Assignment 4: Database Modeling And Normalization Due Week 4
Assignment 4 Database Modeling And Normalizationdue Week 4 And Worth
Develop an effective Entity Relationship Model (ERM) Diagram considering HR core functions such as hiring, promotions, policy enforcement, benefits management, and training. Outline the iterative steps and factors involved in creating the ERM, and analyze risks associated with skipping these steps. Select and rank at least five entities necessary for the personnel database, specifying components for time-variant data related to policy enforcement and training management. Diagram a 1:M relationship model for salary history, job history, and training history of employees. Plan each normalization step to achieve 3NF for the five entities, documenting assumptions and justifications. Provide diagrams including dependency diagrams and multivalued dependencies for the entities, ensuring clarity and adherence to academic formatting standards. Include appropriate charts or diagrams created with familiar tools, imported into the document, to support the ER and normalization processes.
Paper For Above instruction
Developing an effective Entity Relationship Model (ERM) for a human resources (HR) database for a government agency requires a systematic approach that captures the core functions and responsibilities of HR management while ensuring data integrity and efficiency. The process involves detailed planning, iterative development, and risk mitigation strategies to prevent structural inefficiencies or data anomalies. This paper discusses the steps involved in ERM development, considerations for iteration, risk factors if steps are neglected, selection of critical entities, handling of time-variant data, and normalization processes designed to reach Third Normal Form (3NF). Additionally, it provides a possible relational diagram for tracking salary, job, and training histories within an employee-centered database system.
Development of Effective ER Modeling
The first step in constructing an ER model is requirements gathering. This involves comprehensive discussions with HR stakeholders to understand functional needs, data inputs, and reporting requirements. These conversations help translate business rules into data entities and relationships. Next, conceptual modeling entails identifying key entities, their attributes, and relationships. The process adopts an iterative approach — refining the model through multiple review cycles, including validation with users and system analysts to ensure completeness and accuracy.
During development, it is crucial to identify cardinalities and participation constraints, delineating how entities interact and the minimum and maximum number of occurrences. For example, an employee can have multiple jobs during their tenure, but each job record is linked to a specific employee. Formalizing these relationships in a diagram ensures clarity and correctness. The iterative process also involves normalizing data structures to avoid redundancy and update anomalies, described further in the normalization section.
Factors and Risks in ER Model Development
Key factors influencing successful ER modeling include stakeholder participation, thorough understanding of business processes, and iterative validation. Omitting stakeholder validation can lead to incomplete models that do not reflect real-world practices, resulting in data inconsistencies. Rushed development without iterative refinements may overlook dependencies or multivalued attributes, causing anomalies during data manipulation. Risks from inadequate steps include inefficient data retrieval, increased storage costs, compromised data integrity, and challenges in evolving the database to meet future requirements. Properly executing these steps ensures scalability, accuracy, and robust data management.
Critical Entities for HR Database
Selecting core entities involves prioritizing those fundamental to HR functions. The five essential entities are:
- Employee
- Position
- Salary
- Training
- Policy
These entities are ranked based on their centrality to HR operations: employee records serve as the hub; position and salary data track compensation and role history; training manages professional development; and policies enforce HR standards.
Each entity must include key attributes: Employee (ID, name, contact info, hire date), Position (position ID, title, department), Salary (salary amount, effective date, employee ID), Training (training ID, course title, date, employee ID), Policy (policy ID, type, description, enforcement date).
Handling Time-Variant Data
To manage policy enforcement and training over time, components such as effective dates, expiry dates, and revision histories are vital. For example, the Policy entity includes fields like enforcement date and revision number to track changes. Similarly, training records include completion date and validity period to reflect current qualifications. Versioning attributes and date ranges facilitate temporal data analysis, enabling management to review historical policy updates or training completions efficiently.
Entity Relationship and Dependency Modeling
For salary, job, and training histories, a 1:M relationship model is appropriate. For example, one employee can have multiple salary records over time, each with its own effective date. Similarly, job history is captured as multiple records per employee, each indicating a position held and duration. Graphical models using dependency diagrams depict these relationships and dependencies clearly.
An illustrative example: Employee (1) — (M) Salary, JobHistory, TrainingHistory, with each child entity linked to Employee via foreign keys. For salary history, attributes like salary amount and effective period establish temporal dependencies, allowing retrieval of historical salary data efficiently.
Normalization to 3NF
Normalization reduces redundancy and dependency anomalies, facilitating data integrity. The process involves the following steps:
- Unnormalized Form (UNF): Data stored without regard to structure, e.g., multiple employee attributes duplicated.
- First Normal Form (1NF): Eliminate repeating groups by creating separate records or tables. For example, separate salary records per employee with atomic values for salary and date fields.
- Second Normal Form (2NF): Remove partial dependencies. Attributes must fully depend on the primary key. For example, in Salary table, salary amount depends entirely on salary record ID, not partially on employee ID.
- Third Normal Form (3NF): Remove transitive dependencies. For instance, attributes like department name are dependent on position, so normalization involves creating a Department entity related to Position.
Applying this step to the five entities ensures a lossless, dependency-preserving schema that supports data consistency and integrity across updates and queries.
Conclusion
Constructing a reliable HR database for a government agency involves meticulous planning of ER models and normalization processes. Critical considerations include stakeholder collaboration, iterative refinement, risk mitigation, and meticulous dependency analysis. Properly designed, such a system ensures efficient data management, facilitates HR functions like policy enforcement, training tracking, and salary history, and supports ad hoc reporting. The disciplined use of ER diagrams, dependency analysis, and normalization to 3NF fosters a scalable and robust personnel management system that aligns with enterprise data standards and best practices.