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Basic database terminology and concept

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1 Basic database terminology and concept

2 DATA REPRESENTATION Analog vs. Digital Digital Two states (1) on
(0) off

3 DATA REPRESENTATION Binary number system
Combination of ones and zeroes represent characters

4 Bit and Byte Bit Byte Short for binary digit Smallest element of data
Either zero or one Byte Group of eight bits, which operate as a single unit Represents one character or number

5 Representing Characters in Bytes

6 Using Binary Code to Calculate

7 Hierarchy of Data Bit Byte (Character) Field Record File Database

8 Database objects/tools
Table Form Query Report

9 Table A table is a grid of rows and columns COLUMN R O W

10 Field A single trait or characteristic about a subject of a table NAMA

11 Data type Characteristic designate for an Access field Text Number
Currency Date/time Yes/No Memo OLE object Hyperlink

12 Exercise Salutation (Mr., Mrs., Ms.) Date of birth Home address
Whether a student is allergy to medication The words to describe type of allergy Photo of a student How many sibling in the house Salary

13 Record A group of traits about a particular item …

14 Value The actual data entered at the intersection of a row and column

15 Primary keys Key is a field that serves a specific function within a table. AutoNumber Requirement for a relational database. Means, in a field that is the primary key, there can never be duplicate data example

16 It’s about nothing: Null values and Zero-Length strings
“Report that say something hasn’t happen are always interesting to me because, as we know, there are known knowns, there are things we know we know. We also know there are known unknowns; that is to say, we know there are some things we do not know. But there are also unknown unknowns-the ones we don’t know we don’t know” At a press conference in 2003 Donald Rumsfeld Secretary of Defense (in the Bush Administration)

17 It’s about nothing: Null values and Zero-Length strings
Example: Student Name Has Tel. No.? Tel. No. Jasman Yes Asmah No Does not exist Syafiq Exist, but we don’t know it Elangovan Don’t know Don’t know if there’s one

18 Activity 2

19 Creating a Database

20 Three main steps Determine the data you need You describe the data
You enter the data into the database

21 Determine Data Needs Two basic approaches can be used to determine data needs: A process-oriented approach An enterprise modeling approach

22 A process-oriented approach
To define data needs in a process-oriented approach: Define the problem Identify necessary decisions Describe information needs Determine the necessary processing Specify data needs

23 A process-oriented approach
Sometimes called the problem-oriented approach Because it begins with a problem A problem can be good or bad

24 A process-oriented approach
Once problems are identified, the data and processes dealing with problem solutions can be determined The strength is that it addresses problems well

25 A process-oriented approach
Although the process-oriented approach enables the data needs of each system to be defined in a logical manner, its weakness is the difficulty of linking the data from one problem to another IS cannot easily share data if they are isolated from other IS dealing with other kind of problems.

26 Enterprise modeling approach

27 Data Planning Process Database development is a top-down 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 the key data elements that are needed to perform specific business activities (entity relationship diagrams)

28 Enterprise modeling approach
The strength of this approach is that it takes advantages of a broad view of data resources All areas are considered, and synergy of data resources between areas can be leveraged

29 Enterprise modeling approach
Strategic Planning for information resources Determining all of the org.’s data needs Storing that data in the database

30 Data Modeling Techniques
Modeling the org.’s data needs is supported by techniques that describe the data, how the data aggregates into tables, and how tables relate to each other. A number of techniques: entity-relationship diagrams and class diagrams

31 Entity-relationship diagrams
Are used to describe relationships between conceptual collections of data so that their related records can be joined together

32 Class diagrams Are used to describe both the data relationship and the actions that operate on the data in the relationships

33 Entity-relationship diagrams
ERDs Deal with data in entities and the relationships between entities Entities – conceptual collections of related data fields Tables are the result of breaking entities into smaller units that conform to the rules for database structures

34 Entity-relationship diagrams
An entity may turn into table, but frequently an entity is broken into several tables ERDs are a higher level conceptualization of data than tables

35 Entity-relationship diagrams
Entities in ERDs will have names and relationship links ERD relationships will denote if a record in one entity will relate to one or more records in other entity

36 Entity-relationship diagrams
Let us assume that we need to describe the data needed for a new IS: IS Sekolah SAYA 3 separate data entities will exist:


38 1 1 M M

39 To read the relationship:
One-to-many relationship - “one school record may relate to many staff records and one staff record may relate to only one school record”

40 Many-to-many relationship

41 Many-to-many relationship
A single subject could have many staff, and a single staff could be on many subject

42 1 1 M M M M

43 Class Diagrams clsMataPel Title Ting addMataPel deleteMataPel
updateMataPel clsSchool SchoolName Adress addSchool deleteSchool updateSchool 1 1…* 1 1…* 1…* clsStud Name IC StudAdd addStud deleteStud updateStud ExamStud clsStaf Name Salary HireDate addStaf deleteStaf updateStaf 1…*

44 Using the database Forms, reports and queries are common methods for accessing the database held in database management system

45 Database Structures In all IS, 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.

46 Database Structures Common database structures… Hierarchical Network
Relational Object-oriented Multi-dimensional

47 Hierarchical Structure
Early DBMS structure Records arranged in tree-like structure Relationships are one-to-many

48 Network Structure Used in some mainframe DBMS packages
Many-to-many relationships

49 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

50 Relational Operations
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

51 Multidimensional Structure
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)

52 Multidimensional Model

53 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

54 Object-Oriented Structure
Source: Adapted from Ivar Jacobsen, Maria Ericsson, and Ageneta Jacobsen, The Object Advantage: Business Process Reengineering with Object Technology (New York: ACM Press, 1995), p. 65. 1995, Association for Computing Machinery. By permission.

55 Object-Oriented Structure
Used in object-oriented database management systems (OODBMS) Supports complex data types more efficiently than relational databases Examples: graphic images, video clips, web pages Example use for product design

56 Evaluation of Database Structures
Hierarchical Works for structured, routine transactions 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 and maintain Not as efficient/quick as hierarchical or network

57 Database Development Database Administrator (DBA)
In charge of enterprise database development Improves the integrity and security of organizational databases Uses Data Definition Language (DDL) to develop and specify data contents, relationships, and structure Stores these specifications in a data dictionary or a metadata repository

58 Data Dictionary A data dictionary It contains information on..
Contains data about data (metadata) Relies on specialized software component to manage a database of data definitions It contains information on.. The names and descriptions of all types of data records and their interrelationships Requirements for end users’ access and use of application programs Database maintenance Security

59 Based on database structure above, describe the characteristics of the IS or the organization which hold the IS. Use the following table for discussion:

60 System types Simple Complex
Has few components, and the relationship or interaction between elements is uncomplicated and straightforward Has many elements that are highly related and interconnected Open Closed Interact with its environment Has no interaction with the environment Stable Dynamic Undergoes very little change over time Undergoes rapid and constant change over time Adaptive Non-adaptive Is able to change in response to changes in the environment Is not able to change in response to changes in the environment Permanent Temporary Exists for a relatively long period of time Exists for only relatively short period of time

61 Database Structures Source: Management Information Systems by James A. O'Brien and George Marakas. McGraw-Hill Higher Education

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