Question

Data modeling is a key component to creating a database. There are all different aspects of data modeling, with concerns from various things to the methodology of modeling, to software, to interfaces used between each model.

Paper: Write a 3 page paper (at model 1.2 spacing, 12 pt font, 1 inch margins with at most one half of the paper including a figure, citations not included) on some aspect of data modeling in industry. You must use reliable academic and industry resources. You must have at least one resource that connects your topic to industry. Write up should not exceed 4 pages, excluding citations. Example topics include:

• Data modeling challenges in transportation industry (logistics)

Answer 1

Data modeling:

1. Definition: In software engineering, data modeling is the process of creating a data model for the data to be stores in a data base.

2. Data modeling answers a set of specific questions that are relevant to any data processing application. What are the primary data objects to be processed by the system? What is the composition of each data object and what attributes describe the object? Where do the objects currently reside? What are the relationships between each object and other objects? What are the relationships between the objects and the processes that transform them? To answer these questions, data modeling methods make use of the entity relationship diagram. The ERD enables a software engineer to identify data objects and their relationships using a graphical notation.
3. Different types of data models are:

1. Internal data model – It deals with the physical representation of the data base on the computer and thus it is also known as physical model.
2. Conceptual data model – It deals with the logical structure of the database and is also called as logical model.
3. External data model – It deals with the user’s view of data and is also known as view level.

4. Challenges in data modeling are:

• The user may not be having proper documents regarding the requirements of the new software.
• Sometimes the requirements and demands of the user will be more.
• Selection of data modeling tools requires wise decision.
• No proper plan in the architecture of the project.
• Modeling of the software should happen at the right time in the software development cycle.
• Sometime user need training .
• Data modelers may not be able to understand the business requirements of the users.

. Data modelers may not be able to understand the business requirements of the users.
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