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NiT DATA Interview Questions and Answers

Updated 23 Oct 2024

Q1. SQL query : Write a query to find the employees from employee table whose middle name is 'Mohan' and have salary more than 2 lac

Ans.

Query to find employees with middle name 'Mohan' and salary over 2 lac.

  • Use SELECT statement to retrieve data from employee table

  • Use WHERE clause to filter employees with middle name 'Mohan' and salary over 2 lac

  • Example: SELECT * FROM employee WHERE middle_name = 'Mohan' AND salary > 200000

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Q2. Count the common occurrence of elements of list A and list B

Ans.

Count common elements in two lists

  • Iterate through both lists and count occurrences of each element

  • Use a dictionary to store counts of elements in both lists

  • Return the common elements and their counts

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Q3. How to migrate the datawarehouse with gcp services using real time data services

Ans.

Real-time data services can be used to migrate datawarehouse with GCP services.

  • Use Cloud Dataflow to ingest and transform data in real-time

  • Use Cloud Pub/Sub to stream data to BigQuery or Cloud Storage

  • Use Cloud Dataproc to process data in real-time

  • Use Cloud Composer to orchestrate data pipelines

  • Use Cloud Spanner for real-time transactional data

  • Use Cloud SQL for real-time relational data

  • Use Cloud Bigtable for real-time NoSQL data

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Q4. WAP to convert a string into uppercase and lowercase

Ans.

A program to convert a string into uppercase and lowercase.

  • Use built-in functions like toUpperCase() and toLowerCase() to convert the string.

  • Iterate through each character of the string and convert it to uppercase or lowercase accordingly.

  • Ensure to handle special characters and spaces appropriately.

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Q5. Describe any one project in detail with code manipulation

Ans.

Developed a cloud-based data analytics platform using Python and AWS services

  • Used AWS Lambda functions for serverless computing

  • Implemented data processing pipelines with AWS Glue and S3

  • Utilized Python libraries like Pandas and NumPy for data analysis

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Q6. How to create data pipeline in gcp

Ans.

Data pipelines in GCP can be created using various tools like Dataflow, Dataproc, and Cloud Composer.

  • Choose the appropriate tool based on the use case and data volume

  • Define the data source and destination

  • Create a pipeline using the chosen tool and define the data transformations

  • Test and deploy the pipeline

  • Monitor and troubleshoot the pipeline for any issues

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Q7. What services in gcp u have used

Ans.

I have used various services in GCP including BigQuery, Dataflow, Cloud Storage, and Pub/Sub.

  • BigQuery for data warehousing and analytics

  • Dataflow for data processing and ETL

  • Cloud Storage for storing and accessing data

  • Pub/Sub for messaging and event-driven architectures

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Q8. Replication performance issues

Ans.

Replication performance issues can arise due to network latency, hardware limitations, and inefficient queries.

  • Network latency can cause delays in replication, leading to slower performance.

  • Hardware limitations such as insufficient memory or slow disk speeds can also impact replication performance.

  • Inefficient queries can cause replication to lag behind, leading to slower performance.

  • Monitoring replication lag and optimizing queries can help improve replication performance.

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