack a data science interview. The book contains important and most asked questions in data science interviews. There are case studies, data science and statistics questions which are a must before any data science interview.

Time to complete the book – 6 hours

This is a must before you step into a data science interview.

Thank you,

The Data Monk