Data modeling is also considered black art by several business organizations as when practiced by the IT department of the business enterprise, it makes them more confused. Thus, IT department believes this perspective thinks data modeling doesn’t bring any real benefits to the business. However, the truth is that if you carry the steps properly, then data modeling can bring plenty of opportunities to the enterprise. Become a Data Scientist with 360DigiTMG Data Science institutes in Hyderabad. Get trained by the alumni from IIT, IIM, and ISB.
How to do data modeling rightly?
There are two fundamental guidelines for doing data analysis and data modeling properly.
Rule 1
The first rule includes utilizing a similar source from where business functions have been extracted to extract data for data modeling.
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Rule 2
To support the proper functioning of a business enterprise, only model data is required.
When you start with rule 1, you follow rule 2. You get a reliable technique in the integrated modeling approach, which helps extract relationships, candidates, entities, and attributes from the sources where extraction of business functions has taken place. This approach is utilized by both experienced as well as novice analysts. It includes the following sources
- Information flow diagrams that are derived from analysis workshops
- Development of description and function titles in the process of function modeling
- Transcripts of taped analysis interviews with experienced company managers
- Typed up additional notes derived from these interviews
Technique
This step involves the following technique
- Work through electronic formatted data sources and search for and underline noun structures that are candidate entities.
- All candidate entities and their association must be extracted into s different documents.
- Convention into actual attributes, entities, and relationships should take place of all these candidate associations and entities.
- Building ERD, which stands for Entity Relationship Diagram
- Relevant relational databases have to be designed from the entity-relationship diagram.
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Rationalizing Entities
The complete candidate entities list requires more modifications for removing false entities. For instance, an invoice is a basic example of a candidate item that is not considered an entity. A typical business item that is wrongly modeled as a proper entity is an invoice. The business entity, billing, sale, collection of entities are usually represented by invoice. These data entities are real and need to be modeled instead of pieces of paper such as invoices representing the data entities.
Converting Associations to Relationships
The identified association needs to be rationalized and transformed into a Relationship. Whether two entities are related or not is simply determined by associations that suggest that association’s name. All important information related to the association is known from this relationship. Earn yourself a promising career in data science by enrolling in the Data Science Colleges in Pune offered by 360DigiTMG.
The Entity Relationship Diagram
All the above steps are important; however, it is not possible to visualize the proper use of these steps without ERD construction. ERD is a powerful model for understanding the structures of data and an important element for designing a quality database.
Effective Layout
In the integrated modeling approach on an ERD, the symbol indicates the relationship ends, known as crow’s foot. On turning the symbol upside down, you’ll see a dead crow. This results in simple and powerful rules for designing an effective ERD layout called Dead Crows Fly East. Through this layout, the volatile and high volume entities stay on the topmost left of ERD, whereas constant and low volume entities stay to the right bottom part of ERD.
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