Introduction to data modeling 
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Data modeling is the process of identifying what data needs to stored by the application and then creating data structures accordingly. The emphasis is on identifying the data, organizing the data and providing a structure to the data. Data modeling involves the following key steps:
  • Identifying relevant entities
  • Identifying the attributes of entities
  • Organizing the data
  • Identifying the relationships between entities
  • Creating a data model diagram to visually represent the entities and their relationships

 Is data modeling important?

Data model helps represent all the data entities completely and accurately. An effective data model ensures that a system built on its foundation will meet unanticipated processing requirements for years to come i.e. the system does not need constant reconstruction to accommodate new business requirements and processes. Also, since the data model is represented pictorially, it is easily understood, and can be used to communicate the data structure to the business users, technical team.
How important is data modeling for creating an application using OrangeScape?

OrangeScape based application development centers around data model! Unlike traditional development methods, where the front-end GUI and the back-end are developed separately and integrated during the course of SDLC, OrangeScape's design mandates that we start with data model and progress to form and process design. This is an important aspect of OrangeScape as it eliminates integration, which is man-power drain and error prone. This implicit constraint imposed by OrangeScape paradigm eliminates this wastage and makes application development easier.

What's Next?

Now that we know how important data modeling is for creating applications using OrangeScape, let's try to create the data model for our example application. This will help us get familiarized with the data modeling process.