Things you probably don't know about Data Models and Schemas!

Critical comparison of various data models and schemas

Hierarchical Model:

Hierarchical data model is one way of organizing data into the database. It shows many one-many relationships. It is based on the concept of one parent can have many child entities but one children can have only one entity. One of the advantages of this model is that new information can be added and deleted in this model. One disadvantage of this model is that it is difficult to create complex relationships from this model.

Figure 1: Hierarchical Model

(Database Management, 2016)

Relational Model:

Data can be arranged into two dimensional tables and represented through this model. It is very easy to use and understand. It is flexible, precise, secure and data independent. Data manipulation and data definition commands can be used to query the database. (Maxlogix.blogspot.in, 2016)

Figure 2: Relational Model

Network Model:

Network model is the combination of hierarchical model and relational model. It looks like a graph and is an extension of both the above models. The nodes of the graph are represented in form of tables and relationships among them are the arrow connectors. It has all the advantages of hierarchical and relational model. (Dbmsenotes.blogspot.in, 2016)

Figure 3: Network Model

Explain and differentiate between various database technologies (Traditional file based system and database management system)

There are some differences between traditional file system and database management system:

Figure 4: File and DBMS

(Quora, 2016)

This is how you should create a Relational Database System

Discuss various approaches to database design (Top down, bottom up etc.)

Top down Approach

One parent entity can have one or more child entity. Flow of the database or application is from top to down. One module is broken down into subsequent child modules. Entities are decided first and then attributes are defined.

Bottom up Approach

In this approach various child entities can be combined together to form a parent entity. Data elements are combined together and grouped together to form data sets. Attributes are identified and then entities are formed.

Figure 6: Bottom up Approach

Centralized Approach

This approach is applied more in small organisations and it contains moderately small number of models and procedures. One database administrator handles this kind of database structure.

Decentralized Approach

This kind of database approach is applied in large organizational settings. A team of database professionals work on various models of the system. Various modules are prepared individually and then combined together to form an aggregate system.

Figure 8: Decentralized Approach

(Database Management, 2016)

 Identify some real world problems and how top down and bottom up approaches are useful. Also illustrate the importance of ERD in database design

An ERD or Entity relationship diagram is the diagrammatic representation of the database. It explains how various entities are connected with each other. It shows various entities, their attributes and relationships amongst the entities. Concepts like aggregation, generalization and specialization can also be applied within the ER diagram. There can be various methods of putting database constraints like primary key, foreign key etc. In this case study, primary keys are underlined. There are no foreign keys, howsoever.

One of the problem that is encountered while following top down or bottom up approach is that the structure applies to small organizations only. This structure nullifies in case a complex database is to be created. In top down approach, one parent can have one or more child entities while their corresponding child entities can have just one child entity. This is a real life constraint, as there can be more than one sub entities.

Same concept applies for bottom up approach in which one or more entities can be grouped together to form a composite entity. Estimation of attributes has to be done before estimating the entity. (Database Management, 2016)