BIS 261 - Chapter 8 - Structuring System Data Requirements

Which SDLC phase is requirements structuring?

Analysis

event

data manipulation operation (insert, delete, or update) that initiates the operation

degree

- a relationship is the number of entity types that participate in that relationship.

triggering operation

- aka trigger - assertion or rule that governs the validity of data manipulation operations such as insert, update, and delete components - user rule - event - entity name - condition - action

relationship

- an association between the instances of one or more entity types that is of interest to the organization.

optional attribute

- an attribute that may NOT have a value for every entity instance

multivalued attribute

- an attribute that may take on more than one value for each entity instance - NOT synonymous with a candidate key

associative entity

- an entity type that associates the instances of one or more entity types - contains attributes that are peculiar to the relationship between those entity instances

domains

- enforces constraints on valid values for attributes

deliverables and outcomes

- entity-relationship (E-R) diagraming - set of entities about data objects are stored in repository project dictionary, or data modeling software

packaged data model benefit: cost reduction

- ex: projects with purchased models take less time and cost less because the initial discovery steps are no longer necessary, leaving only iterative tailoring and refinement to the local situation.

packaged data model benefit: consistent and complete

- ex: purchased data models are very general, covering almost all options employed by the associated functional area or industry

packaged data model benefit: validated

- ex: purchased models are proven through extensive experience.

entity-relationship (E-R) diagraming

- have entities and relationships - graphical representation of an E-R model expressed in terms of: - Entities in the business environment - Relationships among those entities - The attributes (properties) of both the entities and their relationships

purchased conceptual data models

- provide generic models that can be customized for a particular organization's business rules. - database patterns examples - Universal data models are templates for core subject areas such as customers, products (etc.) - Industry-specific data models are generic and designed for specific industries (health care, telecommunications, etc.) benefits - Validated - Cost reduction - Anticipate future requirements, not just initial requirements - Facilities system analysis - Consistent and complete

event entity type

- should be named for the result of the event, not the activity or process of the event

entity instance

- single occurrence of an entity - aka an instance

business rules

- specifications that preserve the integrity of the logical data model the list - entity integrity - domains - triggering operations - NOT unary relationship

respository

- storage - the mechanism that links the data, processes, and logic models of an information system

perspectives of data modeling

- top-down approach - bottom-up approach dude it's like with teams...

relationships

between entities represented by lines drawn between entities

entities

categories of data, represented by rectangles

user rule

concise statement of the business rule to be enforced by the triggering operation

condition

condition that causes the operation to be triggered

entity

person, place, object about which the organization wishes to maintain data

T or F: In an E-R diagram, system outputs and relationships are the same as data flows from data flow diagrams.

False

action

action taken when the operation is triggered

required attribute

an attribute that must have a value for every entity instance

referential integrity constraints

- concerning the relationships between entity types

common mistake: confusing E-R diagrams and data flow diagrams

- data entities : sinks - relationships : data flows

bottom-up approach

- derives the data model by reviewing specific business documents (computer displays, reports, form)

top-down approach

- derives the data model from an intimate understanding of the business

conceptual data model (CDM)

- detailed model that captures the overall structure of organizational data and is independent of any database management system or other implementation considerations - Usually done in parallel with other requirements analysis - All team member work done and stored in a repository

weak entity

- An entity that displays existence dependence and inherits the primary key of its parent entity. - For example, a DEPENDENT requires the existence of an EMPLOYEE. - shown as a box in a boxz

data modeling software

- Data elements included in the data flow diagram (DFD) must appear in the data model and vice versa - Each data store in a process model must relate to business objects represented in the data model

CDM Process

- Develop a data model for the current system - Develop (or purchase) a new conceptual data model that includes all requirements for the new system - During design, final data model matched with systems inputs/outputs and translated into a physical design - Project repository links all design and data modeling steps taken during the SDLC

condition stub

- If there is a situation where a decision table has a logic decision where an employee data type can have one of two values

entity type

- a collection of entities that share common properties or characteristics - described just once in a data model - many instances of that type may be represented by data stored in the database - aka entity class name - singular noun - descriptive and specific to the organization - concise

supertype

- a generic entity type that has a relationship with one or more subtypes

binary relationship

- a relationship between instances of two entity type - the most common type of relationship encountered in data modeling

A reason some developers believe a data model is the most important part of the information systems requirement?

Data captured during data modeling is crucial to the design of computer screens.

entity name

name of the entity being accessed and/or modified

Requirements Determination Questions for Data Modeling

1. What are the subjects/objects of the business? [data entities and their descriptions] 2. What unique characteristic (or characteristics) distinguishes each object from other objects of the same type? [primary key] 3. What characteristics describe each object? [attributes and secondary keys] 4. How do you use these data? [security controls and understanding who really knows the meaning of data] 5. Over what period of time are you interested in these data? [cardinality and time dimensions of data] 6. Are all instances of each object the same [supertypes, subtypes, and aggregations] 7. What events occur that imply associations among various objects? [relationships and their cardinality and degree] 8. Is each activity or event always handled the same way or are there special circumstances? [integrity rules, minimum and maximum cardinality, time dimensions of data]

Detailed Requirements

1. What types of people, places, things, materials, events, etc. are used or interact in this business, about which data must be maintained? How many instances of each object might exist? 2. Might this distinguishing feature change over time or is it permanent? Might this characteristic of an object be missing even though we know the object exists? 3. On what basis are objects referenced, selected, qualified, sorted, and categorized? What must we know about each object in order to run the business? 4. That is, are you the source of the data for the organization, do you refer to the data, do you modify it, and do you destroy it? Who is not permitted to use these data? Who is responsible for establishing legitimate values for these data? 5. Do you need historical trends, current "snapshot" values, and/or estimates or projections? If a characteristic of an object changes over time, must you know the obsolete values? 6. That is, are there special kinds of each object that are described or handled differently by the organization? Are some objects summaries or combinations of more detailed objects? 7. That is, are there special kinds of each object that are described or handled differently by the organization? Are some objects summaries or combinations of more detailed objects? 8. Can an event occur with only some of the associated objects, or must all objects be involved? Can the associations between objects change over time (for example, employees change departments)? Are values for data characteristics limited in any way?

entity-relationship data modeling (E-R model)

A detailed, logical representation of the entities, associations, and data elements for an organization or business area.

unary relationship

A relationship between instances of a single entity type - ex: if one person may only be married to one other person