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Kadence International Data Executive Interview Questions and Answers
Kadence International Data Executive Interview Experiences
1 interview found
Anonymous
(2 Questions)
- Q1. Syntax writing on spss
- Ans.
Syntax writing on SPSS involves using commands to manipulate and analyze data.
SPSS syntax is written in the syntax editor within the SPSS software.
Commands are written in a specific format, such as 'MEANS' for calculating means or 'FREQUENCIES' for generating frequency tables.
Syntax can be saved and reused for future analyses, saving time and ensuring consistency.
Errors in syntax can lead to incorrect results, so it's ...
- Q2. Data validation on spss
- Ans.
Data validation on SPSS involves checking for accuracy, consistency, and completeness of data.
Data validation ensures that the data entered is accurate and reliable.
It involves checking for missing values, outliers, and inconsistencies in the data.
Examples of data validation techniques in SPSS include frequency checks, range checks, and logic checks.
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Interview questions from similar companies
Selected
I was interviewed in Sep 2024.
They asked various questions on guestimates and few SQL Questions
(2 Questions)
- Q1. They asked questions on spark, SQL and Python
- Q2. They asked questions on ADF as well
(2 Questions)
- Q1. They majorly focused on PySpark and ADF in this round
- Q2. They focused on the project also in this round
(1 Question)
- Q1. They focused on managerial-related questions in this round
I applied via Naukri.com and was interviewed in Dec 2024. There was 1 interview round.
(2 Questions)
- Q1. Explain any ML model.
- Q2. Create Dataframe from two lists.
Interview Preparation Tips
- Python
- pandas
- ML
Rishu Paul
They will ask aptitude, reasoning and other questions as an online test to know your problem solving skills.
They will give a topic where either we have to speak or write on that topic
(2 Questions)
- Q1. Intro, questions related to python, guesstimate questions
- Q2. Behavorial questions and other hr questions included
(2 Questions)
- Q1. Self introduction
- Q2. Excel questions
Interview Preparation Tips
I applied via Referral and was interviewed in Sep 2024. There were 2 interview rounds.
(2 Questions)
- Q1. What is coalesce
- Ans.
Coalesce is a function used to return the first non-null value in a list of expressions.
Coalesce function is commonly used in SQL to handle null values.
It takes multiple arguments and returns the first non-null value.
Example: COALESCE(column1, column2, 'default') will return the value of column1 if not null, else column2, and if both are null, it will return 'default'.
- Q2. What is repartition
- Ans.
Repartition is the process of redistributing data across partitions in a distributed system.
Repartitioning helps in balancing the workload and improving performance in distributed computing environments.
It involves moving data between partitions based on certain criteria such as key values or hash functions.
Repartitioning can be done in Spark using operations like repartition() or coalesce().
(2 Questions)
- Q1. Non repeatable character
- Ans.
A non repeatable character is a character that appears only once in a given string.
Iterate through the string and count the frequency of each character
Identify the characters that have a frequency of 1
Return the first non repeatable character found
- Q2. Sort list without sort method
- Ans.
Sort list without using sort method
Create a custom sorting function using loops
Compare each element with every other element to determine the correct order
Swap elements based on the comparison results
Skills evaluated in this interview
Janani S. P.
(1 Question)
- Q1. About pharmacology
Selected
I applied via Recruitment Consulltant and was interviewed in Apr 2024. There were 2 interview rounds.
Excel data analytics case
(1 Question)
- Q1. Data analytics, data visualisation tools
Interview Preparation Tips
I applied via Naukri.com and was interviewed in Sep 2023. There was 1 interview round.
(1 Question)
- Q1. How to read and write parquet files in pyspark?
- Ans.
Reading and writing parquet files in PySpark involves using the SparkSession API.
Create a SparkSession object
Read a parquet file using spark.read.parquet() method
Write a DataFrame to a parquet file using df.write.parquet() method
Skills evaluated in this interview
I applied via Referral and was interviewed in Apr 2022. There were 2 interview rounds.
Discussed about company and work related topic
(1 Question)
- Q1. Self introduction , mathematical questions
Interview Preparation Tips
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