CS401A's Prelims: Info Management Module 02 Flashcards

(55 cards)

1
Q

focuses on how the database structure will be used to store and manage end-user data.

A

Database design

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2
Q

the first step in designing a database,

A

Data Modeling,

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3
Q

refers to the process of creating a specific data model for a determined problem domain.

A

Data Modeling

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4
Q

is relatively simple representation, usually graphical, of more complex real-world data structures.

A

A data model

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5
Q

is an abstraction of a more complex real-world object or event.

A

a model

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6
Q

can facilitate interaction among the designer, the applications programmer, and the end user.

A

Data models

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7
Q

constitutes the most basic information used by a system.

A

Data

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8
Q

are created to manage data and to help transform data into information,

A

Applications

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9
Q

Basic building blocks for data model

A

Entity
Attribute
Relationship

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10
Q

It is a person, place, thing, or event about which data will be collected and stored.

A

Entity

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11
Q

It is a characteristic of an entity.

A

Attribute

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12
Q

It describes an association among entities.

A

Relationship

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13
Q

Three (3) types of relationships:

A

One-to-one (1:1) relationship
One-to-many (1:M) relationship
Many-to-many (M:M) relationship

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14
Q

It was developed in the 1960s to manage large amounts of data for complex manufacturing projects.

A

Hierarchical Model

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15
Q

The model’s basic logical structure is represented by an upside-down tree.

A

Hierarchical Model

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16
Q

It contains levels, or segments.

A

Hierarchical Model

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17
Q

is the equivalent of a file system’s record type.

A

Segment

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18
Q

It was created to represent complex data relationships more effectively than the hierarchical model, to improve database standard.

A

Network Model

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19
Q

is generally used today, the standard database concepts that emerged with the network model are still used by modern data models:

A

Network Model

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20
Q

the standard database concepts that emerged with the network model are still used by modern data models:

A

Schema
Subschema
Data Manipulation Language (DML)
Data Definition Language (DDL)

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21
Q

It is the conceptual organization of the entire database as viewed by the database administrator.

A

Schema

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22
Q

It defines the portion of the database by the application programs that actually produce the desired information from the data in the database.

A

Subschema

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23
Q

It defines the environment in which data can be managed.

A

Data Manipulation Language (DML)

24
Q

It allows the database administrator to define the schema components

A

Data Definition Language (DDL)

25
It was introduced in 1970 by E.F. Codd of IBM.
Relational Model
26
represented a major breakthrough for both users and designers.
The relational model
27
The foundation of mathematical concept is known as a
relation.
28
It was introduced in 1970 by Peter Chen.
Entity Relationship Model
29
The graphical representation of entities and their relationships in a database structure quickly became popular, because it complemented the relational data model concepts.
Entity Relationship Model
30
are combined to provide the foundation for tightly structured database design.
The relational data model and ERM
31
both data and its relationships are contained in a single structure known as an object.
In the Object-Oriented Data Model (OODM),
32
In turn, the OODM is the basis for the
Object-Oriented Database Management System (OODBMS).
33
A metalanguage used to represent and manipulate data elements.
Extensible Markup Language (XML)
34
Unlike markup languages, permits the manipulation of a document's data elements.
XML (Extensible Markup Language)
35
It refers to a movement to find new and better ways to manage large amounts of web and sensor-generated data and derive business insight from it
Big Data
36
The term seems to have been first used in a computing framework by John Mashey, Silicon Graphics scientist in the 1990s.
Big Data
37
However, it seems to be Douglas Laney, a data analyst from the Gartner Group, who first described the basic characteristics of Big Data databases:
Volume Velocity Variety
38
It refers to the amounts of data being stored.
Volume
39
It refers not only to the speed with which data grows but also to the need to process this data quickly in order to generate information and insight.
Velocity
40
It refers to the fact that the data being collected comes in multiple different data formats.
Variety
41
It is a large-scale distributed database system that stores structured and unstructured data in efficient ways.
NoSQL
42
One of the big advantages of is that they generally use a distributed database node.
NoSQL (databases) supports distributed database architecture
43
can handle very high volumes of data.
NoSQL (databases) supports very large amounts of sparse data
44
are designed to support web operations, such as the ability to add capacity in the form of nodes to the distributed database when the demand is high, and to do it transparently and without downtime.
NoSQL (databases) provides high scalability, high availability, and fault tolerance
45
One of the biggest problems if very large distributed databases are enforcing data consistency.
Most NoSQL databases are geared toward performance rather than transactions consistency
46
It is the end user's view of the data environment.
External Model || external schema
47
It refers to people who use the application programs to manipulate the data and generate information.
External Model || external schema
48
diagrams will be used to represent the external views. A specific representation
External Model || external schema
49
It represents a global view of the entire database by the entire organization.
Conceptual Model || conceptual schema
50
it is the basis for the identification and high-level description of the main data objects.
Conceptual Model || conceptual schema
51
It is the representation of the database as "seen" by the DBMS.
Internal Model || Internal schema
52
It requires the designer to match the conceptual model's characteristics and constraints to those of the selected implementation model.
Internal Model || Internal schema
53
depicts a specific representation, using the database constructs supported by the chosen database.
Internal Model || Internal schema
54
operates at the lowest level of abstraction, describing the way data is saved on storage media.
Physical Model
55
requires the definition of both the physical devices and the (physical) access methods required to reach the data within those storage devices, making it both software and hardware dependent.
Physical Model