1. Lecture-7/ T. Nouf Almujally
Data Resource Management
Section 1: “Technical Foundations of Database Management”
Chapter 5
Lecture-7/ T. Nouf Almujally 1

2. Outline Section 1: Technical Foundations of Database Management
Fundamental Data Concepts
Database Structures
Database Development
Data planning and Database Design (not required)

3. Section 1
Technical Foundations of Database Management

4. Database Management
Data are a vital organizational resource that need to be managed like other important business assets.
Today's business enterprise cannot succeed without quality data about their internal operations and external environment.
In all information systems, data resources must be organized and structured in some logical manner so that they can be accessed easily, processed efficiently, retrieved quickly, and managed effectively.
Database provide a logical organization method and easy access to the data stored in it.

5. Logical Data Elements Data may be logically organized into: character
field
record
file
database

6. Logical Data Elements Character Field (data item) Record Database
File (table, flat file)
Database
A single alphabetic, numeric, or other symbol
Consists of a grouping of related characters.
Represents an attribute (characteristic) of some entity (object, person, place, event)
Examples… salary, job title
Grouping of all the fields used to describe the attributes of an entity
Example… payroll records with name, SSN, pay rate
Primary Key.
Group of related records
Integrated collection of logically related data elements
It consolidates records previously stored in separate files into a common pool of data elements that provides data for many applications

7. Fundamental Data Concepts

8. Fundamental Data Concepts
The data stored in a database are independent of the application programs using them and of the type of storage devices on which they are stored.
Databases contain data elements describing entities and relationships among entities.

9. Electric Utility Database
Business applications that access the data in the DB

10. Database Structures
The relationships among the many individual data elements stored in databases are based on one of several logical data structures, or models.
Database management system (DBMS) packages are designed to use a specific data structure to provide end users with quick, easy access to information stored in databases.
Five fundamental database structures:
Hierarchical , network , relational, object-oriented and multidimensional models.

11. Common Database Structures: Hierarchical
Root Element
Early mainframe DBMS packages used this structure.
Records arranged in a hierarchy or tree-like structure
Relationships are one-to-many

12. Common Database Structures: Network
Can represent more complex logical relationships and is still used by mainframe DBMS packages.
Many-to-many relationships among records.

13. Common Database Structures: Relational
Most widely used structure
Used by microcomputer DBMS packages, as well as by most midrange and mainframe systems.
Data elements are stored in tables (sometimes referred to as relations).
Row represents a record; column is a field.
DBMS packages based on relational model can relate data in one table with data in another, if both tables share a common data element.
Relational operations include:
Select… Create a subset of records that meet a stated criterion. Example: employees earning more than $30,000
Join… Combine two or more tables temporarily. Looks like one big table.
Project… Create a subset of columns in a table

14. Common Database Structures: Relational
A lot of commercial products exist to create and manage relational models:
Mainframe relational DB applications:
Oracle10g from Oracle
DB2 from IBM
Midrange DB applications:
SQL Server from Microsoft.
The most commonly used DB application for the PC is Microsoft Access.

15. Common Database Structures: Multidimensional
Variation of relational model that uses multidimensional structures to organize data and express the relationships between them.
Data elements are viewed as being in cubes. Each side of the cube is considered a dimension of the data.
Each dimension represent a different category.
Have become the most popular database structure for the analytical databases that support Online Analytical Processing (OLAP) applications, in which fast answers to complex business quires are expected.

16. Multidimensional Database Structures

17. Multidimensional Database Structures

18. Multidimensional Model

19. Common Database Structures: Object-Oriented
the object-oriented model is considered one of the key technologies of a new generation of multimedia Web-based applications.
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
OODBMS now is popular in CAD and in multimedia Web-based applications.
Supports complex data types more efficiently than relational databases
Examples: graphic images, video clips, web pages

20. Common Database Structures: Object-Oriented
major relational DBMS vendors add object-oriented modules to their relational software.
Examples include multimedia object extensions to IBM’s DB2 and Oracle’s object- based “cartridges” for Oracle.

21. Evaluation of Database Structures
Hierarchical
- Was for DB’s used for the structured, routine types of transaction processing of many business in the early years of data processing and computing.
- Can’t handle many-to-many relationship
Network
- More flexible than hierarchical
- Unable to handle ad hoc requests
Relational
- Easily responds to ad hoc requests
- Easier to work with & maintain
Can't process large amounts of bus. Transactions as efficient or quick as hierarchical or network
can’t process complex applications as object-oriented models.
- Ex: Oracle, DB2, Access , Lotus Approach

22. Con. Object-Oriented Multidimensional
Can process complex, high volume applications.
- The use of this model is growing steadily.
- Play a great role in web-based applications.
Multidimensional
The use of this model is growing steadily.
- Play a great role in OLAP applications.

23. Database Development
Database management package like Microsoft Access or Lotus Approach allow end users to develop the databases they need easily.
Large organizations usually place control of enterprise database development in the hands of (DBA) and other database specialists.

24. Database Development Database Administrator (DBA)
In charge of enterprise-wide database development
Improves integrity and security of organizational databases
Uses Data Definition Language (DDL) in DBMS to develop and specify data content, relationships, and structure
This information is then stored in a database of data definitions and
specifications called a data dictionary or metadata repository
which is managed by the DBA

25. Data Dictionary Data Dictionary Contains information on…
Directory holds information about the database and the data that it stores (data about data = metadata)
Relies on specialized software component to manage a database of data definitions
Names and descriptions of all types of data records and their interrelationships
Requirements for end users’ access and use of applications
Contains information on…
Database maintenance
Security

26. Data Dictionary

27. Database Development
Developing a large DB of complex data types can be a complicated task.
Database administrator and the database design analyst work with end users and system analysts to model the business processes and the data they require. Then they determine:
What data definitions should be included in the DB.
What relationships should exist among the data elements.

28. Questions ..

29. Read from Chapter 5 (Section 1)
Resources ..
Read from Chapter 5 (Section 1)