Database
Content
Database
Data Hierarchy
Bit 0/1. Byte 8 bits. Single Character, a letter. Field Group of characters into words (Student s name) Record Group of related fields. (Student s name, course taken, grade). ± File Group of related records. ± Database Grouping of related files.
± ± ± ±
Storing and Accessing Records
± Records stored in secondary storage, and arrangement determines manner they are accessed. ± Sequential Access Method: data records are retrieved in same physical sequence in which they are stored.
Database
Storing and Accessing Records
± Direct or random access method: data can be retrieved in any sequence, without regard to actual physical order on storage medium.
± Magnetic tape uses sequential access. Magnetic Disk uses direct access.
File Management Environment.
± Registrar s office Class Programs Class File. ± Accounting office Accounts Programs Account File. ± Athletics Sports Programs Sports File.
Database
Disadvantage with File Approach
± ± ± ± ± ±
Data redundancy Data inconsistency Data isolation Data integrity Security Application/Data dependence.
Database
is logical group of related fields, eliminates the problem associated with traditional file environment. Data is integrated and related so one set of S/W (DBMS) accesses to all data.
Database
Data Models
Hierarchical model Network Model Relational Model
± Hierarchical Model
± Structures data into an inverted tree. ± A hierarchical database consists of a collection of records which are connected to one another through links. ± Record types are organized in the form of a rooted tree. » No cycles in the underlying graph. » Relationships formed in the graph must be such that only one-to-many or one-to-one relationships exist between a parent and a child.
Hierarchical Model
± Network Model
± Relationships formed in the graph can be many-to-many between a parent and a child.
Database
Data Models
± Relational Model
± Based on simple concept of tables ( rows and columns). ± Tables are called relations and Model is based o mathematical theory of sets and relation. ± Each row is equivalent to record (tuple) and each column is equivalent to field (attribute).
Principles
1. 2. 3. 4. Order of tuple or attribute is irrelevant. Each tuple must be uniquely identifiable. Each table must have unique identifier. A cell contains one value.
Database
Data Models
± Relational Model
Basic Operations± ± ±
Select Join project.
DATA WAREHOUSE and DATA MINING
Relational or Multidimensional database management system designed to support management decision making. Oriented around major business subjects.(customer, product, vendor or activity) Current Data and Historical Data.
Database
DATA MARTS
Scaled down version of Data warehouse that focuses on particular subject area. Designed to support unique business requirement of a specific department or business process. Less time to build, costs less, and less complex than an enterprise data warehouse.
DATA MINING
Provides a means of extracting previously unknown, predictive information from base of accessible data in data warehouse. Uses tools to discover hidden patterns, correlations, and relationship among organizational data. Predicting future trends and behaviors, allowing business to make proactive, knowledge driven decisions.
Data Hierarchy
Bit 0/1. Byte 8 bits. Single Character, a letter. Field Group of characters into words (Student s name) Record Group of related fields. (Student s name, course taken, grade). ± File Group of related records. ± Database Grouping of related files.
± ± ± ±
Storing and Accessing Records
± Records stored in secondary storage, and arrangement determines manner they are accessed. ± Sequential Access Method: data records are retrieved in same physical sequence in which they are stored.
Database
Storing and Accessing Records
± Direct or random access method: data can be retrieved in any sequence, without regard to actual physical order on storage medium.
± Magnetic tape uses sequential access. Magnetic Disk uses direct access.
File Management Environment.
± Registrar s office Class Programs Class File. ± Accounting office Accounts Programs Account File. ± Athletics Sports Programs Sports File.
Database
Disadvantage with File Approach
± ± ± ± ± ±
Data redundancy Data inconsistency Data isolation Data integrity Security Application/Data dependence.
Database
is logical group of related fields, eliminates the problem associated with traditional file environment. Data is integrated and related so one set of S/W (DBMS) accesses to all data.
Database
Data Models
Hierarchical model Network Model Relational Model
± Hierarchical Model
± Structures data into an inverted tree. ± A hierarchical database consists of a collection of records which are connected to one another through links. ± Record types are organized in the form of a rooted tree. » No cycles in the underlying graph. » Relationships formed in the graph must be such that only one-to-many or one-to-one relationships exist between a parent and a child.
Hierarchical Model
± Network Model
± Relationships formed in the graph can be many-to-many between a parent and a child.
Database
Data Models
± Relational Model
± Based on simple concept of tables ( rows and columns). ± Tables are called relations and Model is based o mathematical theory of sets and relation. ± Each row is equivalent to record (tuple) and each column is equivalent to field (attribute).
Principles
1. 2. 3. 4. Order of tuple or attribute is irrelevant. Each tuple must be uniquely identifiable. Each table must have unique identifier. A cell contains one value.
Database
Data Models
± Relational Model
Basic Operations± ± ±
Select Join project.
DATA WAREHOUSE and DATA MINING
Relational or Multidimensional database management system designed to support management decision making. Oriented around major business subjects.(customer, product, vendor or activity) Current Data and Historical Data.
Database
DATA MARTS
Scaled down version of Data warehouse that focuses on particular subject area. Designed to support unique business requirement of a specific department or business process. Less time to build, costs less, and less complex than an enterprise data warehouse.
DATA MINING
Provides a means of extracting previously unknown, predictive information from base of accessible data in data warehouse. Uses tools to discover hidden patterns, correlations, and relationship among organizational data. Predicting future trends and behaviors, allowing business to make proactive, knowledge driven decisions.
