Data Modelling

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Course Overview

Data modeling in software engineering is the process of creating a data model for an information system by applying formal data modeling techniques.Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders, as well as potential users of the information system

At the end of the training, participants will be able to:

Pre-requisite

A basic knowledge of data modeling concepts and techniques is required.

Duarion

4  days

Course Outline

  1. Definitions
  2. Benefits of logical data modeling
  3. Data modeling vs. physical database design
  4. Roles involved in data modeling
  5. Steps in the data modeling process
  6. Example data model
  1. Identifying entities
  2. Validating entities
  3. Documenting “instances” of entities
  4. Distinguishing entities from attributes
  5. Naming entities
  6. Starting an Entity/Relationship (E/R) diagram
  1. Identifying significant relationships
  2. Determining the “cardinality” or “degree” of a relationship
  3. One-to-One
  4. One-to-Many
  5. Many-to-Many
  6. Determining whether a relationship is optional or mandatory
  7. Giving a relationship a name
  8. Documenting the relationships in the E/R diagram
  9. Walking people through an E/R diagram
  10. Resolving Many-to-Many Relationships
  11. Real-world examples of many-to-many relationships
  12. Why many-to-many relationships are broken down into simpler relationships
  13. Identifying “association” or “intersection” entities
  14. Documenting the new relationships in the E/R diagram
  1. Defining and categorizing attributes
  2. Domains and integrity rules
  3. Unique identifiers/primary keys
  4. Foreign keys
  5. Occurrence population
  6. Normalization: validating the placement of each attribute
  7. Attribute does not repeat (first normal form)
  8. Attribute is dependent on its entire UID (second normal form)
  9. Attribute is dependent only on its UID (third normal form)
  1. Identifying subtypes: real-world examples of subtypes and supertypes
  2. Determining when entities are similar
  3. UIDs
  4. Attributes
  5. One-to-one relationships
  6. Creating subtypes and supertypes
  7. “Type” entities
  8. Using subtypes to apply fourth normal form
  9. Establishing the relationships of the sub- and super-entities to other entities
  10. Mutually exclusive vs. non-mutually exclusive subtypes
  11. “Role” entities to handle complex subtypes
    1. Real-world examples of recursive relationships
    2. Discovering recursive relationships
    3. Determining whether the relationships are optional or mandatory
    4. Documenting the new relationships in the E/R diagram
    5. Hierarchical vs. Network recursive relationships
    6. “Structure” or “Bill of Materials” entities: fifth normal form
  • 1.Relational database objects: tables, views, indexes, etc.
  • 2. Mapping logical objects to physical objects
  • 3.Denormalization
    • Why
    • How
    • Pros/Cons
  • 4. Distributing databases
  • 5. Referential integrity

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