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Partitioning is the process of dividing a large dataset into smaller, more manageable parts based on certain criteria.
Partitioning helps in improving query performance by reducing the amount of data that needs to be processed.
It can be done based on ranges, hash values, or specific columns.
Examples include partitioning a sales database by date ranges or partitioning a customer database by geographic regions.
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I applied via Referral and was interviewed in Sep 2020. There were 3 interview rounds.
I applied via Campus Placement and was interviewed before Dec 2020. There were 3 interview rounds.
Clear user stories ensure client success. Here's how:
Understand the client's needs and goals
Break down the user story into smaller, manageable tasks
Use clear and concise language
Include acceptance criteria for each task
Collaborate with the client to ensure understanding and agreement
Regularly review and update the user story as needed
User stories should be concise, specific, and focused on the user's needs.
User stories should be written from the perspective of the user
They should be short and focused on a single feature or functionality
They should include acceptance criteria to ensure the story is complete
They should be prioritized based on business value and user needs
I applied via Campus Placement and was interviewed before Jan 2021. There were 4 interview rounds.
I applied via Referral and was interviewed in Dec 2020. There were 5 interview rounds.
I was interviewed before Jul 2021.
It consisted of logical and quantitative along with Verbal.
I was interviewed before Feb 2021.
I applied via LinkedIn and was interviewed before Jan 2021. There were 3 interview rounds.
I applied via Naukri.com and was interviewed before Nov 2020. There was 1 interview round.
I applied via Referral and was interviewed in Nov 2020. There were 3 interview rounds.
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