Facebook Data Analyst Interview Questions and Answers

Basic Apititude Questions

Q1. Difference between WHERE and HAVING??
Ans. 
WHERE is used to filter rows before grouping, HAVING is used to filter groups after grouping.
• WHERE is used with SELECT statement to filter rows based on a condition

• HAVING is used with GROUP BY statement to filter groups based on a condition

• WHERE is applied before data is grouped, HAVING is applied after data is grouped

• Example: SELECT * FROM table WHERE column = 'value'

• Example: SELECT column, COUNT(*) FROM table GROUP B
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Q2. Where- Row Level Filters Having-Aggregate Filters
Ans. 
Row level filters are applied before aggregations, while aggregate filters are applied after aggregations.
• Row level filters are used to filter individual rows of data before any aggregations are performed.

• Aggregate filters are used to filter the aggregated results after the data has been grouped and summarized.

• Row level filters are typically applied using WHERE clause in SQL, while aggregate filters are applied using H...read more
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Q1. Why do you wanna join Uber?
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Q2. Best Company Ever
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GD COMMON TOPIC WAS DISCUSSED

Q1. TELL ABOUT YOURSELF , SKILLSETS YOU BRING TO THE TABLE
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Q1. EXPECTED INCOME , RELOCATION PREFERENCE
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Number sires, clock, logic, arithmetic, geometry

Code test basic, ans the basic knowledge, write code

Q1. What is python?
Ans. 
Python is a high-level programming language known for its simplicity and readability.
• Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.

• It emphasizes code readability and uses indentation to define code blocks.

• Python has a large standard library and a vibrant community of developers.

• Example: print('Hello, World!')

• Example: import pandas as pd
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Q2. What is python used for?
Ans. 
Python is a versatile programming language used for data analysis, web development, artificial intelligence, automation, and more.
• Data analysis and visualization

• Web development (Django, Flask)

• Artificial intelligence and machine learning (TensorFlow, PyTorch)

• Automation and scripting

• Scientific computing (NumPy, SciPy)
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Q3. What type of language is python?
Ans. 
Python is a high-level programming language known for its simplicity and readability.
• Python is an interpreted language, meaning it does not need to be compiled before running.

• It supports multiple programming paradigms, including object-oriented, imperative, and functional programming.

• Python has a large standard library and a thriving community, making it versatile and widely used.

• Example: Python is used for web develop...read more
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Q4. What is oops in python?
Ans. 
Object-oriented programming (OOP) is a programming paradigm based on the concept of 'objects', which can contain data and code.
• OOP allows for the organization of code into reusable components called classes.

• Classes can have attributes (variables) and methods (functions) associated with them.

• In Python, everything is an object, and classes can be defined using the 'class' keyword.

• Encapsulation, inheritance, and polymorph
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Q5. What is array in python?
Ans. 
An array in Python is a data structure that stores a collection of elements of the same type.
• Arrays can store elements such as integers, floats, or strings.

• Arrays are indexed starting from 0, with elements accessed using their index.

• Example: arr = ['apple', 'banana', 'cherry']
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Q1. What’s your previous experience
Ans. 
I have 3 years of experience as a data analyst in the finance industry.
• Worked with large datasets to extract meaningful insights

• Performed data cleaning, transformation, and visualization

• Created and maintained dashboards and reports for stakeholders

• Conducted statistical analysis and built predictive models

• Collaborated with cross-functional teams to identify business opportunities
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Q2. What’s your skills for the current role
Ans. 
I have strong skills in data analysis, including proficiency in statistical analysis, data visualization, and programming languages such as Python and SQL.
• Proficient in statistical analysis techniques

• Skilled in data visualization using tools like Tableau

• Strong programming skills in Python and SQL

• Experience with data cleaning and preprocessing

• Ability to interpret and communicate insights from data

• Familiarity with machin...read more
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Q1. How well do you know excel?
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Q1. Resume based questions
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Q2. General discussion about work
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Q1. When I initially joined my job right after college there was a point where I was constantly
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Q2. It's a great organisation and I've learner a lot here but it's such a small company that it's difficult to find ways to move up ask yourself what makes you feel passionate or happy when you work😊
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Q3. Opportunity great time interest must
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Group discussion can also provide feedback to instructors on participant comprehension.

Reasoning
Coding
Spit out
General discussion

Algorithm coding
Array sorting
Machine learning
SQL
Python
C#

It was easy consisting of sql and excel questions