Data Analysis and Design: A Relational Database System for Dominican College

Data Analysis and Design
Lucian Melecciu
Lecturer:
Campus: Wentworth House
Course: HND Computing and System
Date:

Contents
Preface........................................................................................................................................................2
Exercise1.....................................................................................................................................................4
1.1 critically compare different data models and schemas.....................................................................4
1.2 Benefits and limitations of database technologies............................................................................9
1.3 Approach to design database: -.......................................................................................................11
Exercise2...................................................................................................................................................13
2.Relational DBMS design in contradiction ofrequirement...................................................................13
2.2 Build Relational Database system based on design........................................................................18
2.3 Tools of Database to enhance user interface..................................................................................28
Exercise3...................................................................................................................................................30
3.1 Ease of query tools and manipulation.............................................................................................30
3.2 Implement query language into RDBMS..........................................................................................32
3.3 Estimation of extracting meaningful data........................................................................................38
Exercise 4..................................................................................................................................................40
4.1 Criticallly review and Test a Relational database system.................................................................40
4.2 Create documentation to support the implementation and testing of RDBMS...............................41
4.3 User Document for developed Relational Database System...........................................................63
4.4 How verification and validation has been addressed......................................................................74
4.5 Mechanism of controlling................................................................................................................78
Outcomes..................................................................................................................................................80
Resources..................................................................................................................................................81

Preface
This report is based on Data Analytics and their design. This report designed for Dominican
College of Blauvelt which is situated near New York. Dominica College offer various courses in
the field of science, art, healthcare, and commerce. College is cited near Rockland country, New
York. College offer various Bachelor’s and Master Degree program. Dominican college started
with teaching with underprivileged student after few years it become a coeducation college
which has courses like Social welfare, nursing, athletics, psychology etc.
This project shows the data Analysis of college data where data is menu plated to show the
basic operation like selection, data insertion, data fetching, data deletion, etc which is done
using simple command of SQL. Data base is made easy access of data which is done to make
large data access for big organization easy.

Exercise1
1.1 critically compare different data models and schemas
Data model is used to use to document the database design which makes a complicated
software design simpler to be understandable easily. In below section it is defined the data
model of different type.
1. Hierarchical data model
Hierarchical model is a kind of data which is organised in form of tree like structure. That
structure is also known as top down approach which has top most data item is known as root,
and rest are child of that root, that root child can have more sub category or sub child which
will can have their sub category or sub child. This root child relation will be the consider as
relation between data with hierarchy.
2. Network data model
Network Data model Is a kind of Data model which allow user to connect to the another
with by giving the flexibility of data sharing or exchange. This data sharing is can be faster
using network data model as it allows the user to have a sender and receiver relation which
categories the process of transfer of data which is at a time sending or receiving. A sender
can have as many receivers wanted to share data. That multiple sharing is possible by the
ability have data relation with multiple client source. Data transfer in the form of images,
text, document etc.

3. Relational data model
Relational data model is popular and common kind of data model which is used too access
data in the form of relation like one client to many clients, many clients to one client, many
clients to many client, one client to one client etc. This data model consists of raw and
column which is also known as tuple, tuple or row which can be data regarding a specific
information which is needed to the client. That specific information can be an account
number or unique id which is needed by the client. Data model can have data in form of
combination of different information.

4. Entity-Relationship data model
This model is used to model the logical view of the system. It is the entity-relationship
model in which an entity may be an object with a physical or a conceptual existence such as
a particular person, a company, a job. The set of all entities is called entity set for example-
E1 is an entity having employee entity type and the set of all employees is the entity set.
Comparison of data models are as follows:
Characteristics Hierarchical Model Network Model Relation Model
Data structure This model allows
one to one and one
to many
relationships.
It allows many to
much relationship.
It allow one to one,
one to many and
many to many
relationship.
Based On It is based on parent
child relationship.
Can have many
children’s and many
parents.
Based on relational
data structure.
Data Manipulation Algorithm for
retrieve data is very
complex and
asymmetric.
Algorithm for
retrieve data is
complex and
symmetric.
Retrieve algorithms
are simple and
symmetric.
Data integrity Child who does not
have any parent
There are no
insertion anomalies.
There are no
insertion anomalies.

cannot insert data
When we update
the child record who
has multiple
occurrences leads
the problem of
inconsistency.
This is free from
updation anomalies.
This is free from
updation anomalies.
If we want to delete
parent record also
deletes the child
records.
There are no
deletion anomalies.
There are no
deletion anomalies.
Data independence
Data independence is a concept by which data kept isolated from the using software or client
information source. Independency refers to data logic which help data to be immune from the misuse of
it, it will be used by the application only on need but it will be kept away.
1. Logical Data Independency: Logical data indecency refers toa logic which is used in mapping of
the data that is done by the combination of record or record into the single record or dual
record.
2. Physical data independence: Physical data independency is physical database used to store data
without overlapping or damaging the existing data model.

Data redundancy-
Data redundancy is repetitions of data without help of any other data that superfluity is the of data.
Data redundancy is a concept which helps to understand the multiple data for same data which is
already inside the database. Redundancy is word which represents a single data which is present in
different place. If database has more data it will work slower which is avoided.
Data integrity-
Data integrity is a concept which allow the client to assure that data is provide is secure. Data
has run in cycle which is safe that mean data is built in such a way that it difficult to misuse.
Data integrity is a parameter which allow user to establish the network which is used to detect
the data is secure or not.
Database Schema
Data schema is defined as the orientation of data which is used to structure the data which help
to identify the user of data which is known to the database identification schema. It defines the
use of data which is used in view of entire database.
1. Physical Schema
It refers to the physical database record which helps to identify every bite of data which is used
in installing the database internal data.
2. Conceptual/Logical Schema
In this schema the data is used to identify the storage of the product which has specific domain
in which the data is stored.
Tables fields relationships
A table is formed by the column and row which are the basic building blog of the table. Table
field relations are the used by the client to access data from the database. Table filed have a
key which help to identify specific data from various data which are inside the database.
Views
View is a help to display data on client machine. Database is the for of raw and column which is
confusing for client so view display the data in such a manner that client has ability to view data
in user intractable manner.