Systems Analysis and Design 9th Edition Chapter 9 Data Design

Chapter Objectives Explain file-oriented systems and how they differ from database management systems 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

Chapter Objectives Explain the importance of codes and describe various coding schemes Explain data warehousing and data mining Differentiate between logical and physical storage and records Explain data control measures

Introduction 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 storage and access, including strategic tools such as data warehousing and data mining, physical design issues, logical and physical records, data storage formats, and data controls

Data Design Concepts Data Structures Each file or table contains data about people, places, things or events that interact with the information system File-oriented system Database management system (DBMS)

Data Design Concepts Overview of File Processing File processing can be efficient and cost-effective in certain situations Potential problems Data redundancy Data integrity Rigid data structure

Data Design Concepts Overview of File Processing Various types of files Master file Table file Transaction file Work file Security file History file

Data Design Concepts The Evolution from File Systems to 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

Data Design Concepts The Evolution from File Systems to Database Systems Some Advantages Scalability Better support for client/server systems Economy of scale Flexible data sharing Enterprise-wide application – database administrator (DBA) Stronger standards

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

DBMS Components Interfaces for Users, Database Administrators, and Related Systems Related information systems A DBMS can support several related information systems that provide input to, and require specific data from, the DBMS No human intervention is required for two-way communication

DBMS Components Data Manipulation Language Schema A data manipulation language (DML) controls database operations, including storing, retrieving, updating, and deleting data Schema The complete definition of a database, including descriptions of all fields, tables, and relationships, is called a schema You also can define one or more subschemas

DBMS Components Physical Data Repository The data dictionary is transformed into a physical data repository, which also contains the schema and subschemas The physical repository might be centralized, or distributed at several locations ODBC – open database connectivity JDBC – Java database connectivity

Web-Based Database Design Characteristics of Web-Based Design

Web-Based Database Design Internet Terminology Web browser Web page HTML (Hypertext Markup Language) Tags Web server Web site

Web-Based Database Design Internet Terminology Intranet Extranet Protocols Web-centric Clients Servers

Web-Based Database Design Connecting a Database to the Web Database must be connected to the Internet or intranet Middleware Adobe ColdFusion Data Security Well-designed systems provide security at three levels: the database itself, the Web server, and the telecommunication links that connect the components of the system

Data Design Terminology Definitions Entity Table or file Field Record Tuple

Data Design Terminology Key Fields Primary key Candidate key Foreign key Secondary key

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 Orphan

Entity-Relationship Diagrams Drawing an ERD The first step is to list the entities that you identified during the fact-finding process and to consider the nature of the relationships that link them A popular method is to represent entities as rectangles and relationships as diamond shapes

Entity-Relationship Diagrams Types of Relationships Three types of relationships can exist between entities One-to-one relationship (1:1) One-to-many relationship (1:M) Many-to-many relationship (M:N)

Entity-Relationship Diagrams Cardinality Cardinality notation Crow’s foot notation Unified Modeling Language (UML) Now that you understand database elements and their relationships, you can start designing tables

Normalization Standard Notation Format Designing tables is easier if you use a standard notation format to show a table’s structure, fields, and primary key Example: NAME (FIELD 1, FIELD 2, FIELD 3)

Normalization Repeating Groups and Unnormalized Design Often occur in manual documents prepared by users Unnormalized Enclose the repeating group of fields within a second set of parentheses

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

Normalization Second Normal Form A table design is in second normal form (2NF) if it is in 1NF and if all fields that are not part of the primary key are functionally dependent on the entire primary key A standard process exists for converting a table from 1NF to 2NF The objective is to break the original table into two or more new tables and reassign the fields so that each nonkey field will depend on the entire primary key in its table

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 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

Normalization A Normalization Example

Using Codes During Data Design Overview of Codes Because codes often are used to represent data, you encounter them constantly in your everyday life They save storage space and costs, reduce data transmission time, and decrease data entry time Can reduce data input errors

Using Codes During Data Design Types of Codes Sequence codes Block sequence codes Alphabetic codes Significant digit codes Derivation codes Cipher codes Action codes

Using Codes During Data Design Developing a Code Keep codes concise Allow for expansion Keep codes stable Make codes unique Use sortable codes

Using Codes During Data Design Developing a Code Avoid confusing codes Make codes meaningful Use a code for a single purpose Keep codes consistent

Database Design: One Step At a Time Create an initial ERD Next, create an ERD Review all the data elements Review the 3NF designs for all tables Double-check all data dictionary entries After creating your final ERD and normalized table designs, you can transform them into a database

Database Models A Real-World Business Example Imagine a company that provides on-site service for electronic equipment, including parts and labor

Database Models Working with a Relational Database To understand the power and flexibility of a relational database, try the following exercise Suppose you work in IT, and the sales team needs answers to three specific questions The data might be stored physically in seven tables

Data Storage and Access Data storage and access involve strategic business tools Strategic tools for data storage and access Data warehouse – dimensions Data mart Data Mining

Data Storage and Access Logical and Physical Storage Logical storage Characters Data element or data item Logical record Physical storage Physical record or block Buffer Blocking factor

Data Storage and Access Data Coding and Storage Binary digits Bit Byte EBCDIC, ASCII, and Binary Unicode

Data Storage and Access Data Coding and Storage Storing dates Y2K Issue Most date formats now are based on the model established by the International Organization for Standardization (ISO) Absolute date

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

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

Chapter Summary An entity-relationship (ERD) is a graphic representation of all system entities and the relationships among them A code is a set of letters or numbers used to represent data in a system The most common database models are relational and object-oriented

Chapter Summary Logical storage is information seen through a user’s eyes, regardless of how or where that information actually is organized or stored 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

Chapter Summary Chapter 9 complete