Assignment Definition: Use The Data Model Designed In Week 2

Assignment Definitionuse The Data Model Designed In Week 2 This Data

Assignment Definition: Use the data model designed in Week 2. This data model will be reviewed and taken from the conceptual model to logical and physical model status. Make sure you define the following: 1. Select database management system (Oracle, SQL Server, MYSQL, etc) and identify the data types and sizes for all attributes. 2. Make sure all relationships have been addressed and corrected. 3. Review data model to make sure data model is in at least 3rd normal form (as defined by the normalization process).

Promoting Self-Esteem in Adolescents: The Influence of Wellness Factors Myers, Jane E; Willse, John T; Villalba, José A Journal of Counseling and Development : JCD; Winter 2011; 89, 1; ProQuest pg. 28

Paper For Above instruction

The task at hand involves transforming a conceptual data model developed in week 2 into a fully operational logical and physical data model, suitable for implementation within a chosen database management system (DBMS). This process requires meticulous attention to detail, ensuring that the data model accurately represents the real-world entities and relationships pertinent to the subject matter—particularly aspects concerning promoting self-esteem in adolescents and associated wellness factors, as referenced in the article by Myers, Willse, and Villalba (2011).

Selecting the Database Management System (DBMS)

The initial step in this process is to select an appropriate DBMS. Options include Oracle, SQL Server, MySQL, or others, each with specific features and data type specifications. For illustration, let's assume the use of MySQL due to its prevalence, open-source nature, and ease of use in academic and practical applications.

Defining Data Types and Attribute Sizes

Once the DBMS is selected, the next step is to map each attribute identified in the conceptual model to specific data types supported by MySQL, along with suitable attribute sizes. For example, if the conceptual model includes entities such as Adolescents, WellnessFactors, and SelfEsteemScores, attributes like Names might be assigned VARCHAR(100), Age as TINYINT, and scores as DECIMAL(4,2).

For instance, the Adolescents table may include:

- `adolescent_id`: INT, PRIMARY KEY, AUTO_INCREMENT

- `name`: VARCHAR(100)

- `age`: TINYINT

- `gender`: ENUM('Male', 'Female', 'Other')

The WellnessFactors entity might include:

- `factor_id`: INT, PRIMARY KEY, AUTO_INCREMENT

- `description`: VARCHAR(255)

And a SelfEsteemScores table:

- `score_id`: INT, PRIMARY KEY, AUTO_INCREMENT

- `adolescent_id`: INT, FOREIGN KEY referencing Adolescents

- `date_assessed`: DATE

- `score`: DECIMAL(4,2)

Ensuring Referential Integrity through Relationships

Relationships between entities such as adolescents and wellness factors, or self-esteem scores, should be explicitly modeled via foreign keys. The relationships must be reviewed to ensure they are correctly implemented, with appropriate constraints to maintain data integrity, such as ON DELETE CASCADE or SET NULL options where relevant. Many-to-many relationships—such as adolescents and multiple wellness factors—should be resolved using junction tables, for instance, `Adolescent_WellnessFactors`.

Normalizing the Data Model to at Least 3rd Normal Form

The normalized data model minimizes redundancy and dependency. First, ensure no repeating groups or arrays exist (1NF). Then, ensure that non-key attributes depend solely on the primary key (2NF). Finally, verify that no transitive dependencies exist—that is, non-key attributes should not depend on other non-key attributes (3NF).

For example, if the WellnessFactors table includes a description and category, and the category depends only on the wellness factor, normalization ensures such dependencies are correct. Regular review and restructuring of data tables eliminate anomalies and ensure data integrity.

Conclusion

Transforming the conceptual model into a logical and physical implementation involves selecting a suitable DBMS like MySQL, defining specific data types and sizes for attributes, ensuring all relationships are correctly established and referential integrity is maintained, and normalizing the database to at least 3NF. This process ensures a robust, efficient, and scalable database system capable of supporting research on promoting self-esteem among adolescents within the context of wellness factors, as discussed by Myers, Willse, and Villalba (2011).

Effective database design is foundational for collecting, storing, and analyzing data accurately, ultimately contributing to interventions that foster adolescent development and well-being.

References

  • Myers, J. E., Willse, J. T., & Villalba, J. A. (2011). Promoting Self-Esteem in Adolescents: The Influence of Wellness Factors. Journal of Counseling and Development, 89(1), 28-36. https://doi.org/10.1002/j.1556-6678.2011.tb00023.x
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