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HI632_Modern Database Management 12 e Chapter 1

Associative entity
An entity type that associates the instance of one or more entity types and contains attributes that are preculiar to the relationship between those entity instances
Attribute
“A property or characteristic of an entity or relationship type that is of interest to the organization.
Attribute
Required vs Optional
Attribute
Simple vs Composite
Attribute
Single-valued vs multivalued
Attribute
Stored vs derived
Binary relationship
A relationship between the instances of two entity types
Business Rule
“A statement that defines or constrains some aspect of the business. IT is intended to assert businessstructure or to control or influence the behavior of a business
A business rules approach is based on the following premises:
1. They are a core concept in an enterprise because they are an expression of the business policy and guide individual and aggregrate behavior. (Well-structured business rules can be stated in natural language for end users and in a database model for system developers)
A business rules approach is based on the following premises:
2.They can be expressed in terms that are familiar to end users. Thus, users can define and then maintain their own rules.
A business rules approach is based on the following premises:
3. They are highly maintainable. They are stored in a central repository and each rule is expressed on ly once, then shared throughout the organization. Each rule is discovered and documented only once, to be applied in all systems development projects
A business rules approach is based on the following premises:
4. Enforcement of them can be automated through the use of software that can interpret the rules and enforce them using the integrity mechanisms of the dbms”
Characteristics of a good business rule
“1. Declarative
Characteristics of a good business rule
2.Precise
Characteristics of a good business rule
3. Atomic
Characteristics of a good business rule
4. Consistent
Characteristics of a good business rule
5. Expressible
Characteristics of a good business rule
6. Distinct
Characteristics of a good business rule
7. Business-Oriented “
Cardinality constraint
a rule that specifies the number of instances of one entity that can (or must) be associated with each instance of another entity
Composite attribute
An attribute that has meaningful components (attributes)
Composite identifier
An identifiers that consists of an composite attribute
Degree
The number of entity types that participate in a relationship
Derived attribute
An attribute whose values can be calcualted from related attribute values
entity
A person, place, object, event, or concept in the user environment about which the orgnaization wishes to maintain data (Such as Customer, Employee, Product, etc…)
entity instance
A single occurrence of an entity type
Entity Relationship Diagram (ERD)
A graphical representation of an entity-relationship model
Entity Relationship Model (ER Model)
A logical representation of the data for an organization or for a buisness area, using entities for categories of data and relationships for associations between entities
Entity Type
Collection of entities that share common properties or characterisitics
Fact
An association between two or more terms
Identifier
An attribute (or combination of attributes) whose value distinguishes instances of an entity type
Indentifying owner
The entity type on which the weak entity type depends
Indetifying relationship
The relationship between a week entity type and its owner
Maximum Cardinality
The maximum number of instances of one entity that may be assoicated with each instance of another entity
Minimum Cardinality
The minimum number of instances of one entity that may be associated with each instance of another entity
Multivalued Attributes
An attribute that may take on more than one value for a given entity (or relationship) instance
Optional Attribute
An attribute that may not have a value for every entity (or relationship) instance with which it is associated
Relationship Type
A meaningful association between or among entity types
Relationship Instance
An association between or amoung entity instances where each relationship instance associates exactly one entity instance from each particiapting entity type
Required Attribute
An attribute that must have a value for every entity (or relationship) instance with which it is associated
Simple (or atomic) attribute
An attribute that cannot be broken down into smaller componens that are meaningful to the organization
Strong Entity Type
An entity that exists independently of other entity types
Term
A word or phrase that has a specific meaning for the business
Ternary relationship
A simultaneous relationships among the instances of three entity types
Time Stamp
Time value associated with a data value, often indicating when some event occurred that affected the data value
Unary Relationship
A relationship between instances of a single entity type
Weak Entity Type
An entity whose existence depends on some other entity type
Data Names should be:
“1. Relate to Business, not technical
Data Names should be:
2. Be meaningful
Data Names should be:
3. Be unique
Data Names should be:
4. Be readable
Data Names should be:
5. Be composed of words taken from an approved list
Data Names should be:
6. Be repeatable
Data Names should be:
Follow a standard syntax
Guidelines for Good Data Definitions
“1. Definitions are gathered from the same sources as all requirements for information systems. Thus the systems and the data analysts should be looking for data objects and their definitions as these sources of information systems requiresments are studied
Guidelines for Good Data Definitions
2. Definitions will usually be accompanies by diagrams, such as ERD
Guidelines for Good Data Definitions
3. Definitions will be stated in the singular and explain what the data element i, not what it is not. A definiion will use commonly understood terms an abbrevs and stand alon e in its meaning and not embed other definitions within it. It should be consices and concentrate on the essential meaning of hte data, but it may also state such charcters of the data object, such as examples or subtleties”
Agile Software Development
An approact to db and software development that emphasizes “Individuals an interactions over processes and tools, working software over comprehensive documentaiton, customer collaboration over contract negotiation, and response to change over following a plan”
Conceptual Schema
A detailed technology-independent specification of the overall structure of organizational data
Constraint
A rule that cannot be violated by db users
Data
Stored representations of objects and events that have meaning and inportance in the user’s environment
Data Independence
The sparatation of data descriptions from the application programs that use the data
Data Model
Graphical Systems used to capture the nature and relationships among data
Data Modeling and Design Tools
Software tools that provdie automated support for creating data models
Data Warehouse
An integrated decision support database whose content is derived from the various operational databases
Database
An organized collection of logically related data
Database application
An application program (or set of related programs) that is used to perform a series of database activities (create, read, update, and delete) on behalf of the db users.
Database Management system (DBMS)
A software system that is used to create, maintain, and provide controlled access to user database
Enterprise Data Modeling
The first step in db development, in which the scope and general contents of organizational dbs are specified
Enterprise resource planning (ERP)
A business mgmt system that integrates all functions of the enterprise. ERP systems are software applications that provide the data necessary
Information
Data that have been procesed in such a way as to increase the knowledge of the person who uses the data
Logical Schema
The representation of a database for a particular data mgmt technology
Physical Schema
Specifications for how data from a logical schema are stored in a computer’s 2ndary memory by a dbms
Project
A planned undertaking of related activities to reach an objective that has a beginning and an end
Prototyping
An iterative process of systems development in which requirements are converted to a working system that is continually revised through close work between analysts and users
Relational Database
A db that represents data as a colleciton of tables in which all data relationships are represented by common values in related tables
Repository
A centralized knowledge base of all data definitions, data relationships, screen and report formats, and other system components
Systems Development Life Cycle (SDLC)
The traditional methodology used to develop, maintain, and replace information systems
User View
A logical description of some portion of the database that is required by a user to perform some task
Client Server Architecture
Enterprise Data Modeling
Done during the Planning Stage of the SDLC
Enterprise Data Modeling
Analyze current data processing
Enterprise Data Modeling
Analyze the general business functions and their db needs
Enterprise Data Modeling
Justify need for new data and dbs in support of business
Conceptual Data Modelling
Done during the Planning and Analysis Stage of the SDLC
Conceptual Data Modelling
Identify scope of db rqmts for proposed insys
Conceptual Data Modelling
Analyze overall data rqmts for business function(s) supported by the db
Logical Data Model
Physical Data Model
Disadvantages of File Processing Systems
Program-data dependence
Disadvantages of File Processing Systems
Duplication of data
Disadvantages of File Processing Systems
Limited Data Sharing
Disadvantages of File Processing Systems
Lengthy development times
Disadvantages of File Processing Systems
Excessive program maintenance
Advantages of the Database approach
Program-data independence
Advantages of the Database approach
Planned Data Redundancy
Advantages of the Database approach
Improved Data Consistency
Advantages of the Database approach
Improved Data Sharing
Advantages of the Database approach
Increased productivity of application development
Advantages of the Database approach
Enforcement of Standards
Advantages of the Database approach
Improved Data Quality
Advantages of the Database approach
Improved Data Accessbility and Responsiveness
Advantages of the Database approach
Reduced Program Maintenance
Advantages of the Database approach
Improved decision support
Costs and Risks of the database approach
New, specialized personnel
Costs and Risks of the database approach
Installations and managmenet cost and complexity
Costs and Risks of the database approach
Conversion Costs
Costs and Risks of the database approach
Need for explicit backup and recovery
Costs and Risks of the database approach
Organizational Conflict
Components of a database environment
Database modeling and tools
Components of a database environment
Repository
Components of a database environment
DBMS
Components of a database environment
Database
Components of a database environment
Application Programs
Components of a database environment
User Interface
Components of a database environment
Data and db administrators
Components of a database environment
System developers
Components of a database environment
End Users

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