Apple Senior Data Analyst Interview Questions | Day 9
Topic – Apple Senior Data Analyst Interview Questions
Company – Apple
Designation – Senior Data Analyst
Salary – 25 to 40 LPA (Depending on CTC,college and counter offers)
Apple Senior Data Analyst Interview Questions
There were in total 4 rounds including Hiring Manager round. The process is a bit lengthy as the result of each round takes 5-7 working days. The difficulty level was decent, not very hard. There were no case studies , but the hiring manager round was important as you need to answer questions like
‘What motivates you to come to Apple?’
‘What is the one improvement we need to work on on any of our product?’
Round 1 – SQL Basics and project details
Round 2 – Project and SQL
Round 3 – SQL, Python and Project
Round 4 – Hiring Manager Round
Since there were multiple rounds on SQL, following is the list of questions and topics asked in all the rounds of SQL:-
– Exploding column, basically unnesting of a column. This is an important concept as at times we need to convert
– Concepts of moving sum, the question was to have a moving sum for a table that had revenue of each hotel with date of business
– Data Pipeline – The concepts and infrastructure of the current company
– Add 2 days in a date in Presto
date ‘2012-08-08’ + interval ‘2’ day
– Advantage and Disadvantage of DBMS
Advantage of DBMS:
Restriction of unauthorized access
Enforcing Integrity Constraints
Providing backup and recovery
Inconsistency can be avoided
Disadvantages of DBMS:
Complexity, End – users and the Database Administrators must understand all the functionalities.
Occupying large portion of disk space.
Cost of DBMS, High Initial Investment.
Not useful in situations where the applications are well defined, simple and not expected to change.
Higher impact of failure, due to the centralization of resources, failure of any component may bring down the DBMS.
– Difference between DBMS and RDBMS –
DBMS stores data as file.
Data is stored in hierarchical form.
Normalization not present.
No security to data manipulation.
No relation between the tables.
Doesn’t support distributed database.
Meant for organizations that deal with small data, it supports single user.
RDBMS stores data in tabular form.
Tables have a unique identifier called the primary key to identify tuples uniquely.
Defines integrity constraints for ACID properties.
Relationship between data values is stored as a table.
Supports distributed database.
Meant for organizations that deal with large volumes of data supporting multiple users.
Also, go through the following definition (sitters, but you can not mess up here)
Entity – A thing in the real world with an independent existence.
Entity type – Set of entities that have some attributes.
Weak Entity Set – An entity set may not have sufficient attributes to form a primary key and its primary key consists of its partial key and primary key of the parent entity.
Table – In RDBMS data is organized in tables, these tables are called relations.
Row/Tuple – A row in a table represents the relationship among a set of values.
Attributes – Are the properties of the relation and are also known as columns.
Degree of a relation – The number of attributes (columns) in a relation (table).
Cardinality of a relation – The number of tuples (rows) in a relation (table).
View – A view is a (virtual) table that doesn’t exist physically, instead is derived from one or more underlying base tables.
Primary Key – Set of one more attributes that uniquely identifies tuples within a relation.
Candidate Key – All combinations of attributes that can serve as a primary key are the candidates for the primary key position.
Alternate Key – A candidate key that is not a primary key.
Foreign Key – A non-key attribute whose values are derived from the primary key of some other table is a foreign key in its own table.
DDL (DATA DEFINTION LANGUAGE) – The DDL provides a set of definitions to specify to specify the storage structure and access methods of the database system.
DML (DATA MANIPULATIVE LANGUAGE) – The DML enables user to manipulate or access data as organized by the appropriate data model.
Project Level Questions
Very deep and directed questions were asked based on your project. You need to be very thorough with the project, for me the questions were asked on statistics(basics), coding logic and impact of the project.
– Work on the basic concepts of ranking, window functions, etc. from the below link (questions get repeated a lot)
Day 1 –Zomato Business Analyst Interview Questions
Day 2 – AirBnB Data Scientist Interview Questions
Day 3 – Myntra Business Analyst Interview Questions
Day 4 – Amazon Business Intelligence Engineer Interview Questions
Day 5 –Linkedin Business Analyst Interview Questions
Day 6 –OYO Rooms Data Analyst Interview Questions
Day 7 – Swiggy Data Analyst Interview Questions
Day 8 – EXL Senior Consultant Interview Questions
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
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
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:-
Company-wise Data Science Interview Questions – Must Watch
Keep Learning !!