Conceptual business model. You’ll construct a conceptual business model similar to the one we discussed in Module 1.

computer science


The final assessment for course 1 is peer-graded. While it won’t incorporate every idea we’ve covered in the course, it will include key elements from each of Modules 1 through 4 in one integrated exercise.

The assessment has four parts:

1.    Conceptual business model. You’ll construct a conceptual business model similar to the one we discussed in Module 1.

2.    Relational data model. You’ll then design a simple relational data model to represent some of the ideas from your conceptual model (like in Module 2), and describe what types of systems you think the data might come from (Module 1).

3.    SQL queries. You’ll write two SQL queries to extract an interesting data set from your data model (Module 3)

4.    Sensitive data and data quality issues. Finally, you’ll identify whether your model contains certain types of sensitive data, and assess where your model might be susceptible to data quality issues (Module 4).

Detailed Instructions

Submission file formats. The graphical items in the assignment may be drawn and scanned or constructed using any convenient software, but the submitted file should be in a common file format like PDF (preferred), JPG, Word, PowerPoint or Excel. Regardless of method, the submission must be neat and legible to facilitate peer review. 

Part 1: Conceptual business model. Construct a conceptual business model for an industry or business that you are familiar with or have interest in. Visually it should be similar to the one we illustrated in Module 1, Video 2.

·         Your model should represent at least 10 ideas

·         It should visually represent one to one, many to one, or many to many relationships among ideas

Part 2: Relational data model. Take a subset of the ideas from the conceptual model you constructed in Part 1 and design a simple relationship model similar to the ones we discussed in Module 2, Video 4

·         Your model should have at least 5 tables

·         You should include at least 20 attributes, or fields, in your model (20 total across all tables, not per table)

·         Your model should be normalized

·         Identify the primary key in each table, and state whether it is a natural or surrogate key

·         For each relationship between tables, identify any foreign keys needed to define the relationship

·         For each table, identify what type of system or systems you think the data might come from, like those we discussed in Module 1, Video 6.

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