Exam 1-Chapter 2 Flashcards
Model
An abstraction of a real-world object or event; useful in understanding complexities of the real world environment
Data Models
Relatively simple representations of complex real-world data structures (often graphical); data modeling is iterative and progressive)
Importance of Data Models
Facilitate interaction among the designer, the applications programmer, and the end user
End users have different views and needs for data
Data model organizes data for various users
Data model is an abstraction (cannot draw required data out of the data model)
Entity
Anything about which data are to be collected and stored
Attribute
Describes an association among entities
One-to-many (1:M) relationship
Many-to-many (M:N or M:M) relationship
One-to-one (1:1) relationship
Constraint
A restriction placed on the data
Business Rules
Descriptions of policies, procedures, or principles within a specific organization (apply to any organization that stores and used data to generate information); Description of operations to create/enforce actions within an organization’s environment (must be in writing and kept up to date;must be easy to understand and widely disseminated);describe characteristics of data as viewed by the company
Sources of Business Rules
Company managers Policy makers department managers Written documentation (procedures;standards; operations manuals) Direct interviews with end users
Importance of Documenting Business Rules
- Standardize company’s views of data
- Communications tool between users and designers
- Allow designer to understand the nature, role, and scope of data
- Allow designer to understand business processes
- Allow designer to understand business processes
- Allow designer to develop appropriate relationship participation rules and constraints
The Hierarchical Model
The hierarchical model was developed in the 1960s to manage large amounts of data for manufacturing projects
Basic logical structure is represented by an upside-down “tree” with levels or segments
Higher layer=parent
Lower layer=child
1:1, 1:M
Network Model
The network model was created to represent complex data relationships more effectively than the hierarchical model (improves database performance)
Network database=collection of records in 1:M and M:M relationships
Owner
Equivalent to the hierarchical model’s parent
Member
Equivalent to the hierarchical model’s child
Schema
Conceptual organization of entire database as viewed by the database administrator
Subschema
Database portion “seen” by the application programs
Data Management Language (DML)
Defines the environment in which data can be managed
Data Definition Language (DDL)
Enables the administrator to define the schema components
Disadvantages of the Network Model
Became too cumbersome for larger, more complex data sets
Lack of ad hoc query capability placed burden on programmers to generate code for reports
Structural change in the database could produce havoc in all application programs
Relational Database Management System (RDBMS)
Hides complexity from the user by managing all the physical details and allowing the user to work at the logical level
How the data is physically stored in the database is of no concern to the user or the designer
Relational table stores collection of related entities
Tables are related through common attributes
Relational Diagram
Representation of entities, attributes, and relationships
Entity Relationship Model
Graphical representation of entities and their relationships in a database structure
Entity is represented in ERD by a rectangle
Mapped to a relational type
Entity Relationship Diagram (ERD)
Uses graphic representations to model database components
Entity is mapped to a relational table
Chen Notation
Relationships are represented by a diamond with the relationship name written inside it
Connectivities written next to entity boxes
Crow’s Foot Notation
Connectivities represented by symbols
Object-Oriented (OO) Model
OODM (Object-Oriented Data Model) is the basis for OODBMS
Both data and relationships are contained in a single structure known as an object
An object also contains all operations that can be performed on it
Classes
Objects that share similar characteristics (attributes and methods) Organized in a class hierarchy
Inheritance
Object inherits methods and attributes or parent class
Unified Modeling Language (UML)
Based on OO concepts that describe diagrams and symbols (used to graphically model a system, UML class diagrams used to represent data and relationships
Extended Relational Data Model (ERDM)
Semantic data model developed in response to increasing complexity of applications
Includes many of OO model’s best features
Often described as an object/relational database management system (O/RDBMS)
Primarily geared to business applications
Extensible Markup Language (XML)
The Internet revolution created the potential to exchange critical business information
Emerged as the de facto standard
Current databases support XML (XML: the standard protocol for data exchange among systems and Internet services
Big Data
- Find new and better ways to manage large amounts of Web-generated data and derive business insight from it
- Simultaneously provides high performance and scalability at a reasonable cost
- Relational approach does not always match the needs of organizations with Big Data Challenges
NoSQL Databases
- Not based on the relational model, hence the name NoSQL
- Supports distributed database architectures
- Provides high scalability, high availability, and fault tolerance
- Supports very large amounts of sparse data (number of attributes is very large; number of actual data instances is low)
- Geared toward performance rather than transaction consistency
External Schema
Specific representation of an external view, Includes:
- Entities
- Relationships
- Processes
- Constraints
The Conceptual Model
Represents global view of the entire database
All external views integrated into single global view: conceptual model or schema
-ERD graphically represents the conceptual schema (logical model)
-Provides a relatively easily understood macro level view of data environment
-Independent of both software and hardware
THey Physical Model
- Operates at lowest level of abstraction
- Requires the definition of physical storage and data access methods
- Physical independence: when changes in physical model do not affect internal model
