Bharat Sanchar Nigam Data Management Executive Interview Questions and Answers

It was basic coding to test the Python skills like reading data from local and uploading in cloud then some basic dag related questions

Q1. Clustering and partition difference in data warehousing solutions
Ans. 
Clustering involves grouping similar data together, while partitioning involves dividing data into smaller, manageable sections.
• Clustering is used to group similar data points together based on certain criteria, such as customer segments or product categories.

• Partitioning involves dividing a large dataset into smaller, more manageable sections for easier data retrieval and processing.

• Clustering is often used for data a...read more
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Q2. What are the different approaches to Optimising SQL
Ans. 
Different approaches to optimizing SQL include indexing, query optimization, and database design.
• Use indexing to improve query performance

• Optimize queries by avoiding unnecessary joins and using appropriate functions

• Design the database schema efficiently to reduce redundancy and improve data retrieval speed
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Q3. Spark and it’s architecture
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Q4. Finding the count of Item bought by an customer from Flipkart during a year excluding February
Ans. 
To find the count of items bought by a customer from Flipkart during a year excluding February, you need to aggregate the data and filter out February transactions.
• Aggregate the data by customer and item purchased

• Filter out transactions from February

• Count the number of items bought by each customer
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Q1. Difference between Data Warehouse, Data Lakes and Tables
Ans. 
Data Warehouse stores structured data for reporting and analysis, Data Lakes store raw and unstructured data, Tables are basic data structures.
• Data Warehouse is used for storing structured data from various sources for reporting and analysis.

• Data Lakes store raw and unstructured data in its native format for future processing and analysis.

• Tables are basic data structures used to organize and store data in a structured ...read more
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Q2. Query difference betweeen Group by and Partition by
Ans. 
Group by is used to group rows that have the same values into summary rows, while Partition by is used to divide the result set into partitions to which the function is applied separately.
• Group by is used with aggregate functions to group rows based on a column or set of columns.

• Partition by is used with window functions to divide the result set into partitions.

• Group by is used with SELECT statement, while Partition by...read more
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Q3. Machine Learning questions such as Regression, Trees etc
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Q1. Explain difference between joins
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Q2. What is your area of intrest
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Q1. Sql question related to windows function
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Q2. Unix basics - find a word in a set of files
Ans. 
Using Unix command 'grep' to find a word in a set of files
• Use 'grep' command followed by the word you want to search for and the file(s) you want to search in

• Add the '-r' flag to search recursively in all files in a directory

• Use '-i' flag for case-insensitive search

• Example: grep 'hello' file.txt

• Example: grep -r 'error' /path/to/directory

• Example: grep -i 'apple' file1.txt file2.txt
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Q3. Python question related to file system, regex
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Q1. Questions were based on DSA and C
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Q2. It was basically a coding round with simple logic
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Q1. What is the difference between start schema and snowflake schema
Ans. 
Star schema is a denormalized schema with a single fact table and multiple dimension tables, while snowflake schema is a normalized schema with multiple dimension tables normalized into sub-dimension tables.
• Star schema has a single fact table surrounded by multiple dimension tables, while snowflake schema has dimension tables normalized into sub-dimension tables.

• In star schema, dimensions are denormalized, while in sno...read more
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Q2. How do you load data into bigquery using dataflow
Ans. 
Data can be loaded into BigQuery using Dataflow by creating a pipeline in Dataflow that reads data from a source and writes it to BigQuery.
• Create a Dataflow pipeline using Apache Beam SDK

• Read data from a source such as Cloud Storage or Pub/Sub

• Transform the data as needed using Apache Beam transformations

• Write the transformed data to BigQuery using BigQueryIO.write()
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Q1. Power BI get data
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Q2. Excel summation
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Q1. Tell me about your self
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Q2. What is your weakness
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Q3. What is your strength
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Q4. What is your sallery expectation
Ans. 
My salary expectation is based on my experience, skills, and the industry standard.
• Consider my experience and skills when determining salary

• Research industry standard salaries for Data Entry Operators

• Open to negotiation based on benefits and opportunities
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