Ch 9 Flashcards

1
Q

Information system

A

The database is part of a large whole known as an information system, which provides for data collection, storage and retrieval.

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2
Q

System analysis

A

System analysis is the process that establishes the need for an information system and its extent.

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3
Q

Systems development

A

The process of creating an information system is known as systems development.

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4
Q

Database development

A

In a broad sense, the term database development describes the process of database design and implementation. The primary objective in database design is to create complete, normalized, nonredundant (to the greatest extent possible), and fully integrated conceptual, logical and physical database models.

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5
Q

Systems Development Life Cycle (SDLC)

A

The Systems Development Life Cycle (SDLC) traced the history of an information system. The SDLC provides the big picture within which the database design and application development can be mapped out and evaluated.

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6
Q

Database Life Cycle (DBLC)

A

The Database Life Cycle (DBLC) contains six phases: database initial study, database design, implementation and loading, testing and evaluation, operation, and maintenance and evolution.

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7
Q

System scope

A

The system’s scope defines the extent of the design according to operational requirements.

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8
Q

Boundaries

A

The proposed system is subject to limits known as boundaries, which are external to the system.

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9
Q

Virtualization

A

Virtualization is a technique that creates logical representations of computing resources that are independent of the underlying physical computing resources.

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10
Q

Full back-up

A

Database backups can be performed at different levels. A full backup, or dump, of the entire database. In this case, all database objects are backed up in their entirety.

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11
Q

Differential backup

A

A differential backup of the database, in which only the objects that have been updated or modified since the last full backup are backed up.

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12
Q

Transaction log backup

A

A transaction log backup, which backs up only the transaction log operations that are not reflected in a previous backup copy of the database. In this case, no other database objects are backed up.

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13
Q

Conceptual design

A

Conceptual design is the first stage in the database design process. The goal at this stage is to design a database that is independent of database software and physical details. The output of this process is a conceptual data model that describes the main data entities, attributes, relationships, and constraints of a given problem domain. This design is descriptive and narrative in form. In other words, it is generally composed of a graphical representation as well as textual descriptions of the main data elements, relationships and constraints.

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14
Q

Minimal data rule

A

All that is needed is there, and all that is there is needed.

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15
Q

Description of operations

A

Ideally, business rules are derived from a formal description of operations, which is a document that provides a precise, up-to-date, and thoroughly reviewed description of the activities that define an organization’s operating environment.

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16
Q

Module

A

A module is an information system component that handles a specific business function, such as inventory, orders, or payroll. Under these conditions, each module is supported by an ER segment that is a subset or fragment of an enterprise ER model.

17
Q

Cohesivity

A

The term cohesivity describes the strength of the relationships found among the module’s entities. A module must display high cohesivity, that is, entities must be strongly related, and the module must be complete and self-sufficient.

18
Q

Module coupling

A

Module coupling describes the extent to which modules are independent of one another. Modules must display low coupling, indicating that they are independent of other modules. Low coupling decreases unnecessary intermodule dependencies, thereby allowing the creation of a truly modular system and eliminating unnecessary relationships among entities.

19
Q

Database fragment

A

A database fragment is a subset of a database that is stored at a given location.

20
Q

Logical design

A

Logical design is the second stage in the database design process. The logical design goal is to design an enterprise-wide database that is based on a specific data model but independent of physical-level details. Logical design requires that all objects in the conceptual model be mapped to the specific constructs used by the selected database model.

21
Q

Physical design

A

Physical design is the process of determining the data storage organization and data access characteristics of the database to ensure its integrity, security, and performance. This is the last stage in the database design process.

22
Q

Clustered tables

A

The clustered tables storage technique stores related rows from two related tables in adjacent data blocks on disks. This ensures that the data are stored in sequentially adjacent locations, thereby reducing data access time and increasing system performance.

23
Q

Database rol

A

A database role is a set of database privileges that could be assigned as a unit to a user or group.

24
Q

Top-down design

A

Top-down design starts by identifying the data sets and then defines the data elements for each of those sets. This process involves the identification of different entity types and the definition of each entity’s attributes.

25
Q

Bottom-up design

A

Bottom-up design first identifies the data elements (items) and then groups them together in data sets. In other words, it first defines attributes, and then groups them to form entities.

26
Q

Centralized design

A

Centralized design is productive when the data component has a relatively small number of objects and procedures. The design can be carried out and represented in a fairly simple database. Centralized design is typical of relatively simple, small databases and can be successfully done by a single database administrator or by a small, informal design team.

27
Q

Decentralized design

A

Decentralized design might be used when the system’s data component has a considerable number of entities and complex relations on which very complex operations are performed. Decentralized design is also often used when the problem itself is spread across several operational sites and each element is a subset of the entire data set.