Database Structures

Database Structures

• Common database structures include: Hierarchical, Network, Relational, Object-oriented, and Multi-dimensional

Hierarchical Structure

• Early DBMS structure
• Records arranged in a tree-like structure
• Relationships are one-to-many

Network Structure

• Used in some mainframe DBMS packages
• Many-to-many relationships are possible

Relational Structure

• Most widely used structure
• Data elements are stored in tables
• Row represents a record; column is a field
• Can relate data in one file with data in another, if both files share a common data element
• Relational Operations:
  • Select: create a subset of records that meet a stated criterion
  • Join: combine two or more tables temporarily
  • Project: create a subset of columns in a table

Multidimensional Structure

• A multidimensional database is created from multiple relational databases
• Variation of relational model
• Uses multidimensional structures to organize data
• Data elements are viewed as being in cubes
• Popular for analytical databases that support Online Analytical Processing (OLAP)

Object-Oriented Structure

• An object consists of:
  • Data values describing the attributes of an entity
  • Operations that can be performed on the data
• Encapsulation: combine data and operations
• Inheritance: new objects can be created by replicating some or all of the characteristics of parent objects
• Used in object-oriented database management systems (OODBMS)
• Supports complex data types more efficiently than relational databases (e.g. graphic images, video clips, web pages)

Evaluation of Database Structures

• Hierarchical:
  • Works for structured, routine transactions
  • Can’t handle many-to-many relationships
• Network:
  • More flexible than hierarchical
  • Unable to handle ad hoc requests
• Relational:
  • Easily responds to ad hoc requests
  • Easier to work with and maintain
  • Not as efficient/quick as hierarchical or network

Database DevelopmentRoles

• A Database Administrator (DBA) is in charge of enterprise database development, improving the integrity and security of organizational databases.

Database Development Tasks

• Uses Data Definition Language (DDL) to develop and specify data contents, relationships, and structure.
• Stores data specifications in a data dictionary or a metadata repository.

Data Dictionary

• A data dictionary contains data about data (metadata) and relies on specialized software to manage a database of data definitions.
• It contains information on:
  • Names and descriptions of all types of data records and their interrelationships.
  • End users’ access and use requirements for application programs.
  • Database maintenance.
  • Security.

Database Development Phases

Data Planning Process

• Develop an enterprise model that defines the basic business process of the enterprise.
• Define the information needs of end users in a business process.
• Identify key data elements needed to perform specific business activities using entity relationship diagrams.

Database Design Process

• Represent data relationships in a data model that supports a business process.
• This model becomes the schema or subschema for:
  • The physical design of the database.
  • The development of application programs to support business processes.

Logical Design

• A schema provides an overall logical view of relationships.
• A subschema provides a logical view for specific end users.
• Develop data models for DBMS.

Physical Design

• Determine how data will be physically stored and accessed on storage devices.