Intelligent SQL Server 2014 Assessment Test

SQL stands for Structured Query Language. It is a programming language that is used to manage and manipulate relational databases. SQL allows users to create, modify, and retrieve data from databases using a set of predefined commands and statements. It is widely used in the field of database management and is considered the standard language for interacting with relational databases.

In an RDBMS (Relational Database Management System), the data is stored in tables. Tables are used to organize and store data in a structured manner, with rows representing individual records and columns representing different attributes or fields of the data. These tables are then used to establish relationships between different sets of data, enabling efficient storage, retrieval, and manipulation of information in the database.

When data is updated in a view, it means that the existing information in the view has been modified or changed. This update does not affect the original data in the table, but only the representation of that data in the view. Therefore, the correct answer is "Updated" because the data in the view has been updated, not deleted, cleaned, or removed from the table.

The given options are all examples of queries and commands in the Data Manipulation Language (DML) of SQL, which is used to retrieve, modify, and delete data in a database. However, "Drop table" is not a query or command used to manipulate data. It is a Data Definition Language (DDL) command used to delete an entire table from the database.

An index is a physical structure that contains pointers to a table. It helps in optimizing the retrieval of data from a database by allowing quick access to specific rows based on the values in certain columns. By using pointers, the index can efficiently locate the desired data without having to scan the entire table. This improves the performance of queries and reduces the time required for data retrieval.

DBMS (Database Management System) is the correct answer because it is a software that stores and manages SQL triggers. A DBMS is responsible for managing databases, including creating, modifying, and deleting database structures, as well as handling queries and transactions. Triggers are database objects that are associated with a table and are automatically executed in response to specific events or actions, such as inserting, updating, or deleting data. Therefore, a DBMS is the appropriate choice for storing and managing SQL triggers.

The reason why truncate is faster than delete in SQL is because it only deletes data from the database without keeping a record of the deleted records. On the other hand, the delete operation writes the deleted records into a rollback table, which requires additional time and resources. Therefore, truncate is faster as it simply removes the data from the database without any additional steps.

DDL stands for Data Definition Language, which is used to define and manage the structure of the database. It includes commands like CREATE, ALTER, and DROP, which are used to create, modify, and delete database objects like tables, indexes, and constraints.

DML stands for Data Manipulation Language, which is used to manipulate and query the data stored in the database. It includes commands like SELECT, INSERT, UPDATE, and DELETE, which are used to retrieve, insert, update, and delete data from tables.

Therefore, the correct answer is DDL and DML as these are the two parts of SQL that deal with defining and managing the structure of the database and manipulating and querying the data stored in the database, respectively.

The statement "The result of using a view are permanently stored in the database" is not true. Views in a database are virtual tables that are generated on the fly based on the underlying data. They do not store any data themselves. When a view is queried, it retrieves the data from the underlying tables. Any changes made to the underlying tables will be reflected in the view, but the view itself does not store the data permanently.

Normalization is the process used to optimize databases and remove the potential for redundancy. It involves organizing the data in a database to eliminate duplicate information and ensure data integrity. By breaking down the database into smaller, more manageable tables and establishing relationships between them, normalization helps to minimize data redundancy and improve efficiency in data storage and retrieval.