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Innova Solutions Data Science Intern Interview Questions and Answers
Innova Solutions Data Science Intern Interview Experiences
1 interview found
Anonymous
(1 Question)
- Q1. What is your goal in life
- Ans.
My goal in life is to make a positive impact on others and continuously learn and grow.
To make a positive impact on others through my work and actions
To continuously learn and grow personally and professionally
To achieve a work-life balance that allows me to pursue my passions and interests
Top trending discussions
Interview questions from similar companies
I applied via Campus Placement and was interviewed before Jan 2021. There were 4 interview rounds.
Interview Questionnaire
3 Questions
- Q1. Describe your projects?
- Q2. What are the technologies you have worked on?
- Ans.
I have worked on various technologies including Hadoop, Spark, SQL, Python, and AWS.
Experience with Hadoop and Spark for big data processing
Proficient in SQL for data querying and manipulation
Skilled in Python for data analysis and scripting
Familiarity with AWS services such as S3, EC2, and EMR
Knowledge of data warehousing and ETL processes
- Q3. Behavioral Questions
Interview Preparation Tips
I applied via Walk-in and was interviewed before Feb 2020. There was 1 interview round.
Interview Questionnaire
1 Question
- Q1. Interview mainly asked about spark architecture.
Interview Preparation Tips
I applied via Campus Placement and was interviewed before Jul 2021. There were 3 interview rounds.
In this round we have aptitude plus coding mcq questions
Here we have to write full fledge code 2 questions were there and are easy
(1 Question)
- Q1. Here we have hr plus technical interview
Interview Preparation Tips
I applied via Campus Placement and was interviewed before Jul 2020. There was 1 interview round.
Interview Questionnaire
1 Question
- Q1. Joined as a fresher, basic C program algo
Interview Preparation Tips
Interview Questionnaire
1 Question
- Q1. What is the architecture of Spark
- Ans.
Spark has a master-slave architecture with a cluster manager and worker nodes.
Spark has a driver program that communicates with a cluster manager to allocate resources and schedule tasks.
The cluster manager can be standalone, Mesos, or YARN.
Worker nodes execute tasks and store data in memory or on disk.
Spark can also utilize external data sources like Hadoop Distributed File System (HDFS) or Amazon S3.
Spark supports va...
Skills evaluated in this interview
I applied via Referral and was interviewed before Jun 2021. There were 2 interview rounds.
(3 Questions)
- Q1. SQL based scenario mostly windows functions
- Q2. Basic data warehouse concepts
- Q3. Basic ETL and data modelling issues
Interview Preparation Tips
- ETL
- SQL
- Data Warehousing
- Data Modeling
- Python
I have work experience on talend ETL they asked basic concepts of ETL, Data warehouse and data modelling.
Basic questions about
Selected
I applied via Recruitment Consulltant and was interviewed in Oct 2023. There were 2 interview rounds.
Test kn logical reasons , date time , train , relationship questions.
Basic python questions
Selected
I applied via Naukri.com and was interviewed in Sep 2023. There was 1 interview round.
(1 Question)
- Q1. Explain ur experience
- Ans.
I have 5 years of experience working as a Data Engineer in various industries.
Developed ETL pipelines to extract, transform, and load data from multiple sources into a data warehouse
Optimized database performance by tuning queries and indexes
Implemented data quality checks to ensure accuracy and consistency of data
Worked with cross-functional teams to design and implement data solutions for business needs
Interview Preparation Tips
Selected
I applied via Company Website and was interviewed before Apr 2023. There were 2 interview rounds.
(3 Questions)
- Q1. Intro from the candidate
- Q2. Projects he has worked on in the data engineering field
- Ans.
I have worked on projects involving building data pipelines, optimizing data storage, and implementing data processing algorithms.
Built data pipelines to extract, transform, and load data from various sources
Optimized data storage by implementing efficient database schemas and indexing strategies
Implemented data processing algorithms for real-time and batch processing
Worked on data quality monitoring and data governanc
- Q3. Tools and technologies and challenges faced
- Ans.
As a data engineer, I have experience with tools like Apache Spark, Hadoop, and SQL. Challenges include data quality issues and scalability.
Experience with Apache Spark for processing large datasets
Proficiency in Hadoop for distributed storage and processing
Strong SQL skills for querying and manipulating data
Challenges include dealing with data quality issues
Challenges with scalability as data volume grows
(2 Questions)
- Q1. Intro from the candidate
- Q2. Salary disscussion
Interview Preparation Tips
- AWS
- Data Warehousing
- Daat pipeline
- Python
- SQL
- Snowflake
Skills evaluated in this interview
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