COURSE 2695 | 2-day SESSION
Building the Logical Data Model

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Course Outline

Section I. Introduction of key concepts

• Business Process Management concepts and application
  
• Learning objectives
  
• Course agenda
  
• Introductions
  

Section II. Process modeling overview
Chapter objectives are: 1) Review the key techniques for modeling business processes; 2) Gain knowledge of the approach for modeling business processes and the needs for raw data.

• Logical vs. physical models
  
• Process decomposition
  
• Data flow modeling
  
• Event Modeling
  
• Documenting process properties
  
• Steps in modeling a business process
  

Section III. Introduction to data modeling principles
Chapter objectives are: 1) Learn the basic components of a data model; 2) Introduce the key concepts and assumptions necessary for building a logical data model; 3) Acquire the level of proficiency needed to be able to identify and document components from existing documents and systems.

• Logical vs. physical data modeling
  
• Documenting data requirements of a process
  
• Definition of the components of a data model
  
• Properties of a data model and building foundation
  
• Examine the need for defining the scope of the data modeling effort
  
• Finding data model components in the physical world of automated and manual systems
  

Section IV. Describe the components of a Data Model
Chapter objectives are: 1) Gain an understanding of the differences between the components of a logical data model and the physical representation and storage; 2) Acquire basic skills to identify and describe the components of a data model.

• Naming and describing entities
  
• Classification of entities
  
• Identifying and describing attributes
  
• Types of attributes
  
• Select an unique entity identifier
  
• Definition of relationships and cardinality
  
• Documentation of relationships
  
• Entity relationship diagram
  
• Identification and incorporation of business rules
  

Group Activity: Identify data model components
The objective of this activity is to have the participants examine documentation of a process and existing forms and reports to identify and document the components of a data model. The participants will be asked to create the following deliverables:

1. Identify and document data model components
   
2. Describe significant properties of the components
   
3. Create initial Entity Relationship Diagram (ERD)
   
4. Identify and apply business rules
   

Section V. Creating the Conceptual Data Model
Chapter objectives are: 1) Gain knowledge of the top down approach for creating a data model and the uses and value of an enterprise data model; 2) Acquire knowledge and skills to create a conceptual data model; 3) Integrate the views of the scope of the modeling effort provided by the process and data models.

• Definition and need for building a conceptual data model
  
• Top down approach and steps
  
• Introduction of the enterprise data model and its uses
  
• Partition the process and data models
  
• Establish the business area for modeling the data requirements of a number of business processes or subset of the business
  
• Create conceptual model in parallel with creation of high level process model
  
• Integration of process and data models to ensure consistency in defining the scope of the process and data modeling efforts
  

Group Activity: Create the conceptual data model Information will be distributed on the results of the efforts to define the scope of the modeling and analysis project, excerpts from a Project Charter, and the initial high-level process model will be examined by the participants to create the following items:

1. Define scope of data modeling effort
   
2. Conceptual data model components and ERD
   
3. Initial documentation of properties of data model components
   
4. Refinement of initial scope based on integrating process and model views
   

Section VI. Building the Logical or Fully Attributed Model
Chapter objectives are: 1) Gain the working knowledge of the different approaches for completing the logical data model; 2) Acquire skills for creating the data model by defining and consolidating the needs of individual processes

• Definition and uses of the fully attributed model
  
• Top down vs. bottom approach to data model creation
  
• Parallel development of process and data models
  
• Specify the data requirements of individual sub-processes
  
• Document individual data requirements of each sub-process as subsets of data model
  
• Integrate individual process views of the data model into an overall model for the business process or business area
  
• Integrating top down and bottom up data requirements and definitions
  

Group Activity: Create the fully attributed data model
The objective of this exercise is to expand the initial conceptual data model and create the logical or fully attributed data model. Completion of the assignment will be broken down into the following parts:

1. Following the top down approach, extract from a series of fact-gathering sessions the knowledge needed to expand the objects and definitions created in the previous exercise
   
2. Additional information will be provided on a number of sub-processes to identify their data requirements and define their subsets of the data model based on individual needs
   
3. Integrate the individual views or subsets of the data model required by each process into an overall model
   

Section VII. Refining the Data Model
Chapter objectives are: 1) Assess the quality and validity of the model and determine additional steps to resolve incomplete definitions and anomalies; 2) Apply the rules for further classification of entities; 3) Normalize the data model.

• Refining the data model to include the classification of entities into super types and subtypes
  
• Identify and eliminate redundant relationships
  
• Identify entities requiring additional definition and resolution of anomalies
  
• Describe data normalization forms and rules
  
• Normalize the data model
  

Group Activity: Refine the data model
A partially complete subset of the data model will be handed to the participants to review and complete the following:

1. Assess the quality of the data model and determine the needed steps to addresses the inconsistencies or weaknesses identified
   
2. Identify opportunities and classify entities into super types and sub-types
   
3. Identify and eliminate redundant relationships
   
4. Normalize the data model
   

Section VIII. Mapping processes and data
Participants will gain the skill level needed to apply proven techniques to ensure the consistency of the process and data model views. In addition, the participants will acquire the knowledge to work with the documented needs for information and its impact on the data model.

• Create a CRUD matrix
  
• Create an Entity Life Cycle diagram
  
• Review the concepts and approach for identifying information needs
  
• Mapping information needs to data model
  

Group Activity: Map process and data models
A number of process diagrams, documentation of their properties, and a subset of the data model will be provided for the participants to create a partial CRUD matrix. A second part of the assignment will be for the participants to create an Entity Life Cycle diagram based on the information provided on a set of elementary processes.

Section IX. Transition to design
This module will provide the participants with a view of the next steps in the process, the design of the physical databases and the need to optimize performance.

• De-normalization
  
• Steps in the transition
  
• Physical data model