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1 Basic database terminology and concept. 2 DATA REPRESENTATION Analog vs. Digital Digital  Two states (1) on (0) off.

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Presentation on theme: "1 Basic database terminology and concept. 2 DATA REPRESENTATION Analog vs. Digital Digital  Two states (1) on (0) off."— Presentation transcript:

1 1 Basic database terminology and concept

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

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

4 4 Bit and Byte Bit  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 5 Representing Characters in Bytes

6 6 Using Binary Code to Calculate

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

8 8 Database objects/tools Table Form Query Report

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

10 10 Field A single trait or characteristic about a subject of a table NAMATARIKH LAHIR JANTINANO TELGAJI

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

12 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 13 Record A group of traits about a particular item Simply a row in a table! NAMATARIKH LAHIR JANTINANO TELGAJI … …

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

15 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 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 17 It’s about nothing: Null values and Zero-Length strings Example: Student NameHas Tel. No.?Tel. No. JasmanYes AsmahNoDoes not exist SyafiqYesExist, but we don’t know it ElangovanDon’t knowDon’t know if there’s one

18 Activity 2 18

19 19 Creating a Database

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

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

22 22 A process-oriented approach To define data needs in a process- oriented approach: 1. Define the problem 2. Identify necessary decisions 3. Describe information needs 4. Determine the necessary processing 5. Specify data needs

23 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 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 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 26 Enterprise modeling approach

27 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 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 29 Enterprise modeling approach Strategic Planning for information resources Determining all of the org.’s data needs Create an enterprise data model Create database Storing that data in the database

30 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 31 Entity-relationship diagrams Are used to describe relationships between conceptual collections of data so that their related records can be joined together

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

33 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 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 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 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:  …

37 37

38 38 11 MM

39 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 40 M M Many-to-many relationship

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

42 42 M M 1 M 1 M

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

44 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. 45

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

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

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

49 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 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 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 52 Multidimensional Model

53 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 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 , Association for Computing Machinery. By permission.

55 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 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 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 58 Data Dictionary A data dictionary  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: 59

60 System types SimpleComplex Has few components, and the relationship or interaction between elements is uncomplicated and straightforward Has many elements that are highly related and interconnected OpenClosed Interact with its environmentHas no interaction with the environment StableDynamic Undergoes very little change over timeUndergoes rapid and constant change over time AdaptiveNon-adaptive Is able to change in response to changes in the environment Is not able to change in response to changes in the environment PermanentTemporary Exists for a relatively long period of timeExists for only relatively short period of time 60

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


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