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Chapter 6 Data Design.

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Presentation on theme: "Chapter 6 Data Design."— Presentation transcript:

1 Chapter 6 Data Design

2 Design Phase Description
Systems Design is the third of five phases in the systems development life cycle (SDLC) Begin the physical design of the IS that meet the specifications described in the system requirements document IS design tasks include data design, user interface design, and system architecture

3 Chapter Objectives Explain data design concepts and data structures
Describe file processing systems and various types of files Understand database systems and define the components of a database management system (DBMS) 3

4 Chapter Objectives Explain data design terminology, including entities, fields, common fields, records, files, tables, and key fields Describe data relationships, draw an entity-relationship diagram, define cardinality and use cardinality notation Explain the concept of normalization Understand the steps in database design 3

5 Chapter Objectives Describe hierarchical, network, relational, and object-oriented database models Explain data warehousing/data mining Differentiate between logical and physical storage and records Explain data control measures

6 Introduction Develop a physical plan for data organization, storage, and retrieval Begins with a review of data design concepts and terminology, then discusses file-based systems and database systems, including Web-based databases Concludes with a discussion of data mining, data warehousing, physical design issues, logical and physical records, data storage formats, and data controls 4

7 Data Design Concepts Before constructing an IS, a systems analyst must understand basic design concepts, including data structures and the characteristics of file-oriented and database systems

8 Data Design Concepts Data Structures
A file or table contains data about people, places or events that interact with the system File-oriented system File processing Database system

9 Data Design Concepts Overview of File Processing
Some companies use file processing to handle large volumes of structured data Although less common today, file processing can be more efficient and cost less than a DBMS in certain situations

10 Data Design Concepts Overview of File Processing Potential problems
Data redundancy Data integrity Rigid data structure Uses various types of files Master file Table file Transaction file Work file – scratch file Security file History file

11 Data Design Concepts Overview of Database Systems
A properly designed database system offers a solution to the problems of file processing Provides an overall framework that avoids data redundancy and supports a real-time, dynamic environment

12 Data Design Concepts Overview of Database Systems

13 Data Design Concepts Overview of Database Systems
A database management system (DBMS) is a collection of tools, features, and interfaces that enables users to add, update, manage, access, and analyze the contents of a database The main advantage of a DBMS is that it offers timely, interactive, and flexible data access

14 Data Design Concepts Overview of Database Systems Advantages
Scalability Better support for client/server systems Economy of scale Flexible data sharing Enterprise-wide application – database administrator (DBA) Stronger standards Controlled redundancy Better security Increased programmer productivity Data independence

15 Data Design Concepts Database Tradeoffs
Because DBMSs are powerful, they require more expensive hardware, software, and data networks capable of supporting a multiuser environment More complex than a file processing system Procedures for security, backup, and recovery are more complicated and critical

16 DBMS Components Interfaces for Users, Database Administrators, and Related Systems Users Query language Query by example (QBE) SQL (structured query language) Database Administrators A DBA is responsible for DBMS management and support

17 DBMS Components Data Manipulation Language
A data manipulation language (DML) controls database operations, including storing, retrieving, updating, and deleting data

18 Data Design Terminology
Definitions Entity Table or file Field Attribute - Common field Record Tuple

19 Data Design Terminology
Key Fields Primary key Combination key Composite key Concatenated key Multi-valued key Candidate key Nonkey field Foreign key Secondary key

20 Data Design Terminology
Referential Integrity Validity checks can help avoid data input errors In a relational database, referential integrity means that a foreign key value cannot be entered in one table unless it matches an existing primary key in another table

21 Steps to Build Database
Understand and list business rules Define major processes Define information components Assign all data elements to the entities Develop ER model Define cardinality and keys Identify all dependencies Normalize the entities

22 Data Relationships Entity-Relationship Diagrams

23 Data Relationships A relationship is a logical link between entities based on how they interact Entity-Relationship Diagrams One-to-one relationship (1:1) One-to-many relationship (1:M) Many-to-many relationship (M:N) Cardinality Cardinality notation Crow’s foot notation Unified Modeling Language (UML)

24 Normalization Normalization Table design
Involves four stages: unnormalized design, first normal form, second normal form, and third normal form Most business-related databases must be designed in third normal form

25 Normalization Repeating Groups and Unnormalized Design
Repeating group - Often occur in manual documents prepared by users Unnormalized design

26 Normalization First Normal Form
A table is in first normal form (1NF) if it does not contain a repeating group To convert, you must expand the table’s primary key to include the primary key of the repeating group

27 Normalization Second Normal Form
To understand second normal form (2NF), you must understand the concept of functional dependence Field X is functionally dependent on field Y if the value of field X depends on the value of field Y

28 Normalization Second Normal Form
A standard process exists for converting a table from 1NF to 2NF Create and name a separate table for each field in the existing primary key Create a new table for each possible combination of the original primary key fields Study the three tables and place each field with its appropriate primary key

29 Normalization Second Normal Form
Four kinds of problems are found with 1NF description that do not exist with 2NF Consider the work necessary to change a particular product’s description 1NF tables can contain inconsistent data Adding a new product is a problem Deleting a product is a problem

30 Normalization Third Normal Form
3NF design avoids redundancy and data integrity problems that still can exist in 2NF designs A table design is in third normal form (3NF) if it is in 2NF and if no nonkey field is dependent on another nonkey field

31 Normalization Third Normal Form
To convert the table to 3NF, you must remove all fields from the 2NF table that depend on another nonkey field and place them in a new table that uses the nonkey field as a primary key

32 Normalization A Normalization Example
To show the normalization process, consider the familiar situation in Figure 6-24 which might depict several entities in a school advising system: ADVISOR, COURSE, and STUDENT The relationships among the three entities are shown in the ERD in Figure 6-25

33 Steps in Database Design
Create the initial ERD Assign all data elements to entities Create 3NF designs for all tables, taking care to identify all primary, secondary, and foreign keys Verify all data dictionary entries After creating your final ERD and normalized table designs, you can transform them into a database

34 Data Storage Data Warehousing Data warehouse - dimensions
Without a data warehouse it would be difficult for a user to extract data that spans several information systems and time frames Allows users to retrieve and analyze the data easily

35 Data Control File and database control must include all measures necessary to ensure that data storage is correct, complete, and secure A well-designed DBMS must provide built-in control and security features, including subschemas, passwords, encryption, audit trail files, and backup and recovery procedures to maintain data

36 Data Control User ID Password Backup Recovery procedures
Audit log files Audit fields Encryption

37 Chapter Summary Files and tables contain data about people, places, things, or events that affect the information system DBMS designs are more powerful and flexible than traditional file-oriented systems 49

38 Chapter Summary Data design tasks include creating an initial ERD; assigning data elements to an entity; normalizing all table designs; and completing the data dictionary entries for files, records, and data elements The four basic database models are hierarchical, network, relational, and object-oriented 49

39 Chapter Summary Physical storage is hardware-related and involves reading and writing blocks of binary data to physical media File and database control measures include limiting access to the data, data encryption, backup/recovery procedures, audit-trail files, and internal audit fields 49

40 Review: Analysis Phase
Deliverable – Systems Requirement Document Fact-finding of current system and identify system requirements Develop logical model (WHAT IS must do) Develop physical model (HOW IS is constructed) Evaluate development strategies Create the System Requirement Document

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