BMGT 402 Midterm
First Normal Form (1NF)
- All key attributes are defined - There are no repeating groups in the relation - All attributes are dependent on the primary key
Network Model
- Created to represent complex data relationships more effectively - Resembles hierarchical model, but allows a record to have more than one parent - Disadvantages: cumbersome, structural dependence, lack of ad hoc query capability placed burden on programmers to generate code for reports
DBMS Functions
- Data Dictionary Management - Data Storage Management - Data Transformation and Presentation - Security Management - Multiuser Access Control - Backup and Recovery Management - Data Integrity Management - Database Access Languages and Application Programming Interfaces - Database Communication Interfaces
Relational Model
- Developed by E. F. Codd (IBM) in 1970 - Model foundation is a mathematical concept known as a relation (or table)
DBMS Advantages
- Enables data to be shared - Presents the end user with an integrated view of data - Provides more efficient and effective data management - Improves sharing, security, integration, access, decision-making, productivity, etc.
DBMS Disadvantages
- Increased Costs - Management Complexity - Maintaining Currency - Vendor Dependence - Frequent Update/Replacement Cycles
Hierarchical Model
- The first data model (1960) - Basic logical structure is represented by an upside-down "tree" - Disadvantages: complex to implement, difficult to manage, lacks structural independence, no standards
Structural Dependence
-Access to a file is dependent on its own structure -All file system programs are modified to conform to a new file structure
Extended Relational Data Model (ERDM)
-Includes many of OO model's best features (e.g. inheritance) -Also often described as an object/relational database management system (O/R DBMS) -Primarily geared to business applications
Database Management System (DBMS)
-Is a collection of programs that manages the database structure -Controls access to data stored in the database -Acts as the intermediary between the user and the database
Second Normal Form (2NF)
-The relation is already in first normal form (1NF) -The relation contains no partial dependencies •If a relation has a single attribute as the primary key, it is automatically in 2NF if it is in 1NF
Third Normal Form (3NF)
-The relation is already in second normal form (2NF) -The relation contains no transitive dependencies
Determinant
A -> B A is known as the ______.
Dependent
A -> B B is known as the ______.
Business Rule
A brief, precise, and unambiguous description of a policy, procedure, or principle
Field
A character or group of characters (alphabetic or numeric) that has a specific meaning; used to define data
Attribute
A characteristic of an entity
Update Anomaly
A circumstance in which redundant data in a relation may not be properly updated.
Relational Database
A collection of normalized relations with distinct relation names
File
A collection of related records
Operational Database
A database is designed to support an organization's daily operations
Normalization
A design process for evaluating and correcting data structures to reduce data anomalies
System Catalog
A detailed system data dictionary that describes all objects in a database
NoSQL (Not Only SQL)
A distributed database system that efficiently stores structured and unstructured data
Partial Dependency
A functional dependency in which an attribute is dependent on only a portion (subset) of the primary key (only occurs when the primary key is a composite key)
Transitive Dependency
A functional dependency in which an attribute not part of the primary key is dependent on another attribute that is not part of the primary key
Natural Key (or Natural Identifier)
A generally accepted identifier for real world objects
Entity Relationship Diagram (ERD)
A graphical representation to model database components: -Entity instances (or entity occurrences) describe rows in the relational table -Attributes describe particular characteristics -Connectivity describes the relationship classification between entities (i.e. 1:1, 1:M, M:N)
Repeating Group
A group of multiple entries of the same or multiple types of a single key attribute occurrence
Composite Key
A key consists of two or more attributes
Record
A logically connected set of one or more fields that describes a person, place, or thing
Relation
A matrix (table) consisting of row/column intersections
Big Data
A movement to find new and better ways to manage large amounts of web-generated data and derive business insight from it, while simultaneously providing high performance and scalability at a reasonable cost.
Attribute
A named column of a relation
Entity
A person, place, thing, idea, or event about which data will be collected and stored
Design Trap
A problem that occurs when a relationship is improperly or incompletely identified and therefore is represented in a way that is not consistent with the real world.
Recursive Relationship
A relationship that is found within a single entity type. For example, an EMPLOYEE is married to an EMPLOYEE or a PART is a component of another PART.
Dependency Diagram
A representation of all data dependencies (e.g. full functional, partial, and transitive)
Constraint
A restriction placed on data
Relational Database Schema
A set of all relation schemas for the database
Database
A shared, integrated computer structure that stores data
Data Model
A simple representation of a complex, real-world data structures (often graphical)
Primary Key
A single attribute or combination of attributes that: -Uniquely identifies each entity instance -Guarantees entity integrity -Works with foreign keys to implement relationships
Derived Attribute
A value may be calculated from other attributes
Model
An abstraction of a more complex real-world object or event
Relationship
An association between entities
Ternary Relationship
An association is maintained between three entities
Binary Relationship
An association is maintained between two entities
Unary Relationship
An association is maintained within a single entity
Composite Attribute
An attribute that can be further subdivided to yield additional attributes. For example, a phone number such as 615-898-2368 may be divided into an area code (615), an exchange number (898), and a four-digit code (2368).
Atomic Attribute
An attribute that cannot be further subdivided to produce meaningful components
Composite Entity
An entity created as a bridge between the two entities (also known as associative entity or bridge entity)
Hadoop
An open-source framework, built in Java, to store and process data
Simple Attribute
Attribute that cannot be subdivided
Multi-valued Attributes
Can have many values (not allowed in relational models)
Business Intelligence
Captures and processes business data to generate information to support decision making
Entity Occurrence (Entity Instance)
Corresponds to a row in relational environment
Cloud Database
Created and maintained using cloud data services that provide defined performance measures for the database
Metadata
Data about data, through which the end-user data is integrated and managed
Data Dependence
Data access changes when data storage characteristics change
Data independence
Data storage characteristics are changed without affecting the program's ability to access the data
Unstructured Data
Data that exist in their original, raw state; that is, in the format in which they were collected
Structured Data
Data that has been processed
Semistructured Data
Data that has been processed to some extent
Time-variant Data
Data whose values are a function of time
Deletion Anomaly
Deleting rows may cause a loss of data that would be needed for other future rows
Normal forms
Denote standardized structures meeting specific characteristics
Connectivity
Describes the relationship classification -1:1, 1:N, or M:N
Distributed Database
Distributes the database across different sites
Participants
Entities within a relationship are called _____
Existence Independence
Entity can exist apart from one or more related entities
Existence Dependence
Entity exists in database only when it is associated with another related entity occurrence
Strong (or Identifying) Relationship
Exists when the primary key of the related entity does contain a primary key component of the parent entity; represented with a solid line
Weak (or Non-Identifying) Relationship
Exists when the primary key of the related entity does not contain a primary key component of the parent entity; represented with a dashed line
Cardinality
Expresses minimum and maximum number of entity occurrences associated with one occurrence of related entity
Structural Independence
File structure is changed without affecting the application's ability to access the data
Weak Entity
Fulfills two criteria: -Existence-dependent (associated with another related entity occurrence) -Primary key partially or totally derived from parent entity in relationship
Relational Schema
Graphical representation of relations, attributes, and relationships
Single-value Attribute
Holds a single value for each occurrence of an entity type
General-purpose Database
Holds a wide variety of data used in multiple disciplines
Centralized Database
Holds data at a single site
Discipline-specific Database
Holds data focused on specific subject areas
Data Warehouse
Holds data in a format optimized for decision support
Principle of Determination
If you know the value of attribute(s) A, you can determine the value of attribute(s) B
Optional Participation
In ER modeling, a condition in which one entity occurrence does not require a corresponding entity occurrence in a particular relationship; occurs when the minimum cardinality is 0
Relationship Degree
Indicates the number of entities or participants associated with a relationship
Workgroup Database
Multiuser Database; Supports a small number of users or a single department
Enterprise Database
Multiuser Database; Supports many users across many departments
Insertion Anomaly
Occurs when certain attributes cannot be inserted into the database without the presence of other attributes
Data Anomaly
Occurs when not all required changes in redundant data are made successfully
Fan Trap
Occurs when one entity is in two 1:M relationships, as the "1" side, to other entities
Redundant Relationship
Occurs when there are multiple relationship paths between related entities
Mandatory Participation
One entity occurrence requires a corresponding entity occurrence in a particular relationship; occurs when minimum cardinality is 1
Functional Dependency
One or more attributes determines one or more other attributes
Key
One or more attributes that determine other attributes
Identifiers (primary keys)
One or more attributes that uniquely identify each entity instance
Physical Model
Operates at the lowest level of abstraction, describing the way data are saved on storage media such as magnetic, solid-state, or optical media
Database System Environment
Organization of components that define and regulate the collection, storage, management, and use of data in a system, including: -Hardware -Software -People -Procedures -Data
Composite Identifier
Primary key composed of more than one attribute
End-user Data
Raw facts of interest to end user
Data
Raw facts, such as a telephone number, a birth date, a customer name, and a year-to-date (YTD) sales value
Variety
Refers to the idea of the multiple formats of source data
Volume
Refers to the large amount of data being stored
Velocity
Refers to the speed at which data grows and at which it must be processed to gain insights
Logical Design
Refers to the task of creating a conceptual model
Conceptual Model
Represents a global view of the entire database by the entire organization
Internal Model
Represents the database as "seen" by DBMS
External Model
Represents the end users' view of the data environment
Tuple
Row of a relation
Data Dictionary
Stores definitions of data elements and their relationships (stores metadata)
Multiuser Database
Supports multiple users at the same time
Single-user Database
Supports one user at a time
Performance
The higher the normal form, the fewer the data redundancies and inconsistencies, but the decreased ______.
Granularity
The level of detail represented by the values stored in a table's row
Degree
The number of attributes in a relation
Cardinality
The number of tuples in a relation
Domain
The set of allowable values for one or more attributes
Online Analytical Processing (OLAP)
Tools can be used to retrieve, process, and model data within the data warehouse
Logical Independence
When changes in the internal model do not impact the conceptual model
Physical Independence
When changes in the physical model do not impact the internal model
Denormalization
a design process by which a relation is changed from a higher-level normal form to a lower-level normal form
Relation Schema
a named relation followed by the attribute names in parentheses Examples (note the primary key is bold + underlined and the foreign key is italicized): •Branch(branchNo, street, city, postcode) •Staff(staffNo, fName, lName, position, sex, DOB, salary, branchNo)