Understanding the Database: Concepts and Models

This document provides an in-depth understanding of database systems, including the concepts and models such as hierarchical, network, and relational models. It discusses the advantages of using database systems over file systems and the disadvantages of using DB systems. The document also covers topics like data normalization, entity relationship diagrams, and data manipulation and definition languages.

Database
Database Modelling
Student Name
Institutional Affiliation

Table of Contents
Introduction...............................................................................................................................................3
Understanding the database.....................................................................................................................3
Database Systems Versus File systems.................................................................................................3
Merits of Database Systems over the File systems..........................................................................4
Disadvantages of using DB systems..................................................................................................5
Data Models...........................................................................................................................................5
Hierarchical Model............................................................................................................................5
Network Model..................................................................................................................................6
Relational Model................................................................................................................................7
Top-down Versus Bottom-Up Object DB design.................................................................................8
Top-Bottom Approach......................................................................................................................9
Conceptual Modelling...............................................................................................................................9
Entities....................................................................................................................................................9
Crown’s Foot Notation Design............................................................................................................10
Logical modelling....................................................................................................................................10
Database Normalization......................................................................................................................10
Entity Relationship Diagram..............................................................................................................11
Physical Modelling...................................................................................................................................12
Data Definition Language...................................................................................................................12
Data Manipulation Language.............................................................................................................13
Passenger Table...................................................................................................................................13
Plane Table.......................................................................................................................................13
Employee Table...............................................................................................................................13
Airline Table....................................................................................................................................13
List of References....................................................................................................................................14

Introduction
Understanding the database
In understanding the concepts in database, one must be able to understand the concepts of
how file storage systems have evolved. Ideally for one top understand the thoughts of a database,
it is good for one to perceive how information strategies capacities have been created. Notably, it
will be good for one to appreciate all the needs for grasping the thoughts from the applications of
such file based systems and how database systems came to functions. DB structures are the usage
of an item that supports much on the creation, data upkeep, and control of such data
electronically. DB is the collection of tables which are secured midway and must be associated.
The association between and among related substances makes the entire DB. For this
circumstance, the main scenario is empowering the need for appreciating the sections of
understanding the database in general and specifics empower one to appreciate the case
circumstance by understanding the DB, hypothetical, authentic and physical showing.
Remarkably, For one to understand the major fundamentals sorts of exhibiting, this will rely the
fathom the stray pieces of database and the ways such will help in structuring and displaying.
Database Systems Versus File systems
Ideally, for one to understand the relationship or comparison with regards to the two
major systems namely the database systems as well as the File-Based systems, the most ideal
methodology to tackle it by preparation of records.. Ideally, there is a great deal of information
repetition in the record framework when contrasted with database frameworks. Information
abundance insinuates the concept of data redundancy. Data duplication, assuming that we
managing the school data where in this case an understudy student is to be enrolled for just
courses, in comparing it with another student understudy nuance will have to be secured more
than once thus leading to more accumulation than what is required (Carlsol, 2015). Data

overabundance every now and again prompts higher limit costs and thus leading to poor
accessibility with regards to timing and even available resources. In this case, the other
impediment is that there exists a lot of data inconsistency unlike in the database frameworks.
Information redundancy prompts data abnormality, we should take a comparative point of
reference that we have assumed control more than one student, in this situation an understudy
student will be picked in the manner an understudy is picked for two courses and we have
understudy address verified twice straightforwardly allows express to understudy mentioning to
change his zone, in such situation if such a territory is changed at one spot and not on the main
files, then this may affect the consistency of the data (Xhang, 2016).
Merits of Database Systems over the File systems
Data reiteration: Data overabundance insinuates the duplication of data, assuming that
one is managing the data of a school where an understudy is enrolled for two courses, a
comparative understudy nuances in such case will be secured twice, which in turn may need to
be stockpiled than required. Data overabundance routinely may even prompts even higher
storage cost and thus in turn leading to poor accessibility. Data Consistency: Data reiteration
prompts data inconsistency, how about we take a comparable model that we have assumed
control more than one file, an understudy is enrolled to take 2 units and we have understudy
address secured twice, ideally, by presenting such this will give an express chance to understudy
requesting to change his area, if the area is changed at one spot and not on all of the records then
this can incite data anomaly.
There is data consistency and significantly more a great deal of information uprightness.
The basic driver of data anomaly is data abundance since data institutionalization manages the
data redundancy, data abnormality in like manner been managed as a noteworthy part of it. This

has led to information security here due to the access being constrained which in turn infer with
the given data secured with all the viewpoints. In this situation, it may be likely that one can be
able to access all the available data directly as the DB admin of such data works in the same
lines, that the data is adequately open with fast response times. Another bit of leeway is that
there is a basic recovery. For this situation, since database systems keep the support of data, it is
less difficult to finish a full recovery of data if there ought to be an event of a failure. Ultimately
is that the Database frameworks are versatile making the DB structures to be more versatile than
chronicle the frameworks utilized for handling?
Disadvantages of using DB systems
The cost of operating a database management system or its execution may be very costly
and expensive unlike in the concept of the file-based systems
It is not predictable. This types of systems are intricate for one to acquire them
In term of execution, the DB systems are so much conventional, this makes them to be
appropriate for the various applications in existence. Nevertheless, most of this DBMS
components usually impacts or influences the exhibitions of various apps
Data Models
Hierarchical Model.
In progressive or hierarchical model, information is composed into a tree like structure,
though in this model, each record or node must have a single parent and several or various kids
or nodes. The challenge of this model is that it has so many connections between it and the nodes
available (Schweinberger, 2013). For this situation, the order should begin from the parent root
and along these lines extending for what it's worth in typical trees, this is usually done by

addition of tyke hubs to the parent hubs as it develops as demonstrated as follows.
Features of hierarchical Model
It can speak to excess in information more productively than that in the various leveled
model.
There can be more than one way from a past hub to successor hub/s.
Network Model
The type of database model was made to tackle the deficiencies of the various leveled or
hierarchical database model. In this sort of model, a tyke can be connected to various guardians,
an element that was not upheld by the progressive information model. The parent hubs are
known as proprietors and the kid hubs are called individuals.

The network model can be explained as follows.
Relational Model
In this model, just as the name relational suggest, the data and all the connections are
usually communicated via the tables which are related and accumulated in one place or storage
named as the database. This shows that each and every table is used for gathering the segment
and the associated lines. In understanding this model, it is good to understand that the main
structure of the data in relational database management system is simply tables. Every one of the
information related to a particular kind is secured in lines of that table. In this manner, tables are
generally called relations in the social model.

Features of Relational Model
The utilized Database the board framework must help the autonomy of information.
It should likewise bolster the sensible freedom of information
The information is typically displayed in type of tables which for the most part have a
segment and a column (Pan, 2016).
Top-down Versus Bottom-Up Object DB design
There is an existence of a great deal of discussions with respect to the ways of dealing
with the plan use of the DB in the item arranged frameworks. Notably, for one to understand the
two major approaches, it is great and good for one to know the say such can be summed or
totaled up in all circumstances. The top-base methodology is typically beginning from all the
concepts which and general all the way to the specifics and thus helping to make the best
solution (Ramanan, 2015). In a perfect world one needs to begin by distinguishing the best
thoughts of all what is required for a particular framework and afterward asking the clients such

information that will be put away. This technique may have a few deficiencies, for example, the
main to inadmissible results as the examiner and the end-clients may miss significant things
which are much significant and consequently imperative for the working of the framework.
The base top methodology is the place one begin by recognizing the officers and
proceeds onward to top to the general. For this situation, the investigator should most likely
examine all the framework interfaces, for example, having the framework checking reports,
shapes and the screens. In a perfect world, for one to comprehend the framework well, it will be
beneficial for one to comprehend what the officers are and all things considered one can almost
certainly arrange the commanders in to points of interest (Moskal, 2013).
Top-Bottom Approach
For this situation the best methodology is to utilize the Top-Bottom methodology. Some
of the reasons for choosing this approach is that the analyst will be required have some detail or
understanding of the given database in all ways. The other reason for choosing the top-bottom
approach will involve one identifying the types of entities and thus helping one to be able to
identify some of the attributes.
Conceptual Modelling
Entities
Some of the entities involved in this case scenario are such as the one stated below. In
this case of Jet Airline there exits four major entities namely;
Planes
Employees
Passengers
Airlines

Crown’s Foot Notation Design
Logical modelling
Database Normalization
Database normalization or standardization can be named as one of the method in database
structures which are typically sorted out in the way that they will probably diminish duplications
or redundancies and substantially more relying upon the information reliance. For this situation,
the huge table can be separated into a few littler tables and therefore connecting their
connections. The standards of standardization can be clarified as far as the typical structure to be
specific the 1NF, 2NF, 3NF and Boyce-Codd Normal Form (BCNF). The table below explains

how normalization has been done in this concept of Jet Airline scenario.
Entity Relationship Diagram
In this concept, the database has about four entities namely the passenger, employee, plane and
the airline. Ideally, each table has different columns and thus in passenger table the a passenger

is uniquely identified by the name, the employee has a primary key column namely the
EmployeeIDNO, the modelNumber is the Primary key of the Plane table and lastly is the
FlightNo which is the primary key of the Airline table.
Physical Modelling
Data Definition Language
Database Creation.
CREATE DATABASE Jet_Airline;
Creation of Tables

Data Manipulation Language
In this part, the major activity is populating the table and column created in part A.
Passenger Table
Plane Table
Employee Table
Airline Table
Tables Screenshots Using Xampp
Figure 1 database creation

Figure 2 Passenger table SQL
Figure 3 Plane Table SQL
Figure 4 Employee Table SQL
Figure 5 Airline Table SQL

Populating Database by Inserting Figures
Figure 6 populating Passenger Table
Figure 7 populating Plane Table
Figure 8 populating Employee Table
Figure 9 populating Airline Table

Database population
Figure 10 database population
Figure 11 Airline populated table
Figure 12 Employee populated table

Figure 13 passenger populated table
Figure 14 Plane populated data

List of References
Carlsol, International Business Machines Corp, 2015. System, method, and apparatus for policy-
based data management. U.S. Patent 8,671,132.
Moskal, P., 2013. Analytics that Inform the University: Using Data You Already Have. Journal
of Asynchronous Learning Networks, 16(3), pp.21-38.
Xhang, X., Oracle International Corp, 2016. Rule-based transformation of metadata. U.S. Patent
8,738,663.
Ramanan, D., 2015. Bottom-up and top-down reasoning with hierarchical rectified gaussians.
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 5600-
5609).
Schweinberger, M., 2013. Computational statistical methods for social network models. Journal
of Computational and Graphical Statistics, 21(4), pp.856-882.
Palla, K., Knowles, D. and Ghahramani, Z., 2012. An infinite latent attribute model for network
data. arXiv preprint arXiv:1206.6416.
Pan, S., 2016. Tri-party deep network representation. Network, 11(9), p.12.