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Phase 3. Systems Design Chapter 6 – Data Design Phase Description • Systems Design is the third of five phases in the systems development life cycle (SDLC) • Now you are ready to begin the physical design of the system that will meet the specifications described in the system requirements document • Systems design tasks include data design, user interface design, and system architecture Data Design Concepts • Before constructing an information system, a systems analyst must understand basic design concepts, including data structures and the characteristics of file-oriented and database systems, including Web-based database design Data Design Concepts • Data Structures • A framework for organizing and storing data => consists of one/more files/tables – A file or table contains data about people, places or events that interact with the system – File-oriented system • File processing – Database system Figure 6-2 Figure 6-3 Data Design Concepts • File processing • Database system Data Design Concepts • Overview of File Processing – Although less common today, file processing can be more efficient and cost less than a DBMS in certain situations – E.g. large volumes of structured data such as process records in a sequence Figure 6-4 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 – relatively permanent data about an entity • Table file – reference data (e.g. tax table, rate tables) • Transaction file – day-to-day business records. Input file that updates master file. • Work file/scratch file – temporary file for a single task • Security file – for backup and recovery purposes • History file – for historical or archiving purposes Data Design Concepts • Overview of Database Systems – A properly design database system offers a solution to the problems of file processing A database might serve 5 separate systems in a database environment Figure 6-5 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 Data Design Concepts • Overview of Database Systems – Advantages • Scalability – expandable/modifiable/downsizable • Better support for client/server systems • Economy of scale – efficiency of high-volume processing on larger computers • Flexible data sharing • Enterprise-wide application – database administrator (DBA) Data Design Concepts • Overview of Database Systems – Advantages • Stronger standards – for data names, formats, documentation, etc • Controlled redundancy • Better security – define authorization procedures • Increased programmer productivity • Data independence DBMS Components Figure 6-6 • Interface • DML – controls DB operations (storing, retrieving, updating, deleting) • Schema – Defines the DB (fields, tables, relationships) • Physical Data Repository 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, costeffectiveness, and worldwide connectivity Figure 6-8 Web-Based Database Design • Connecting a Database to the Web – Database must be connected to the Internet or intranet • Middleware • Macromedia’s ColdFusion Figure 6-9 Data Design Terminology • Definitions – Entity – Table or file – Field • Attribute • Common field – Record • Tuple Figure 6-11 Data Design Terminology • Key Fields – Primary key – unique field or combination of more than one field (Combination key, Composite key, Concatenated key, Multivalued key) – Candidate key – any field(s) that could be primary key • Nonkey field – not primary or candidate – Foreign key – a field in one table that matches a primary key. – Secondary key – field that can be used to access/retrieve records. Not unique 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 Figure 6-13 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) Data Relationships • Entity-Relationship Diagrams – Cardinality • Cardinality notation • Crow’s foot notation • Unified Modeling Language (UML) Figure 6-14 Figure 6-15 Figure 6-16 Figure 6-17 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 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 – Repeating group • Often occur in manual documents prepared by users – Unnormalized design Normalization • Repeating Groups and 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 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 – Note: 1NF with a single field primary key is automatically in 2NF Normalization • Second Normal Form – A standard process exists for converting a table from 1NF to 2NF 1. Create and name a separate table for each field in the existing primary key 2. Create a new table for each possible combination of the original primary key fields 3. Study the three tables and place each field with its appropriate primary key Figure 6-21 Normalization • Second Normal Form Figure 6-21 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 Figure 6-22 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 Figure 6-23 Figure 6-24 Figure 6-25 Steps in Database Design 1. Create the initial ERD 2. Assign all data elements to entities 3. Create 3NF designs for all tables, taking care to identify all primary, secondary, and foreign keys 4. Verify all data dictionary entries • After creating your final ERD and normalized table designs, you can transform them into a database Database Models • Hierarchical and Network Databases – In a hierarchical database, data is organized like a family tree or organization chart, with branches representing parent records and child records – A network database resembles a hierarchical design, but provides somewhat more flexibility 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 Figure 6-34 Figure 6-35 Database Models • Object-Oriented Databases – Many systems developers are using object-oriented database (OODB) design as a natural extension of the objectoriented analysis process • Object data standard • Object Database Management Group (ODMG) • Each object has a unique object identifier Figure 6-36 Figure 6-37 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 Figure 6-38 Data Storage • Data Mining – Works best when you have clear, measurable goals • • • • • Increase average pages viewed per session. Increase number of referred customers Reduce clicks to close Increase checkouts per visit Increase average profit per checkout Figure 6-39 Data Storage • Logical and Physical Storage – Logical storage • • • • As seen through a user’s eyes Characters Date element or data item Logical record – Physical storage • Hardware-related • Physical record or block • Blocking factor Figure 6-40 Data Storage • Data Storage Formats – – – – – Binary digits Bit Byte EBCDIC and ASCII Unicode Figure 6-41 Data Storage • 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 • 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 • 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 Figure 6-42 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 Figure 6-43 and recovery procedures to maintain data Data Control • • • • • • User ID Password Backup Recovery procedures Audit log files Audit fields