Sony India Software Center Interview Rounds and Process
Explain the three different types of data models.
Prepare for Your Next Big Data Job Interview with Kafka Interview Questions and Answers
1 Define normalization.
The method of effectively organizing data in a database is known as normalization. The normalization process helps in:
Normalization is useful for minimizing data storage and logically storing data in multiple tables.
1 What do you understand by data models? What is data modelling?
A data model is a visual description of business needs (logical data model) or database objects (physical data model) needed for a database, and its particularly useful for defining and interpreting such objectives and entities.
The practice of using words and symbols to represent data and how it flows in a basic representation of a software system and the data elements it contains is called data modelling. Overall, data modelling assists an organization in successfully using its data to satisfy business information needs.
9 How can you build domains in the ERwin Tool?
Along with the pre-existing domains, you can add new domains using the Domain Editor. When you are in logical edit mode or a physical model, you can build a domain (physical edit mode). Depending on the edit mode, several choices are available in the editor.
4 What is Amazon Aurora?
Amazon Aurora is a high-availability, automated failover relational database engine that supports MySQL and PostgreSQL. To put it another way, Amazon Aurora is a hybrid of MySQL and Postgres. Aurora is a multi-threaded, multiprocessor database engine that prioritizes performance, availability, and operational efficiency.
Amazon Aurora differs from typical MySQL and Postgres database engines in that it does not employ a Write-Ahead Log, but it does feature a crash recovery scheme. Amazon also provides the feature to duplicate data from an Amazon Aurora database to a MySQL or Postgres database on the same instance, as well as vice versa, allowing you to employ the two databases together.
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