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Chapter 7. 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) Describe Web-based data design. Chapter Objectives.
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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) • Describe Web-based data design
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 • Explain the importance of codes and describe various coding schemes
Chapter Objectives • Describe relational and object-oriented database models • Explain data warehousing and data mining • Differentiate between logical and physical storage and records • Explain data control measures
Introduction • You will 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 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 control
Data Design Concepts • Data Structures • A file or table contains data about people, places, things, or events that interact with the system • File-oriented system • File processing system • Database system
Data Design Concepts • Overview of File Processing • Potential problems • Data redundancy • Data integrity • Rigid data structure
Data Design Concepts • Overview of File Processing • Uses various types of files • Master file • Table file • Transaction file • Work file – scratch file • Security file • History file
Data Design Concepts • Overview of Database Systems • A properly design 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 • Database management system (DBMS) • The main advantage of a DBMS is that it offers timely, interactive, and flexible data access
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
Data Design Concepts • Overview of Database Systems • Advantages • Controlled redundancy • Better security • Increased programmer productivity • Data independence
Data Design Concepts • Database Tradeoffs • Because DBMSs are powerful, they require more expensive hardware, software, and data networks capable of supporting a multi-user environment • More complex than a file processing system • Procedures for security, backup, and recovery are more complicated and critical
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
DBMS Components • Data Manipulation Language • 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 • In a Web-based design, the Internet serves as the front end, or interface, for the database management system • Internet technology provides enormous power and flexibility • Web-based systems are popular because they offer ease of access, cost-effectiveness, and worldwide connectivity
Web-Based Database Design • Internet Terminology • Web browser • Web page • HTML – Hypertext Markup Language • Tags • Web server • Web site • Intranet
Web-Based Database Design • Internet Terminology • 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 • Macromedia’s ColdFusion
Web-Based Database Design • Data Security • Web-based data must be totally secure, yet easily accessible to authorized users • To achieve this goal, 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 • Attribute • Common field • Record • Tuple
Data Design Terminology • Key Fields • Primary key • Combination key • Composite key • Concatenated key • Multi-valued key • Candidate key • Nonkey field • Foreign key • Secondary key
Data Design Terminology • Referential Integrity • Validity checks can help avoid data input errors
Entity-Relationship Diagrams • An entity is a person, place, thing, or event for which data is collected and maintained • Provides an overall view of the system, and a blueprint for creating the physical data structures • Entity-relationship diagram
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
Entity-Relationship Diagrams • Types of Relationships • One-to-one relationship (1:1) • One-to-many relationship (1:M) • Many-to-many relationship (M:N) • Associative entity • Cardinality • Cardinality notation • Crow’s foot notation • Unified Modeling Language (UML)
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
Normalization • Standard Notation Format • Designing tables is easier if you use a standard notation formatto show a table’s structure, fields, and primary key Example: NAME (FIELD 1, FIELD 2, FIELD 3)
Normalization • Repeating Groups and Unnormalized Designs • Repeating group • Often occur in manual documents prepared by users • Unnormalized design
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 • Second Normal Form • To understand second normal form (2NF), you must understand the concept of functional dependence • Functionally dependent
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
Normalization • Second Normal Form • Four kinds of problems are found with 1NF designs that do not exist in 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
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 • To show the normalization process, consider the familiar situation, which depicts several entities in a school advising system: ADVISOR, COURSE, and STUDENT
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 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 • Category codes • Abbreviation codes – mnemonic 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 • Avoid confusing codes • Make codes meaningful • Use a code for a single purpose • Keep codes consistent
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
Database Models • Relational Databases • The relational model was introduced during the 1970s and became popular because it was flexible and powerful • Because all the tables are linked, a user can request data that meets specific conditions • New entities and attributes can be added at any time without restructuring the entire database
Database Models • Object-Oriented Databases • Many systems developers are using object-oriented database (OODB) design as a natural extension of the object-oriented analysis process • Object Data standard • Object Database Management Group (ODMG) • Each object has a unique object identifier
Data Storage and Access • Data storage and access involve strategic business tools • Strategic tools for data storage and access • Data warehouse - dimensions
Data Storage and Access • Strategic tools for data storage and access • Data Mining • Increase average pages viewed per session • Increase number of referred customers • Reduce clicks to close • Increase checkouts per visit • Increase average profit per checkout
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 Storage Formats • Binary digits • Bit • Byte • EBCDIC and ASCII • Unicode
Data Storage and Access • Data Storage Formats • Binary • Binary storage format • Integer format • Long integer format • Other binary formats exist for efficient storage of exceedingly long numbers
Data Storage and Access • Selecting a Data Storage Format • In many cases, a user can select a specific data storage format • For example, when using Microsoft Office, you can store documents, spreadsheets, and databases in Unicode-compatible form by using the font called Arial Unicode MS • Best answer is it depends on the situation
Data Storage and Access • Date Fields • Most date formats now are based on the model established by the International Organization for Standardization (ISO) • Can be sorted easily and used in comparisons • Absolute date • Best method depends on how the specific date will be printed, displayed, or used in a calculation
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
Data Control • User ID • Password • Permissions • Encryption • Backup • Recovery procedures • Audit log files • Audit fields