Analyzing the Problem Using Data Modeling Methods

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Analyzing the Problem Using Data Modeling
Methods
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Information

• Embodies an expansion of knowledge perceived from
  data objects examined in their proper context.

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Object

• Something identifiable in the real- world that is
  independent of other objects and contains some
  property or a set of properties that uniquely
  identifies it.

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What Users Need to Knowabout Business Objects

• What are they?
• What are their characteristics are?
• How they might affect their job functions?
• How are they related to other business objects?

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User Requirements

• Collectively comprise the facts about business
  objects that the user wants know about and have
  manipulated by the information system.

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Business Object Characteristics as User
Information Needs

• A Users information need can frequently be
  satisfied by just making them aware of various
  characteristics (properties or attributes) of
  business objects.

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Business Object

• Those objects internal or external to the
  business that comprise persons (or
  organizations), places, things, events, and
  concepts about which it is important to retain
  data.

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Business Object Categories

• Object Type Example________________
• Person An administrator, teacher,
  or student
• Place The location of agencies
  or departments
• Thing A building, machine, or
  production item
• Event Enrolling in a seminar or
  college course
• Abstract A belief about something
• concept

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Data Model

• An abstract model about real-world data objects
  that reasonably symbolizes them.

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Data Type (Object Type)

• Defines data objects together with their
  important properties and helps define the
  operations permitted on those objects and
  properties.

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Data Model

• Consists of a collection of data types.

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The Five Basic Premises of Good Business Modeling

• 1. Data is the center of modern information
  systems supported by data type identification.
• 2. The types of business data objects do not
  change very much.
• 3. Business functions change more frequently than
  data objects, but still do not change much.

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Business Modeling Basic Premises (Cont)

• 4. Business processes change much more frequently
  than functions, but often remain the same for
  long periods of time.
• 5. Information systems procedures (how
  specifications) that use data objects frequently
  change.

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Abstraction

• The ability to hide detail and concentrate on
  general, common properties of a set of data types.

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Generalized Data Type

• A higher-level data type on which the firm has to
  also retain data that consists of a group of
  individual data types.

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Generalized Data Type Example

• An example of a generalized data type is a
  DEPARTMENT data type about which it would be
  important to retain data, such as DEPARTMENT
  HEAD, ADDRESS, TELEPHONE, etc.
• The DEPARTMENT data type would encompass other
  data types, such as DEPARTMENT PERSONNEL,
  SUPPLIES, EQUIPMENT, etc.

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Complete Data Model

• The entire collection of individual and
  generalized data types by searching archive data,
  interviewing personnel, and performing a host of
  other data gathering activities.
• The more complex and greater the number of the
  data types, the more complex is the data model.

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Basic Criteria for Creatingthe Data Model

• Identify all data types (individual and
  generalized) important to the business.
• Identify the properties of those data types to
  satisfy organizational personnel information
  needs.
• Identify relationships between those data types
  and the cardinality of those relationships

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Entities

• Data types in the high-level overview are modeled
  as entities in an E/RD to symbolize the
  real-world data type.

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Defining Entities

• An Entity is normally defined by properties that
  correspond to the properties of the data type it
  represents.

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Entity Type Description

• Defines an entity by listing and describing its
  properties, those entity characteristics
  considered significant to understanding the
  entity and the sufficiently model the real-world
  data type.

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Entity Property

• A named attribute of an entity having a value
  that describes, characterizes, classifies, and
  identifies the characteristics of the data type
  that the entity symbolizes.
• An entity property associates properties of an
  entity to attribute values from a domain of
  possible values.

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Domain

• A uniquely named collection of permissible values
  for a given property.
• Domain Definition A designation that
  limits the value for an entity property to those
  specifically stated values.
• A domain definition (constraint) can also be
  stated between permissible values of entity
  properties in different data types.

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Entity Key Property

• An entity property or collection of properties
  whose values uniquely identify objects belonging
  to the set of objects in the data type or entity
  set.

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Relationship

• A connection between two entities that mutually
  associates them.

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Relationship Cardinality

• A designation on the connection between modeled
  data types that indicates how many of one type of
  business object can be related to the other
  business object.

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Entity Type Description

• Specifies and describes the properties that
  comprise the business object about which the firm
  needs to retain data.

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A PATIENT Entity Type Description

• Patient__________________________
  SOCIAL_SECURITY_NUMBER NAME STREET_ADDRESS
  CITY STATE TELEPHONE_NUMBER DOCTOR_ID_NUMBER
  NEXT_OF_KIN NEXT_OF_KIN_STREET NEXT_OF_KIN_CITY
  NEXT_OF_KIN_STATE NEXT_OF_KIN_TELEPHONE

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Logical Data Stucture (LDS)

• A list of data elements for entity properties
  that meet a reasonable need for data about a data
  type inside and outside a company.

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Subject Areas

• A major topic of interest to the enterprise that
  helps it fulfill its mission, such as
  distribution, project financing, etc.
• Good data modeling divides the enterprise into
  manageable units called subject areas.

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Subject Areas

• Subject areas encompass a manageable set of
  objects that support the overall mission of the
  enterprise from the perspective of that subject
  area.
• Subject areas (sometimes called data classes)
  relate to organizational subjects rather than to
  computer applications.

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Course Subject Areas

• A systematic method of identifying subject areas
  is to start by producing a decomposition of
  functions.
• A sub-function of the functional decomposition is
  treated as a subject area with an accompanying
  E/RD created for it to identify and model the
  sub-function's data types as E/RD entities and
  relationships.
• The essence of what constitutes a business is its
  functions and the data types they comprise, use,
  serve, and that serve them.

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Good Data Modeling Seeks To

• 1. Identify the different data types for the
  business.
• 2. Produce entity type description for those data
  types.
• 3. Specify the relationship between those data
  types including cardinality.

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Data Types in Multiple Subject Areas

• A data type that is part of more than one subject
  area provides a view of it from the context of
  that subject area.
• The appearance of a data type in multiple subject
  areas helps identify all properties of the data
  type.

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Sufficiency Requirement

• 1. Determine all subject areas of which a data
  type is part.
• 2. Create a partial entity type description for
  each subject area.
• 3. Accumulate all data type properties in a
  single full entity type description.

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Entity/Relationship (E/RD) Modeling Method

• Provides a convenient and descriptive way of
  portraying the conceptual view of data types in
  their subject areas.

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E/RD Relationship

• A relationship can be just a line connecting to
  entities or an object that exists because two
  entities have some relationship themselves.

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Identifying All Data Typesfor the Business

• Consists of creating E/RDs for all subject areas
  that contain the data types that support the
  business in those subject areas.

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Design Dictionary

• A recording method used to define users,
  processes, data, and relationships between users
  and other users or users and data for how the
  graphical icons and connections represent
  real-world objects and activities.

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Dictionary Entries for Graphs and Icons

• The dictionary is often used to describe graphic
  models, what icons on the graphic model
  represent, and the purpose for connections
  between icons.

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Design Dictionary Formatand Conventions
Prescribe

• A narrative be included where possible.
• Diagrams appear where necessary.
• Definitions be inserted for all diagram
  components.
• Individual entries be integrated.
• Adherence to conventions of punctuation.
• Summaries appear where appropriate.

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CASE Systems

• Tools used as instruments to make modeling
  methods, techniques, and procedures operational.

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Advantages of Using CASETools during the
Analysis Phase

• More comprehensive and integrated recording of
  investigation results.
• Uniform recording of analysis for all systems.
• Diagram display of analysis results in a form
  easily explained to users.
• Easy navigation through analysis specifications.
• Easily modified entries during the iterative
  actions of analysis.

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Using E/RDs During JADS

• A JAD may be set up to include all of the users
  from a particular subject area to create and/or
  review E/RDs and entity type descriptions for all
  data types included in that subject area.
• JADS can contribute to the accuracy and
  completeness of the data model in a shorter
  period of time than traditional data modeling
  methods.