Data Modeling Software–Data modeling is the process of applying techniques and methodologies to data (data requirements) to transform it into a useful form. This process transforms complex software designs into simple, easy-to-understand diagrams with data flows.
A data model consists of entities, which are objects or concepts that you want to keep track of, and become tables in your database. Products, vendors, and customers are all examples of potential entities in the data model.
The data model explicitly determines the structure of the data. A data model is usually specified in data modeling notation by a data expert, data librarian, or digital humanities scholar. These notations are often presented in graphical form.
The main goal of a data model is to support the development of information systems by providing a definition and format for data. According to West and Fowler (1999), “Data compatibility can be achieved if this is done consistently system-wide.
Why use a data model?
The main goals of using a data model are:
-Ensure that all data objects required by the database are accurately represented. Missing data will result in incorrect reports and incorrect results.
-Data models help design databases at the conceptual, physical, and logical levels.
-Data model structures help define relational tables, primary and foreign keys, and stored procedures.
This data represents machine-readable information as opposed to human-readable information. For example, if customer data does not point to specific product purchases, it is meaningless to the product team. Similarly, if an ID isn’t associated with a specific price point during a purchase, the marketing team won’t use the same data.
It is now clear that data modeling is a necessary foundational task. This makes it easy to store data in a database and has a positive effect on data analysis. Critical to data management, data governance and data intelligence.