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DBMS and Data Warehousing Concepts

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Questions and Answers

Which of the following options is NOT a component of a DBMS?

Data Definition

Data Normalization (correct)

Data Administration

Data Manipulation

Which statement about data marts is INCORRECT?

Data marts can lead to data duplication in organizations.

Data mart is a subtype of a Data Warehouse.

Data marts are simpler to design compared to Data Warehouses.

Data mart is focused on all departments of a company. (correct)

Which statement about the characteristics of Big Data is INCORRECT?

Volume relates to the total amount of data.

Velocity refers to the quality and accuracy of data. (correct)

Variety indicates the different types of data present.

Velocity deals with the speed at which data is generated.

Which of the following is NOT a primary component of a Data Warehouse?

<p>Sorting</p> Signup and view all the answers

Which of the following is NOT true regarding data marts?

<p>They aim to cover all organizational data.</p> Signup and view all the answers

Study Notes

DBMS Components

Data Definition is a component of DBMS
Data Normalization is NOT a component of DBMS
Data Administration is a component of DBMS
Data Manipulation is a component of DBMS

Data Mart vs. Data Warehouse

Data mart is a subtype of a Data Warehouse.
Data mart is easier to design and implement than a Data Warehouse.
Data mart can lead to data duplication across departments.
Data mart focuses on specific departments.

Big Data Characteristics

Volume: Amount of data.
Variety: Diversity of data types.
Velocity: Data quality and accuracy.
Value: Value Big Data can provide.

Data Warehouse Components

Extraction, transformation, and loading (ETL)
Input
Output
Sorting is NOT a major component of a Data Warehouse.

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Description

This quiz tests your knowledge on the components of Database Management Systems, distinctions between Data Marts and Data Warehouses, and the characteristics of Big Data. Prepare to explore key concepts including ETL processes and the importance of data variety and volume in today's data landscape.