Object Oriented Analyis & Design Training Agenda

Object Oriented Analyis & Design Training Agenda

SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman C H A P T E R 8 Irwin/McGraw-Hill DATA MODELING AND ANALYSIS Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Chapter Eight

Whitten Bentley Dittman Data Modeling and Analysis Define data modeling and explain its benefits. Recognize and understand the basic concepts and constructs of a data model. Read and interpret an entity relationship data model. Explain when data models are constructed during a project and where the models are stored. Discover entities and relationships. Construct an entity-relationship context diagram. Discover or invent keys for entities and construct a key-based diagram. Construct a fully attributed entity relationship diagram and describe all data structures and attributes to the repository or encyclopedia. Normalize a logical data model to remove impurities that can make a database unstable, inflexible, and nonscalable.

Describe a useful tool for mapping data requirements to business operating locations. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Chapter Map Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling

Data modeling a technique for organizing and documenting a systems data. Sometimes called database modeling. Entity relationship diagram (ERD) a data model utilizing several notations to depict data in terms of the entities and relationships described by that data. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Sample Entity Relationship Diagram (ERD) Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Data Modeling Concepts: Entity Entity a class of persons, places, objects, events, or concepts about which we need to capture and store data. Named by a singular noun Persons: agency, contractor, customer, department, division, employee, instructor, student, supplier. Places: sales region, building, room, branch office, campus. Objects: book, machine, part, product, raw material, software license, software package, tool, vehicle model, vehicle.

Events: application, award, cancellation, class, flight, invoice, order, registration, renewal, requisition, reservation, sale, trip. Concepts: account, block of time, bond, course, fund, qualification, stock. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Entity Entity instance a single occurrence of an entity. entity Student ID Last Name First Name

instance Irwin/McGraw-Hill 2144 Arnold Betty 3122 Taylor John 3843 Simmons Lisa

9844 Macy Bill 2837 Leath Heather 2293 Wrench Tim Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman

Data Modeling Concepts: Attributes Attribute a descriptive property or characteristic of an entity. Synonyms include element, property, and field. Just as a physical student can have attributes, such as hair color, height, etc., a data entity has data attributes Compound attribute an attribute that consists of other attributes. Synonyms in different data modeling languages are numerous: concatenated attribute, composite attribute, and data structure. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman

Data Modeling Concepts: Data Type Data type a property of an attribute that identifies what type of data can be stored in that attribute. Representative Logical Data Types for Attributes Logical Data Type Logical Business Meaning NUMBER Any number, real or integer. TEXT A string of characters, inclusive of numbers. When numbers are included in a TEXT attribute, it means that we do not expect to perform arithmetic or comparisons with those numbers. MEMO Same as TEXT but of an indeterminate size. Some business systems require

the ability to attach potentially lengthy notes to a give database record. DATE Any date in any format. TIME Any time in any format. YES/NO An attribute that can assume only one of these two values. VALUE SET A finite set of values. In most cases, a coding scheme would be established (e.g., FR=Freshman, SO=Sophomore, JR=Junior, SR=Senior). IMAGE Any picture or image.

Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Domains Domain a property of an attribute that defines what values an attribute can legitimately take on. Representative Logical Domains for Logical Data Types Data Type Domain Examples NUMBER For integers, specify the range. For real numbers, specify the range and precision.

{10-99} {1.000-799.999} TEXT Maximum size of attribute. Actual values are usually infinite; however, users may specify certain narrative restrictions. Text(30) DATE Variation on the MMDDYYYY format. MMDDYYYY MMYYYY TIME For AM/PM times: HHMMT For military (24-hour times): HHMM

HHMMT HHMM YES/NO {YES, NO} {YES, NO} {ON, OFF} VALUE SET {value#1, value#2,value#n} {table of codes and meanings} {M=Male F=Female} Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Data Modeling Concepts: Default Value Default value the value that will be recorded if a value is not specified by the user. Permissible Default Values for Attributes Default Value Interpretation Examples A legal value For an instance of the attribute, if the user does from the domain not specify a value, then use this value. 0 1.00 NONE or NULL

For an instance of the attribute, if the user does not specify a value, then leave it blank. NONE NULL Required or NOT NULL For an instance of the attribute, require that the user enter a legal value from the domain. (This is used when no value in the domain is common enough to be a default but some value must be entered.) REQUIRED NOT NULL Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Data Modeling Concepts: Identification Key an attribute, or a group of attributes, that assumes a unique value for each entity instance. It is sometimes called an identifier. Concatenated key - a group of attributes that uniquely identifies an instance of an entity. Synonyms include composite key and compound key. Candidate key one of a number of keys that may serve as the primary key of an entity. Also called a candidate identifier. Primary key a candidate key that will most commonly be used to uniquely identify a single entity instance. Alternate key a candidate key that is not selected to become the primary key is called an alternate key. A synonym is secondary key. Irwin/McGraw-Hill

Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Subsetting Criteria Subsetting criteria an attribute(s) whose finite values divide all entity instances into useful subsets. Sometimes called inversion entry. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Relationships

Relationship a natural business association that exists between one or more entities. The relationship may represent an event that links the entities or merely a logical affinity that exists between the entities. Student Irwin/McGraw-Hill Is being studied by is enrolled in Curriculum Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman

Data Modeling Concepts: Cardinality Cardinality the minimum and maximum number of occurrences of one entity that may be related to a single occurrence of the other entity. Because all relationships are bidirectional, cardinality must be defined in both directions for every relationship. bidirectional Student Irwin/McGraw-Hill Is being studied by is enrolled in Curriculum Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Cardinality Notations Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Degree Degree the number of entities that participate in the relationship. A relationship between two entities is called a binary relationship. A relationship between different instances of the same entity is called a recursive relationship. A relationship between three entities is called a 3-ary or ternary relationship.

Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Recursive Relationship Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Degree Relationships may exist between more than two

entities and are called N-ary relationships. The example ERD depicts a ternary relationship. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Degree Associative entity an entity that inherits its primary key from more than one other entity (called parents). Associative

Entity Each part of that concatenated key points to one and only one instance of each of the connecting entities. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Foreign Keys Foreign key a primary key of an entity that is used in another entity to identify instances of a relationship. A foreign key is a primary key of one entity that is contributed to (duplicated in) another entity to identify

instances of a relationship. A foreign key always matches the primary key in the another entity A foreign key may or may not be unique (generally not) The entity with the foreign key is called the child. The entity with the matching primary key is called the parent. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Foreign Keys Primary Key Student ID Last Name First Name Dorm

2144 Arnold Betty Smith 3122 Taylor John Jones 3843 Simmons Lisa

Smith 9844 Macy Bill 2837 Leath Heather Smith 2293 Wrench Tim Jones

Primary Key Dorm Residence Director Smith Andrea Fernandez Jones Daniel Abidjan Irwin/McGraw-Hill Foreign Key Duplicated from primary key of Major entity (not unique) Copyright 2004 The McGraw-Hill Companies. All Rights rese

SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Nonidentifying Relationships Nonidentifying relationship a relationship in which each participating entity has its own independent primary key Primary key attributes are not shared. The entities are called strong entities Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Identifying Relationships Identifying relationship a relationship in which the parent entity key is also part of the primary key of the child entity. The child entity is called a weak entity.

Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Sample CASE Tool Notations Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Nonspecific Relationships Nonspecific relationship a relationship

where many instances of an entity are associated with many instances of another entity. Also called manyto-many relationship. Nonspecific relationships must be resolved. Most nonspecific relationships can be resolved by introducing an associative entity. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Resolving Nonspecific Relationships Irwin/McGraw-Hill The verb or verb phrase of a manyto-many relationship sometimes suggests other entities. Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Resolving Nonspecific Relationships (continued) Irwin/McGraw-Hill Many-to-many relationships can be resolved with an associative

entity. Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Resolving Nonspecific Relationships (continued) Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data Modeling Concepts: Generalization Generalization a concept wherein the attributes that are common to several types of an entity are grouped into their own entity.

Supertype an entity whose instances store attributes that are common to one or more entity subtypes. Subtype an entity whose instances may inherit common attributes from its entity supertype And then add other attributes that are unique to the subtype. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Generalization Hierarchy Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman The Process of Logical Data Modeling Strategic Data Modeling Many organizations select IS development projects based on strategic plans. Includes vision and architecture for information systems Identifies and prioritizes develop projects Includes enterprise data model as starting point for projects Data Modeling during Systems Analysis Data model for a single information system is called an application data model. Context data model includes only entities and relationships. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Logical Model Development Stages 1. Context Data model To establish project scope 2. Key-base data model Eliminate nonspecific relationships Add associative entities Include primary and alternate keys Precise cardinalities 3. Fully attributed data model All remaining attributes Subsetting criteria 4. Normalized data model

Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman JRP and Interview Questions for Data Modeling Purpose Candidate Questions (see Table 8-4 in text for a more complete list) Discover system entities What are the subjects of the business? Discover entity keys What unique characteristic (or characteristics) distinguishes an instance of each subject from other instances of the same

subject? Discover entity subsetting criteria Are there any characteristics of a subject that divide all instances of the subject into useful subsets? Discover attributes and domains What characteristics describe each subject? Discover security and control needs Are there any restrictions on who can see or use the data? Discover data timing needs How often does the data change? Discover generalization hierarchies Are all instances of each subject the same?

Discover relationships? What events occur that imply associations between subjects? Discover cardinalities Is each business activity or event handled the same way, or are there special circumstances? Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Automated Tools for Data Modeling Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese

SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Entity Discovery for SoundStage Entity Name Business Definition Agreement A contract whereby a member agrees to purchase a certain number of products within a certain time. After fulfilling that agreement, the member becomes eligible for bonus credits that are redeemable for free or discounted products. Member An active member of one or more clubs. Note: A target system objective is to re-enroll inactive members as opposed to deleting them. Member order

An order generated for a member as part of a monthly promotion, or an order initiated by a member. Note: The current system only supports orders generated from promotions; however, customer initiated orders have been given a high priority as an added option in the proposed system. Transaction A business event to which the Member Services System must respond. Product An inventoried product available for promotion and sale to members. Note: System improvement objectives include (1) compatibility with new bar code system being developed for the warehouse, and (2) adaptability to a rapidly changing mix of products. Promotion Irwin/McGraw-Hill A monthly or quarterly event whereby special product offerings are made available to members.

Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman The Context Data Model Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman The Key-based Data Model Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese

SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman The Key-based Data Model With Generalization Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman The Fully-Attributed Data Model Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman

What is a Good Data Model? A good data model is simple. Data attributes that describe any given entity should describe only that entity. Each attribute of an entity instance can have only one value. A good data model is essentially nonredundant. Each data attribute, other than foreign keys, describes at most one entity. Look for the same attribute recorded more than once under different names. A good data model should be flexible and adaptable to future needs. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman Data Analysis & Normalization Data analysis a technique used to improve a data model for implementation as a database. Goal is a simple, nonredundant, flexible, and adaptable database. Normalization a data analysis technique that organizes data into groups to form nonredundant, stable, flexible, and adaptive entities. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Normalization: 1NF, 2NF, 3NF

First normal form (1NF) an entity whose attributes have no more than one value for a single instance of that entity Any attributes that can have multiple values actually describe a separate entity, possibly an entity and relationship. Second normal form (2NF) an entity whose nonprimary-key attributes are dependent on the full primary key. Any nonkey attributes that are dependent on only part of the primary key should be moved to any entity where that partial key is actually the full key. This may require creating a new entity and relationship on the model. Third normal form (3NF) an entity whose nonprimary-key attributes are not dependent on any other non-primary key attributes. Any nonkey attributes that are dependent on other nonkey attributes must be moved or deleted. Again, new entities and relationships may have to be added to the data model. Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition

Whitten Bentley Dittman First Normal Form Example 1 Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman First Normal Form Example 2 Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman

Second Normal Form Example 1 Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Second Normal Form Example 2 Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Third Normal Form Example 1 Derived attribute an attribute whose value can be calculated from other attributes or derived from the values of other attributes.

Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Third Normal Form Example 2 Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman SoundStage 3NF Data Model Irwin/McGraw-Hill

Copyright 2004 The McGraw-Hill Companies. All Rights rese SYSTEMS ANALYSIS AND DESIGN METHODS 6th Edition Whitten Bentley Dittman Data-to-Location-CRUD Matrix Irwin/McGraw-Hill Copyright 2004 The McGraw-Hill Companies. All Rights rese

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