CS401A's Prelims: Info Management Module 02 Flashcards

(62 cards)

1
Q

Data Models

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

A

Database design focuses on

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2
Q

Data Models

the first step in designing a database,

A

Data Modeling, the first step in

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3
Q

Data Models

refers to the process of creating a specific \_\_\_\_ \_\_\_\_\_ for a determined problem domain.

A

Data Modeling,
refers to the process of \_\_\_\_\_\_\_\_ a specific data model for a \_\_\_\_\_\_\_\_\_\_ \_\_\_\_\_\_\_ \_\_\_\_\_\_.

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4
Q

Data Models

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

A

A data model is relatively

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5
Q

Data Models

In general terms,
is an abstraction of a more complex real-world object or event.

(Coronel and Morris, 2017, p. 36)

A

In general terms, a model is

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6
Q

Data Models

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

A

Data models can facilitate

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7
Q

Data Models

constitutes the most basic information used by a system.

A

Data constitutes

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8
Q

Data Models

\_\_\_\_\_\_\_\_\_\_\_\_ are created to manage data and to help transform data into information, but \_\_\_\_ is viewed in different ways by different people.

A

Applications are created to
but data is viewed in

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9
Q

Data Models

Basic building blocks for data model are the following:

A

Data Model Basic Building Blocks
* * Entity
* Attribute
* Relationship

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10
Q

Data Models

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

A

Data Model Basic Building Blocks
* Entity

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11
Q

Data Models

— It is a characteristic of an entity.

A

Data Model Basic Building Blocks
* Attribute

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12
Q

Data Models

— It describes an association among entities.

A

Data Model Basic Building Blocks
* Relationship

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13
Q

Data Models

○ Three (3) types of relationships:

A

Data Model Basic Building Blocks
* One-to-one (1:1) relationship
* One-to-many (1:M) relationship
* Many-to-many (M:M) relationship

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14
Q

Data Models

These models represent school of thought as to what a dabase is, what it should do, the types of structures that it should use, and technologies would be used to implement these structures.

A

Evolution of Data Model (Coronel and Morris 2017)
Hierarchical Model
Network Model
Relational Model
Entity Relationship Model
Object-Oriented Model

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15
Q

Data Models

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

A

Evolution of Data Model (Coronel and Morris 2017)
Hierarchical Model

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16
Q

Data Models

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

A

Evolution of Data Model (Coronel and Morris 2017)
Hierarchical Model

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17
Q

Data Models

It contains levels, or segments.

A

Evolution of Data Model (Coronel and Morris 2017)
Hierarchical Model

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18
Q

Data Models

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

A

Evolution of Data Model (Coronel and Morris 2017)
Hierarchical Model
- Segment

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19
Q

Data Models

- It was created to represent complex \_\_\_\_ \_\_\_\_\_\_\_\_\_\_\_\_\_ more effectively than the \_\_\_\_\_\_\_\_\_\_\_\_ \_\_\_\_\_, to improve database standard.

A

Evolution of Data Model (Coronel and Morris 2017)
Network Model
- It was created to represent \_\_\_\_\_\_\_ data relationships more \_\_\_\_\_\_\_\_\_\_\_ than the hierarchical model, to \_\_\_\_\_\_\_ database standard.

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20
Q

Data Models

is generally used today, the standard database concepts that emerged with the \_\_\_\_\_\_\_ \_\_\_\_\_ are still used by modern data models.

A

Evolution of Data Model (Coronel and Morris 2017)
Network Model
- The network database model is generally used today, the standard database concepts that emerged with the network model are still used by modern data models.
Schema
Subschema
Data Manipulation Language (DML)
Data Definition Language (DDL)

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21
Q

Data Models

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

A

Evolution of Data Model (Coronel and Morris 2017)
Schema

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22
Q

Data Models

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

A

Evolution of Data Model (Coronel and Morris 2017)
Subschema

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23
Q

Data Models

— It defines the environment in which data can be managed.

A

Evolution of Data Model (Coronel and Morris 2017)
Data Manipulation Language (DML)

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24
Q

Data Models

— It allows the database administrator to define the schema components

A

Evolution of Data Model (Coronel and Morris 2017)
Data Definition Language (DDL)

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25
# **Data Models** `-` It was introduced in 1970 by E.F. Codd of IBM.
**Evolution of Data Model (Coronel and Morris 2017)** **Relational Model**
26
# **Data Models** represented a major breakthrough for both users and designers.
**Evolution of Data Model (Coronel and Morris 2017)** **Relational Model** `-` The relational model
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# **Data Models** `-` The foundation of mathematical concept is known as a
**Evolution of Data Model (Coronel and Morris 2017)** relation.
28
# **Data Models** It was introduced in 1970 by Peter Chen.
**Evolution of Data Model (Coronel and Morris 2017)** **Entity Relationship Model**
29
# **Data Models** `-` The graphical representation of entities and their relationships in a database structure quickly became popular, because it complemented the relational data model concepts.
**Evolution of Data Model (Coronel and Morris 2017)** **Entity Relationship Model**
30
# **Data Models** are combined to provide the foundation for tightly structured database design.
**Evolution of Data Model (Coronel and Morris 2017)** `-` The relational data model and ERM
31
# **Data Models** both data and its relationships are contained in a single structure known as an `______`.
**Evolution of Data Model (Coronel and Morris 2017)** **Object-Oriented Model** In the Object-Oriented Data Model (OODM), both `____` and its `_____________` are contained in a single structure known as an object.
32
# **Data Models** In turn, the OODM is the basis for the
**Evolution of Data Model (Coronel and Morris 2017)** **Object-Oriented Model** Object-Oriented Database Management System (OODBMS).
33
# **Data Models** `-` The `____` is said to be a semantic data model because it indicates meaning.
**Evolution of Data Model (Coronel and Morris 2017)** **Object-Oriented Model** `-` The OODM is said to be a `________ ____ _____` because it indicates `_______`.
34
# **Data Models** **Evolution of Data Model Coronel and Morris 2017)** **Object-Oriented Model** `-` The Object-Oriented Model is based on the following components:
○ An object is an abstraction of a real-world entity ○ Attributes describe the properties of an object ○ Objects that share similar characteristics are grouped in classes. ○ Classes are organized in a class hierarchy. ○ Inheritance is the ability of an object within the class hierarchey to inherit attributes. ○ Object-oriented data models are typically depicted using Unified Modeling Language (UML) class diagrams.
35
# **Data Models** is a collection of similar objects with shared structure (attributes) and behavior (methods).
**Evolution of Data Model (Coronel and Morris 2017)** **Object-Oriented Model** `-` The Object-Oriented Model is based on the following components: A class is a collection of `_______ _______` with `______ _________` (`__________`) and `________` (`_______`).
36
# **Data Models** resembles an upside-down tree in which each class has only one parent.
**Evolution of Data Model (Coronel and Morris 2017)** **Object-Oriented Model** `-` The Object-Oriented Model is based on the following components: The class hierarchy resembles an `______`-`____ ____` in which each class has only `___` parent.
37
# **Data Models** is a language based on `______`-`________` concepts that describes a set of diagrams and symbols you can use to graphically model a system.
**Evolution of Data Model (Coronel and Morris 2017)** **Object-Oriented Model** `-` The Object-Oriented Model is based on the following components: UML is a language based on Object-Oriented concepts that describes a `___` of `________` and `_______` you can use to `___________ _____` a `______`.
38
# **Data Models** — A metalanguage used to represent and manipulate data elements.
**Evolution of Data Model (Coronel and Morris 2017)** **Extensive Markup Language (XML)**
39
# **Data Models** Unlike markup languages, permits the manipulation of a document's data elements.
**Evolution of Data Model (Coronel and Morris 2017)** **Extensive Markup Language (XML)** XML
40
# **Data Models** **Evolution of Data Model Coronel and Morris 2017)** **Emerging Data Models:**
**Big Data and NoSQL**
41
# **Data Models** `-` 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
**Evolution of Data Model (Coronel and Morris 2017)** **Big Data**
42
# **Data Models** `-` The term seems to have been first used in a computing framework by John Mashey, Silicon Graphics scientist in the 1990s.
**Evolution of Data Model (Coronel and Morris 2017)** **Big Data**
43
# **Data Models** However, it seems to be Douglas Laney, a data analyst from the Gartner Group, who first described the basic characteristics of Big Data databases:
**Evolution of Data Model (Coronel and Morris 2017)** ○ **Volume** ○ **Velocity** ○ **Variety**
44
# **Data Models** — It refers to the amounts of data being stored.
**Evolution of Data Model (Coronel and Morris 2017)** ○ **Volume**
45
# **Data Models** — 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.
**Evolution of Data Model (Coronel and Morris 2017)** ○ **Velocity**
46
# **Data Models** — It refers to the fact that the data being collected comes in multiple different data formats.
**Evolution of Data Model (Coronel and Morris 2017)** ○ **Variety**
47
# **Data Models** `-` It is a large-scale distributed database system that stores structured and unstructured data in efficient ways.
**Evolution of Data Model (Coronel and Morris 2017)** **NoSQL**
48
# **Data Models** **NoSQL** `-` The following are the general characteristics of NoSQL databases:
**Evolution of Data Model (Coronel and Morris 2017)** ○ They are not based on the relational model and SQL, hence the name NoSQL. ○ They support distributed database architectures. ○ They provide high scalability, high availability, and fault tolerance. ○ They support very large amounts of sparse data. ○ They are geared toward performance rather than transactions consistency.
49
# **Data Models** One of the big advantages of is that they generally use a distributed database node.
**Evolution of Data Model (Coronel and Morris 2017)** **NoSQL** `-` **NoSQL supports distributed database architecture**
50
# **Data Models** can handle very high volumes of data.
**Evolution of Data Model (Coronel and Morris 2017)** **NoSQL** `-` **NoSQL supports very large amounts of sparse data**
51
# **Data Models** 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.
**Evolution of Data Model (Coronel and Morris 2017)** **NoSQL** `-` **NoSQL provides high scalability, high availability, and fault tolerance**
52
# **Data Models** One of the biggest problems if very large distributed databases are enforcing data consistency.
**Evolution of Data Model (Coronel and Morris 2017)** **NoSQL** `-` **Most NoSQL databases are geared toward performance rather than transactions consistency**
53
# **Data Models** `-` It is the end user's view of the data environment.
**Degrees of Data Abstraction** **External Model**
54
# **Data Models** `-` It refers to people who use the application programs to manipulate the data and generate information.
**Degrees of Data Abstraction** **External Model**
55
# **Data Models** `- __` diagrams will be used to represent the external views. A specific representation of an external view is known as
**Degrees of Data Abstraction** **External Model** ER diagrams an **external schema**.
56
# **Data Models** `-` It represents a global view of the entire database by the entire organization.
**Degrees of Data Abstraction** **Conceptual Model**
57
# **Data Models** it is the basis for the identification and high-level description of the main data objects.
**Degrees of Data Abstraction** **Conceptual Model** `-` Also known as a **conceptual schema**,
58
# **Data Models** `-` It is the representation of the database as "seen" by the DBMS.
**Degrees of Data Abstraction** **Internal Model**
59
# **Data Models** `-` It requires the designer to match the `__________ _____`'s characteristics and constraints to those of the selected implementation model.
**Degrees of Data Abstraction** **Internal Model**
60
# **Data Models** depicts a specific representation of an `__________ _____`, using the database constructs supported by the chosen database.
**Degrees of Data Abstraction** `-` **Internal schema**
61
# **Data Models** operates at the lowest level of abstraction, describing the way data is saved on storage media.
**Degrees of Data Abstraction** **Physical Model**
62
# **Data Models** 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.
**Degrees of Data Abstraction** The physical model