Computer Science

Comparison of inheritance in the EER model and inheritance in the OO model

Inheritance is a mechanism of creating an object or a class upon another thing while still maintaining similar execution. Therefore, in inheritance, a sub-class is stemmed from an existing base class that develops a hierarchy of classes. The subclass acquires traits and behaviors from the base class or object, embodied in various models like the EER and OO model (Elmasri & Navathe, 2017). The inheritance in EER and OO model allows the creation of classes on existing properties. In addition, the inheritance of the two models enables the new implementation to maintain the same interfaces and expand software through public properties independently.  The inheritance between EER and OO models varies in various ways. First, the EER model develops more precise designs to the database plan, while the OO model represents problems and data traits accurately (Elmasri & Navathe, 2017). Besides, the OO model reflects inheritance as a class, while the EER model depicts inheritance as objects broadly.

Additionally, due to inheritance, the properties of the entities reflected in EER are shown in the form of relationships. At the same time, in the OO model, objects that have the same functionalities are categorized together and connected to diverse classes (Elmasri & Navathe, 2017). Also, inheritance in the EER model can be converted easily into relational databases, but inheritance in the OO model cannot be practically executed in database systems because it is more of a theoretical style. Furthermore, due to inheritance, the type of information in the OO model can be reused in diverse classes, which minimizes the cost of maintaining the same information in various regions (Elmasri & Navathe, 2017).  However, in comparison, the type of data in the EER model cannot be reused because inheritance in the model lacks data manipulation of language because it is an extensive abstract concept (Elmasri & Navathe, 2017). The inheritance of the EER model is easy to comprehend, and it has precise and well-described properties and their relations between them, but the inheritance in the OO model is quite complicated to understand and create.

The differences between structured, semi-structured, and unstructured data

Data is a collection of facts from statistics, observations, or descriptions used in making decisions. Data can be classified as structured, semi-structured, or unstructured. These three types of data are in various ways. First structured data is data whose properties can be addressed quickly for operational assessment. Structured data is usually organized in a database, and all data can be maintained in a database with rows and columns. The structured data has relational digits and can be represented in a preplanned field (Wethington & McDarby, 2015).

On the other hand, semi-structured data do not reside in a relational databank but consists of various organizational characteristics that enable it to be assessed quickly. However, some processed, semi-structured data can be maintained in a relational folder (Wethington & McDarby, 2015). Finally, unstructured data is not arranged in a predefined approach, and therefore, it is not suitable for a relational database. The type of data is prevalent in IT structures is employed by firms in analytics applications.

Therefore, structured data follows an approach that is defined and to can be observed in every application. On the other hand, the unstructured data does not follow any strict procedure, and therefore any person can determine any suitable order for them to follow in any situation (Wethington & McDarby, 2015). Semi-structured takes traits from both structured and unstructured classifications. Semi-structured data is consistent and has qualitative aspects, and can be customized based on instances lined with unstructured data (Wethington & McDarby, 2015).  Hence, structured data can be managed effectively and ensues a rigid model. Unstructured data is complex, and any qualitative data can be difficult to e in a relational folder, and semi-structured data possesses properties of both structure and unstructured data. Also, some properties such a scalability and query performance differ in the three types of data. Scalability in structured data is difficult; semi-structured scaling is more straightforward, while unstructured data is more scalable. For query performance, structured query enables complex joining, semi-structured allows queries over anonymous nodes while unstructured allows only textual queries.