Welcome to the Important Terms and Definitions MCQs Page

Dive deep into the fascinating world of Important Terms and Definitions with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Important Terms and Definitions, a crucial aspect of Data Warehousing and OLAP. In this section, you will encounter a diverse range of MCQs that cover various aspects of Important Terms and Definitions, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Warehousing and OLAP.

Check out the MCQs below to embark on an enriching journey through Important Terms and Definitions. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Warehousing and OLAP.

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Important Terms and Definitions MCQs | Page 8 of 14

Explore more Topics under Data Warehousing and OLAP

01

The Compelling Need for Data Warehousing

02

Building Blocks of Data Warehouse 🔒

03

Trends in Data Warehousing 🔒

04

Planning and Project Management 🔒

05

Defining the Business Requirements

06

Requirements as the Driving Force for Data warehousing 🔒

07

Architectural Components 🔒

08

Infrastructure as the Foundation for Data Warehousing 🔒

09

Role of Metadata in Data Warehousing 🔒

10

Principles of Dimensional Modeling

11

Advanced Topics in Dimensional Modeling 🔒

12

Data Extraction,Transformation and Loading 🔒

13

Importance of Data Quality

14

Matching Information to the Classes of Users

15

OLAP in the Data Warehouse 🔒

16

Data Warehousing and the Web 🔒

17

Data Mining Basics 🔒

18

The Physical Design Process 🔒

19

Data Warehouse Deployment 🔒

20

Growth and Maintenance

Q71.

What is the purpose of KM (Knowledge Management) in a computing environment?

Accumulating and encoding software applications

Managing physical resources in an enterprise

Accumulating, encoding, storing, and managing enterprise knowledge

Encoding and managing external data sources

Discuss

Answer: (c).Accumulating, encoding, storing, and managing enterprise knowledge Explanation:Knowledge Management (KM) is a computing environment for accumulating, encoding, storing, and managing enterprise knowledge.

Q72.

What does LAN stand for, and what does it connect within an organization?

Large Area Network; connecting computing devices across a wide geographic area

Local Area Network; connecting computing devices within a small area

Linked Area Network; connecting computing devices with shared resources

Logical Area Network; connecting computing devices with similar functions

Discuss

Answer: (b).Local Area Network; connecting computing devices within a small area Explanation:LAN stands for Local Area Network, connecting computing devices located within a small area.

Q73.

What are Legacy Systems in the context of computing?

Advanced computer applications

Current and up-to-date applications

Old computer applications on disparate platforms, supported by outdated database systems

Innovative and cutting-edge technologies

Discuss

Answer: (c).Old computer applications on disparate platforms, supported by outdated database systems Explanation:Legacy Systems are old computer applications on disparate platforms, supported by outdated database systems that are still in use in many companies, as legacies from the past.

Q74.

What is a Load Image in the context of loading a database table?

Visual representation of database records

Graphic representation of database tables

Record layout in a flat file for loading a database table using database utility programs

Image processing technique for database optimization

Discuss

Answer: (c).Record layout in a flat file for loading a database table using database utility programs Explanation:A Load Image is a record layout in a flat file for loading a database table, generally by using database utility programs. The record layout of the flat file is an exact match or image of the table.

Q75.

What is the purpose of a Log file in a database management system?

Recording all database transactions

Storing database records

Managing data relationships

Performing database recovery

Discuss

Answer: (a).Recording all database transactions Explanation:A Log file is used by the database management system to record all database transactions. The log file is used for the recovery of the database in case of failures.

Q76.

What characterizes a Mainframe computer system?

Small size and limited capabilities

Medium-sized computer system

Large computer system with extensive capabilities and resources, usually housed in a large computer center

Portable and mobile computer system

Discuss

Answer: (c).Large computer system with extensive capabilities and resources, usually housed in a large computer center Explanation:A Mainframe is a large computer system with extensive capabilities and resources, usually housed in a large computer center.

Q77.

What does MDAPI stand for, and what is its significance in the context of OLAP?

Multidimensional Database Application Programming Interface; a database interface for multidimensional data storage

Multidimensional Data Access Protocol Interface; a protocol for data exchange in multidimensional databases

Multi-Dimensional Application Programmers Interface; the standard developed by the OLAP Council

Multi-Dimensional Database Programming Interface; a programming interface for multidimensional data cubes

Discuss

Answer: (c).Multi-Dimensional Application Programmers Interface; the standard developed by the OLAP Council Explanation:MDAPI stands for Multi-Dimensional Application Programmers Interface, which is the standard developed by the OLAP Council.

Q78.

What is an MDDB, and how does it store data?

Multidimensional Database Definition; a schema for defining multidimensional databases

Master Data Database; a database for storing nontransactional data entities

Multidimensional Database; a proprietary database storing multidimensional data cubes using multidimensional arrays

Metadata Database; a database storing information about the data itself

Discuss

Answer: (c).Multidimensional Database; a proprietary database storing multidimensional data cubes using multidimensional arrays Explanation:MDDB stands for Multidimensional Database, and it is a proprietary database meant to store multidimensional data cubes. MDDBs use multidimensional arrays to store data.

Q79.

What is the purpose of Master Data Management (MDM)?

Managing transactional data entities

Managing metadata for databases

Managing multidimensional data cubes

Consistently defining and managing nontransactional data entities of an organization

Discuss

Answer: (d).Consistently defining and managing nontransactional data entities of an organization Explanation:Master Data Management (MDM) comprises a set of processes and tools that consistently define and manage the nontransactional data entities of an organization, such as customers and products.

Q80.

What is Metadata in the context of a database?

Data representing transactions

Data used for multidimensional analysis

Data about data itself, such as data type, length, format, default values, etc.

Data stored in multidimensional arrays

Discuss

Answer: (c).Data about data itself, such as data type, length, format, default values, etc. Explanation:Metadata is data about data itself, such as data type, length, format, default values, etc., in a database.

Page 8 of 14

Building Blocks of Data Warehouse 🔒

Trends in Data Warehousing 🔒

Planning and Project Management 🔒

Requirements as the Driving Force for Data warehousing 🔒

Architectural Components 🔒

Infrastructure as the Foundation for Data Warehousing 🔒

Role of Metadata in Data Warehousing 🔒

Advanced Topics in Dimensional Modeling 🔒

Data Extraction,Transformation and Loading 🔒

OLAP in the Data Warehouse 🔒

Data Warehousing and the Web 🔒

Data Mining Basics 🔒

The Physical Design Process 🔒

Data Warehouse Deployment 🔒

Welcome to the Important Terms and Definitions MCQs Page

Important Terms and Definitions MCQs | Page 8 of 14

Explore more Topics under Data Warehousing and OLAP

The Compelling Need for Data Warehousing

Defining the Business Requirements

Principles of Dimensional Modeling

Importance of Data Quality

Matching Information to the Classes of Users

Growth and Maintenance

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