CIT 381 Chapter 2, Database Systems: Design, Implementation, and
Management
1. 3 Vs: Three basic characteristics of Big Data databases: volume, velocity, and variety.
2. American National Standards Institute(ANSI): A group that accepted the DBTG recommenda-
tions and augmented database standards in 1975 through its SPARC committee.
3. Attribute: A characteristic of an entity or object. An attribute has a name and data type.
4. 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.
5. 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.
6. Chen Notation: See entity relation (ER) model.
7. Class: A collection of similar objects with shared structure (attributes) and behavior (methods). A class encapsu-
lates an object's data representation and a method's implementation. Classes are organized in a class hierarchy.
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, 8. Class Diagram: A diagram used to represent data and their relationship in UML object notation.
9. Class Diagram Notation: The set of symbols used in the creation of class diagrams in UML object
modeling.
10. Class Hierarchy: The organization of classes in a hierarchical tree in which each parent class is a superclass
and each child class is a subclass. See also, inheritance.
11. Client Node: One of three types of nodes used in the Hadoop Distributed File System (HDFS). The client node
acts as the interface between the user application and HDFS. See also Name Node and Data Node.
12. Conceptual Model: The output of the conceptual design process. The conceptual model provides a global
view o an entire database and describes the main data objects, voiding details.
13. Conceptual Schema: A representation of the conceptual model, usually expressed graphically. See also
Conceptual Model.
14. Connectivity: The type of relationship between intities. Classifications include 1:1, 1:M and M:N.
15. Constraint: A restriction placed on data, usually expressed in the form of rules. For example, "A student's GPA
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Management
1. 3 Vs: Three basic characteristics of Big Data databases: volume, velocity, and variety.
2. American National Standards Institute(ANSI): A group that accepted the DBTG recommenda-
tions and augmented database standards in 1975 through its SPARC committee.
3. Attribute: A characteristic of an entity or object. An attribute has a name and data type.
4. 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.
5. 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.
6. Chen Notation: See entity relation (ER) model.
7. Class: A collection of similar objects with shared structure (attributes) and behavior (methods). A class encapsu-
lates an object's data representation and a method's implementation. Classes are organized in a class hierarchy.
1/5
, 8. Class Diagram: A diagram used to represent data and their relationship in UML object notation.
9. Class Diagram Notation: The set of symbols used in the creation of class diagrams in UML object
modeling.
10. Class Hierarchy: The organization of classes in a hierarchical tree in which each parent class is a superclass
and each child class is a subclass. See also, inheritance.
11. Client Node: One of three types of nodes used in the Hadoop Distributed File System (HDFS). The client node
acts as the interface between the user application and HDFS. See also Name Node and Data Node.
12. Conceptual Model: The output of the conceptual design process. The conceptual model provides a global
view o an entire database and describes the main data objects, voiding details.
13. Conceptual Schema: A representation of the conceptual model, usually expressed graphically. See also
Conceptual Model.
14. Connectivity: The type of relationship between intities. Classifications include 1:1, 1:M and M:N.
15. Constraint: A restriction placed on data, usually expressed in the form of rules. For example, "A student's GPA
2/5
