NURS-8201 Week 4 Assignment Frequency And Descriptive Statistics Essay

NURS-8201 Week 4 Assignment Frequency And Descriptive Statistics Essay

NURS-8201 Week 4 Assignment Frequency And Descriptive Statistics Essay

Database Design

Health care, business, and learning institutions, among other sectors, collect and store massive data for different uses. Computer databases preserve such information to facilitate easy retrieval and management. Data can also be updated as situations necessitate. Database designs organize data according to the preferred database model. The particulars of a database design vary depending on the choices of a database designer, particularly the data to be stored and interrelationships between data elements. Generally, database designing primarily involves data classification and interrelationships’ identification. The purpose of this paper is to compare and contrast database design phases and differentiate the bottom-up and top-down design approaches.

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The 3 Phases of a Database Design

Conceptual Design

The construction of many things starts with a concept. The same case applies to database design. The database design process commences with the conceptual design. In this critical phase, the database designer develops conceptual data models detailing the primary entities, relationships, and attributes (Mahanti, 2019). It is also crucial to identify the possible constraints. The primary objective is designing a database separate from the software essentials and physical details. All the necessary data elements must be defined in this phase.

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The conceptual design has four interrelated steps. Strengholt (2020) explained that the first step is data analysis and requirements, whose defining characteristic is discovering data elements’ characteristics. Emphasis is on data that can be transformed into useful information. The second step involves entity relationship modeling and normalization. Data model verification follows, where the database designer verifies the entity relationships against the proposed system (Mahanti, 2019). The last step in this phase is distributed database design. It is not a critical phase but recommended. It involves distributing the database across dispersed locations. Eventually, the database designer gets a comprehensive conceptual representation ready for the second phase.

Logical Database Design

The second phase of the database design is the logical database. In this phase, the database designer’s primary task is designing an enterprise-wide database guided by the specifics of the preferred database model but without physical-level details. The main element differentiating this phase from others is mapping the features in the conceptual design to specific constructs (Huk et al., 2019). For instance, the logical design of a database management system includes tables, relationships, and constraints. Tables specify relations, while constraints contain security views and data validation elements.

Like the conceptual design, the logical design involves four interrelated steps. The first step is mapping the conceptual model to logical components. The concept is turned into a set of relations such as strong entities and binary relationships. The second step involves validating the logical model via normalization. The primary purpose is to unveil some new attributes or discover composite attributes. As a result, there is a high chance of adding unique attributes to the logical tables. As such adjustments occur, the database designer must ensure that characteristics in the old and new tables are wholly dependent on the primary key (Mahanti, 2019). The third step involves validating the integrity constraints where attribute domains and appropriate constraints are defined. In the last step, the database designer validates the logical model against user requirements, including transaction and security essentials.

The Physical Design

Moving from logical to physical design is akin to moving from a structure drawing to commence the building process. Physical design is predominantly about converting logical design’s data into a physical database (Davis & Yen, 2019). The database designer describes physical database essentials such as tables and constraints in this phase. Critical decisions such as index partitioning usually impact query performance significantly. The other defining element is translating the expected schemas into actual database structures (Strengholt, 2019). Next, the database designer should transform entities into tables and instances into rows. It is the same phase where attributes should be transformed into columns.

Schemas’ translation into actual database structures involves creating tablespaces and partitions. Other essential components include indexes and constraints. Mahanti (2019) explained that the database designer should separate tablespaces by differences. A suitable example is separating large and small tables and tables from their indexes. The primary objective of partitioning is to enhance performance since it is more convenient to manage each partition. Overall, a complete physical design must define all tables and columns.

Bottom-Up and Top-Down Database Design Approaches

Database development applies two main approaches, the top-down and the bottom-up technique. Although the approaches appear radically distinct, the objective is to unite a system by detailing its process interactions. The top-down approach involves moving from general to specific details of a database (GeeksforGeeks, 2020). In this case, the database designer starts with a general idea of what a database requires and asks the end-uses to describe the data stored in the database. It is highly collaborative since a database designer teams up with the end-users to determine what to keep in the database (Mahanti, 2019). Getting it right in this approach requires the database designer to understand the system in detail. Extensive planning and research are also critical.

The bottom-up approach is the reverse of the top-down approach. It is characterized by movement from specific details to a general concept. To commence the process, the database designer analyzes all the system’s interfaces while checking particulars such as forms, screens, and reports. Next, the designer works backwards to determine the specific data stored in the database (Huk et al., 2019). The approach is common where a database exists but requires some modifications or relationships.

The best approach for designing a simple database with few attributes is the top-down approach. Although time-consuming, the top-down approach is associated with a more detailed view of all the database components. The other advantage suiting a simple database is a full view of the impacts of change on the entire database and relationships. The approach is also more coherent and associated with fewer tasks than the bottom-up approach. More importantly, the collaboration between the database designer/analyst and end-users ensures that everyone involved understands the features and what a database stores.


Database design involves data organization based on the requirements of a database model. The database designer determines the type of data to store in a database and the interrelationship between its elements. The three phases of a database design include conceptual, logical, and physical designs. The database designer builds the concept in the conceptual database design and converts the concept into a logical structure in the logical phase. The physical phase involves determining how to implement the logical structure. The top-down and bottom-up approaches are the common methods used in database designing. The top-down moves from general to specific details, while the bottom-up moves from the specific to the general.


Davis, W. S., & Yen, D. C. (Eds.). (2019). The information system consultant’s handbook: Systems analysis and design. CRC press.

GeeksforGeeks.(2020). Difference between bottom-up model and top-down model.

Huk, M., Maleszka, M., &Szczerbicki, E. (Eds.). (2019). Intelligent information and database systems: Recent developments. Springer.

Mahanti, R. (2019). Data quality: Dimensions, measurement, strategy, management, and governance. Quality Press.

Strengholt, P. (2020). Data management at scale: Best practices for enterprise architecture. O’Reilly Media.

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Week4 Database Exercise Instructions


Part 1 (60%)
A) Complete Exercise 10.6 on page 325 in the Connolly text. Include a comprehensive explanation of each phase.

10.6 question is:

Compare and contrast the 3 phases of database design.



  1. B) Explain how the bottom-up design approach differs from the top-down design approach. Which approach do you believe should be used to design a simple database with a relatively small number of attributes and why?

    Include the questions with your answers.

    The submission should demonstrate your understanding of the assigned material. The submission should be in the order of 1,000+ words in length.

    The content must be original, and include supporting sentences using the terms, concepts, and theories from the assigned readings and other material (optional). The submission must paraphrase the referenced material, restrict the use of direct quotes (copy and paste) to less than 15% of the submission (the grade will be impacted if this limit is exceeded).

    There are writing guidelines in the syllabus – use good judgement, the submission must be well organized. Provide citations and references in APA style.


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