Open Financial Technologies Private Limited Data Analyst Interview Questions and Answers

It was a basic Aptitude test, Needed to learn Probability, Permutation , Cobination and SQL.
Total Duration 1 Hour.

Q1. Types of Window Function
Ans. 
Window functions are used in SQL to perform calculations across a set of table rows related to the current row.
• Types include ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE(), LAG(), LEAD(), FIRST_VALUE(), LAST_VALUE(), etc.

• They allow for calculations to be performed on a specific subset of rows within a query result set.

• Window functions are commonly used for running totals, moving averages, and ranking data.
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Q2. Difference between Joins with examples
Ans. 
Joins are used to combine rows from two or more tables based on a related column between them.
• Inner Join: Returns rows when there is a match in both tables.

• Left Join: Returns all rows from the left table and the matched rows from the right table.

• Right Join: Returns all rows from the right table and the matched rows from the left table.

• Full Outer Join: Returns rows when there is a match in one of the tables.

• Cross Join:
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Hackerrank test mostly on python and sql

Q1. SQL based questions
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Q2. Python based questions
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Mostly medium leetcode

Mostly medium level DSA

Q1. AWS, GCP , Kubernetes, Docker
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Q1. Security standards, cloud security
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Q1. What techonologies do you know?
Ans. 
I am proficient in SQL, Python, R, Tableau, and Excel for data analysis and visualization.
• SQL

• Python

• R

• Tableau

• Excel
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SQL Coding Tests. You get 3 tables and they ask you to find customer with certain conditions. Not hard

Q1. Detailed discussion on past experience and projects.
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Q1. 2 Hackerrank SQL Questions
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Q2. 1 Hackerrank Python Question
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Technical SQL Coding Round of 1 hour

Began with 2 easy generic question -
1. No. of record on different types of joins.
2. Employees who have higher salaries than their managers,

Then moved to medium questions -
1. Implement Rolling sum with & without window functions.
2. Other questions were on CTEs, Joins & other complex queries.

Bar Raiser Round of 1 hour involving -

1. Case study: How can we leverage product knowledge & analytics to increase Amazon Prime Revenue from 10% to 12%?

2. Metrics awareness: Common metrics discussion like DAU, PDAU, MAU, Retention, Churn, etc.

3. Resume based work exp discussion

Q1. Quick culture fitment round with HR discussing about past work experience, my expectations & why I want to join Jupiter.
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