IST 210 Quiz 2
attribute
A characteristic of an entity or object. An attribute has a name and a data type
entity set
A collection of like entities.
relational database management system (RDBMS)
A collection of programs that manages a relational database. The RDBMS software translates a user's logical requests (queries) into commands that physically locate and retrieve the requested data.
entity relationship (ER) model (ERM)
A data model that describes relationships (1:1, 1:M, and M:N) among entities at the conceptual level with the help of ER diagrams. The model was developed by Peter Chen.
business rule
A description of a policy, procedure, or principle within an organization. For example, a pilot cannot be on duty for more than 10 hours during a 24-hour period, or a professor may teach up to four classes during a semester.
entity relationship diagram (ERD)
A diagram that depicts an entity relationship model's entities, attributes, and relations.
relational diagram
A graphical representation of a relational database's entities, the attributes within those entities, and the relationships among the entities.
table (relation)
A logical construct perceived to be a two-dimensional structure composed of intersecting rows (entities) and columns (attributes) that represents an entity set in the relational model
schema
A logical grouping of database objects, such as tables, indexes, views, and queries, that are related to each other.
entity
A person, place, thing, concept, or event for which data can be stored. See also attribute.
Crow's Foot notation
A representation of the entity relationship diagram that uses a three-pronged symbol to represent the "many" sides of the relationship.
data model
A representation, usually graphic, of a complex "real-world" data structure. Data models are used in the database design phase of the Database Life Cycle.
constraint
A restriction placed on data, usually expressed in the form of rules. For example, "A student's GPA must be between 0.00 and 4.00." Constraints are important because they help to ensure data integrity.
entity instance (entity occurrence)
A row in a relational table.
Model
Abstraction of a real-world object or event
relationship
An association between entities.
network model
An early data model that represented data as a collection of record types in 1:M relationships.
hierarchical model
An early database model whose basic concepts and characteristics formed the basis for subsequent database development. This model is based on an upside-down tree structure in which each record is called a segment. The top record is the root segment. Each segment has a 1:M relationship to the segment directly below it.
many-to-many (M:N or *..*) relationship
Association among two or more entities in which one occurrence of an entity is associated with many occurrences of a related entity and one occurrence of the related entity is associated with many occurrences of the first entity.
one-to-one (1:1 or 1..1) relationship
Associations among two or more entities that are used by data models. In a 1:1 relationship, one entity instance is associated with only one instance of the related entity.
one-to-many (1:M or 1..*) relationshi
Associations among two or more entities that are used by data models. In a 1:M relationship, one entity instance is associated with many instances of the related entity.
Object/Relational Database Management System (O/R DBMS)
Based on ERDM, focuses on better data management
Object-oriented database management system(OODBMS)
Based on OODM
Conceptual schema
Basis for the identification and high-level description of the main data objects Has a macro-level view of data environment Is software and hardware independent
Business Rules
Brief, precise, and unambiguous description of a policy, procedure, or principle Enable defining the basic building blocks Describe main and distinguishing characteristics of the data
Physical independence
Changes in physical model do not affect internal model
Logical independence
Changing internal model without affecting the conceptual model
Attribute
Characteristic of an entity
Class
Collection of similar objects with shared structure and behavior organized in a class hierarchy
Attribute
Columns
Sources of Business Rules
Company managers Policy makers Department managers Written documentation Direct interviews with end users
NoSQL - Disadvantages
Complex programming is required There is no relationship support There is no transaction integrity support In terms of data consistency, it provides an eventually consistent model
Schema
Conceptual organization of the entire database as viewed by the database administrator
Network Model - Advantages
Conceptual simplicity Handles more relationship types Data access is flexible Data owner/member relationship promotes data integrity Conformance to standards Includes data definition language (DDL) and data manipulation language (DML)
Object
Contains data and their relationships with operations that are performed on it Basic building block for autonomous structures Abstraction of real-world entity
Network Models
Created to represent complex data relationships effectively Improved database performance and imposed a database standard Allows a record to have more than one parent Depicts both one-to-many (1:M) and many-to-many (M:N) relationships
Attributes
Describe the properties of an object
Relationship
Describes an association among entities One-to-many (1:M) Many-to-many (M:N or M:M) One-to-one (1:1)
Unified Modeling Language (UML)
Describes sets of diagrams and symbols to graphically model a system
relational model
Developed by E. F. Codd of IBM in 1970, the relational model is based on mathematical set theory and represents data as independent relations. Each relation (table) is conceptually represented as a two-dimensional structure of intersecting rows and columns. The relations are related to each other through the sharing of common entity characteristics (values in columns).
Hierarchical Models
Developed to manage large amounts of data for complex manufacturing projects Represented by an upside-down tree which contains segments (equivalent of a file system's record type) Depicts a set of one-to-many (1:M) relationships
The External Model
End users' view of the data environment ER diagrams are used to represent the external views
SQL-Based Relational Database Application
End-user interface Allows end user to interact with the data Collection of tables stored in the database Each table is independent from another Rows in different tables are related based on common values in common attributes SQL engineExecutes all queries
Naming Conventions
Entity names - Required to: Be descriptive of the objects in the business environment Use terminology that is familiar to the users Attribute name - Required to be descriptive of the data represented by the attribute Proper naming: Facilitates communication between parties Promotes self-documentation
First - 1960s-1970s
File system VMS/VSAM Used mainly on IBM mainframe systems Managed records, not relationships
Big Data Aims to:
Find new and better ways to manage large amounts of web and sensor-generated data Provide high performance and scalability at a reasonable cost
The Entity Relationship Model
Graphical representation of entities and their relationships in a database structure
Big Data New Technologies
Hadoop Hadoop Distributed File System (HDFS) MapReduce NoSQL
Reasons for Identifying and Documenting Business Rules
Help standardize company's view of data Communications tool between users and designers Allow designer to: Understand the nature, role, scope of data, and business processes Develop appropriate relationship participation rules and constraints Create an accurate data model
Second - 1970s
Hierarchical and network IMS, ADABAS, IDS-II Early database systems Navigational access
NoSQL - Advantages
High scalability, availability, and fault tolerance are provided Uses low-cost commodity hardware Supports Big DataKey-value model improves storage efficiency
segment
In the hierarchical data model, the equivalent of a file system's record type.
tuple
In the relational model, a table row.
Data modeling
Iterative and progressive process of creating a specific data model for a determined problem domain
Emerging Models: NoSQL Early 2000s to present
Key-value store Column store SimpleDB (Amazon) BigTable (Google) Cassandra (Apache) MongoDB Riak Distributed, highly scalable High performance, fault tolerant Very large storage (petabytes) Suited for sparse data Proprietary application programming interface (API
Entity Relationship Model - Disadvantages
Limited constraint representation Limited relationship representation No data manipulation language Loss of information content occurs when attributes are removed from entities to avoid crowded displays
Extensible Markup Language (XML)
Manages unstructured data for efficient and effective exchange of all data types
Relation or table
Matrix composed of intersecting tuple and attribute
NoSQL Databases
Not based on the relational model Support distributed database architectures Provide high scalability, high availability, and fault tolerance Support large amounts of sparse data Geared toward performance rather than transaction consistency Store data in key-value stores
Translating Business Rules into Data Model Components
Nouns translate into entities Verbs translate into relationships among entities Relationships are bidirectional Questions to identify the relationship type How many instances of B are related to one instance of A?How many instances of A are related to one instance of B?
Inheritance
Object inherits methods and attributes of parent class
Fourth - Mid-1980s
Object-oriented Object/relational (O/R) Versant Objectivity/DB DB2 UDB Oracle 12c Object/relational supports object data types Star Schema support for data warehousing Web databases become common
The Physical Model
Operates at lowest level of abstraction Describes the way data are saved on storage media such as disks or tapes Requires the definition of physical storage and data access methods Relational model aimed at logical level Does not require physical-level details
Relational Database Management System (RDBMS)
Performs basic functions provided by the hierarchical and network DBMS systems Makes the relational data model easier to understand and implement Hides the complexities of the relational model from the use
Subschema
Portion of the database seen by the application programs that produce the desired information from the data within the database
The Relational Model
Produced an automatic transmission database that replaced standard transmission databases
Hierarchical Model - Advantages
Promotes data sharing Parent/child relationship promotes conceptual simplicity and data integrity Database security is provided and enforced by DBMS Efficient with 1:M relationships
Third - Mid-1970s
Relational DB2 Oracle MS SQL Server MySQL Conceptual simplicity Entity relationship (ER) modeling and support for relational data modeling
The Internal Model
Representing database as seen by the DBMS mapping conceptual model to the DBMS
The Conceptual Model
Represents a global view of the entire database by the entire organization
Hierarchical Model - Disadvantages
Requires knowledge of physical data storage characteristics Navigational system requires knowledge of hierarchical path Changes in structure require changes in all application programs Implementation limitations No data definition Lack of standards
Relational Model - Disadvantages
Requires substantial hardware and system software overhead Conceptual simplicity gives untrained people the tools to use a good system poorly May promote information problems
Class hierarchy
Resembles an upside-down tree in which each class has only one parent
Tuple
Rows
Entity instance or entity occurrence
Rows in the relational table
Chen notation
See entity relationship (ER) model
Object-Oriented Model - Advantages
Semantic content is added Visual representation includes semantic content Inheritance promotes data integrity
Constraint
Set of rules to ensure data integrity
Data models
Simple representations of complex real-world data structuresUseful for supporting a specific problem domain
Object-Oriented Model - Disadvantages
Slow development of standards caused vendors to supply their own enhancements Compromised widely accepted standard Complex navigational system Learning curve is steep High system overhead slows transactions
External schema
Specific representation of an external view
Internal schema
Specific representation of an internal model Uses the database constructs supported by the chosen database Is software dependent and hardware independent
Relational Model - Advantages
Structural independence is promoted using independent tables Tabular view improves conceptual simplicity Ad hoc query capability is based on SQL Isolates the end user from physical-level details Improves implementation and management simplicity
Extended relational data model (ERDM)
Supports OO features and complex data representation
Network Model - Disadvantages
System complexity limits efficiency Navigational system yields complex implementation, application development, and management Structural changes require changes in all application programs
Logical design
Task of creating a conceptual data model
Connectivity
Term used to label the relationship types
data definition language (DDL
The language that allows a database administrator to define the database structure, schema, and subschema.
subschema
The portion of the database that interacts with application programs.
data modeling
The process of creating a specific data model for a determined problem domain.
data manipulation language (DML)
The set of commands that allows an end user to manipulate the data in the database, such as SELECT, INSERT, UPDATE, DELETE, COMMIT, and ROLLBACK.
class diagram notation
The set of symbols used in the creation of class diagrams.
connectivity
The type of relationship between entities. Classifications include 1:1, 1:M, and M:N.
Entity
Unique and distinct object used to collect and store data
Entity relationship diagram (ERD)
Uses graphic representations to model database components
Entity Relationship Model - Advantages
Visual modeling yields conceptual simplicity Visual representation makes it an effective communication tool Is integrated with the dominant relational model
Characteristics
Volume Velocity Variety
Big Data Challenges
Volume does not allow the usage of conventional structures Expensive OLAP tools proved inconsistent dealing with unstructured data
Fifth - Mid-1990s
XML Hybrid DBMS dbXML Tamino DB2 UDB Oracle 12c MS SQL Server Unstructured data support O/R model supports XML documents Hybrid DBMS adds object front end to relational databases Support large databases (terabyte size)
Customer and invoice
are objects of interest for the environment and should be represented by their respective entities.
