Shrinivas Laboratories Data Analyst Interview Questions and Answers

It was easy normal data regarding test

Q1. Be prepared with Pyspark and SQL
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Q2. How to rename a column in pyspark
Ans. 
To rename a column in PySpark, use the 'withColumnRenamed' method.
• Use the 'withColumnRenamed' method on the DataFrame

• Specify the current column name and the new column name as arguments

• Assign the result to a new DataFrame to store the renamed column
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Q3. Difference between multiprocessing and multithreading
Ans. 
Multiprocessing involves executing multiple processes simultaneously, while multithreading involves executing multiple threads within a single process.
• Multiprocessing utilizes multiple CPUs or cores to execute multiple processes concurrently.

• Multithreading involves creating multiple threads within a single process to execute tasks concurrently.

• Processes in multiprocessing have separate memory spaces, while threads in m...read more
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Q4. Which one to use when
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Good and not that much difficult

Q1. Good, interview was gone very smooth and you should know about what you mentioned in resume
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Q1. They will ask about personal information and inform you about your role
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Q1. Do you know adobe analytics
Ans. 
Yes, I am familiar with Adobe Analytics and have experience using it for data analysis.
• I have used Adobe Analytics to track website traffic and user behavior

• I have created custom reports and dashboards using Adobe Analytics

• I am proficient in extracting insights from Adobe Analytics data to drive business decisions
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Q2. Explain example of window function
Ans. 
Window functions are used to perform calculations across a set of table rows related to the current row.
• Window functions are applied to a set of rows related to the current row in a query result.

• They can be used to calculate running totals, averages, ranks, and more.

• Examples include ROW_NUMBER(), RANK(), DENSE_RANK(), and NTILE().
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It was easy normal data regarding test

Q1. Explain example of window function
Ans. 
Window functions are used to perform calculations across a set of table rows related to the current row.
• Window functions are used in SQL to perform calculations within a specific window or subset of rows.

• They allow you to perform aggregate functions like SUM, AVG, COUNT, etc. over a specific range of rows.

• Examples include ROW_NUMBER(), RANK(), DENSE_RANK(), and NTILE().
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Q2. A question using aggregate function and case when in sql
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Q1. Difference between all union all distinct
Ans. 
ALL returns all rows, UNION removes duplicates, DISTINCT returns unique rows.
• ALL: includes all rows, even duplicates

• UNION: combines two result sets and removes duplicates

• DISTINCT: returns only unique rows

• Example: SELECT name FROM table1 UNION SELECT name FROM table2;

• Example: SELECT name FROM table1 UNION ALL SELECT name FROM table2;

• Example: SELECT DISTINCT name FROM table1;
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Q2. Convert the given dictionary to list and sort dictionary in ascending order
Ans. 
Convert dictionary to list and sort in ascending order
• Use the items() method to convert dictionary to list of tuples

• Use the sorted() function to sort the list of tuples

• Use a lambda function to sort by dictionary values

• Convert the sorted list of tuples back to a dictionary using dict() method
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