ITC 540 Infrastructure Management: Alipay Case Study and Data Analysis

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ITC 540
Infrastructure Management
Assessment -3
Case Study and IT Research

Contents
Task A........................................................................................................................................3
Task B........................................................................................................................................6
Abstract...................................................................................................................................6
Index terms:............................................................................................................................6
Introduction............................................................................................................................6
Data.........................................................................................................................................6
Database.................................................................................................................................8
Data warehouse......................................................................................................................9
Data Mining..........................................................................................................................10
Conclusion............................................................................................................................12
References................................................................................................................................13

Task A
Case Study – “Alipay – Challenges created by the E-Business and E-Research”.
Alipay is the world's biggest third-party payment platform providing mobile and online
payment methodology. Jack Ma and Alibaba group is the founder of Alipay. The company is
situated in Shanghai, China. By the mid of 2018, the number of Alipay user increased to 870
million. Alipay is considered as the world’s most versatile online payment administration
association. The primary product of Alipay is Alipay wallet and digital wallet. It has its own
mobile app which makes it user-friendly to conduct transactions directly from the user mobile
device.
 Benefits offered by Alipay
Alipay has been the world's best due to the services and benefits it provides to its user.
Alipay. It uses the encryption methodology for conducting a secure transaction. In
2017, it published facial recognition in payment service. Installation service and
transaction cost are very low. It is very easy to use and flexible. Due to high coverage
and availability in almost every field makes it a more reliable payment method. It is
based on payment at the on click which makes the user experience the transaction in
no time. The wide range of features Alibaba provides are P2P services, credit card
payment, management of bank account, storage facility, ordering of food. Alipay is
present everywhere in the malls, petrol station, shopping centres etc. It has expanded
its services to pay bills of water and electricity, property consultation and cable
television fee. They also facilitate international payments which make them expand its
range worldwide. It helps to reduce the burden of operational cost for small scale
business.
 Problems presented in Alipay
One of the problems Alipay has is the translation of Alipay wallet in the English
version is not present in a sufficient manner. Hence Alipay wallet doesn't work with a
company which has customer from English domain. Due to advancement in
technology, Alipay lacks in the various features of social payment. One of the main
problems, it faces is regarding security breach where it is recorded that financial
details of users can be hacked. They have loose supervision of their users while
introducing new product where people circulated false news about it which ruined the

people's trust. The in-app conversion of Alipay into English is not translated fully and
its services are provided and applicable in China only. The QR scanning process
provided by it has faced so much loss of money.
 How Alipay works/ detail mechanism used
Alipay is real time, fast payment solution available for both local and international
payment solution. The business has a legal certification can use to accept the
payment. Buyers buy from the merchant and complete transaction in RMB. Alipay
deducts the cost from buyers account. Then Alipay collects the RMB to buy the
currency from foreign and transfer to the merchant's account.
 The difference and similarities between Alipay and another online payment
system.
The Alipay has an association with a large variety of financial services including
insurance services, credit rating and banking sector. It has a large financial base
support system which no other company has.

Similarities Differences
 Alipay and other online payment
system are similar in nature and
provide the same services of
purchasing, money transferring,
e-commerce etc.
 Alipay focuses more on the
business nature, payment,
wholesale and selling while
others focus on the social nature
and social aspects of e-
commerce.
 They have their own app for
mobile-friendly users.
 Alipay supports all the desktop
and smartphone and desktop
while many other supports only
smartphone
 All have expanded their services
in other countries too.
 Alipay is best known for the e-
commerce payment while others
are popular for their user-
friendly social system.
 The payment system is the same
in all first opening the app and
then scan the QR code.
 Alipay supports the currency of
18 worldwide while others are
still lacking behind it.

Task B
Abstract
The following section is about the topic
“Database, Data, Warehouse and Data
Mining”. Data forms the basis of every
organisation. It is the information which is
communicated between two companies or
organisation. Every organisation has its
own data, but handling such data is not
that easy.
Data is present in many forms either
informative or useful or not and hence the
processing of data becomes the essential
step. But these data to be stored
somewhere and hence the concept of
databases, data warehouse and data mining
comes. Databases is an umbrella term
which contains a collection of data under
it. The database has many in-built tools to
handle and process data. Various databases
are available in the market which has their
own specification.
After collecting data and storing data we
need a mechanism where data remain safe
and volatile and hence the concept of data
warehouse fits. A data warehouse is the
subject-oriented, time variant, non-volatile
and integrated collection of computer-
based information. The data mining
process is a process of discovering various
model, summaries and derived values from
a collection of data. Therefore, this
research has been conducted in the light of
data, database, data warehouse and data
mining.
Index terms:
Data, database, data warehouse, data
mining.
Introduction
The following research is conducted to
subject the importance of data, database,
warehouse and data mining. First, it
highlights the definition of data and its
various type. Next, it goes on the database
which is used to store the data in various
form. Third, it explains about Data
warehouse which provides generalised and
consolidated data in a multi-dimensional
view, describing its key features, benefits,
components and structure. Lastly, it gives
the highlights of data mining and its
process.
Data
Data is raw fact and artifices which are
reported, collected and analysed. It is
drawn from observation, experiment and
calculation. When this raw data is analysed
and processed then it turns into
information. When information is drawn to
understand and carry out the experiment it

is known as knowledge. Application of
knowledge is known as (Agresti, A, 2018)
wisdom. Data can be collected through the
primary source and secondary source. Data
from the foundation of everything.
Data can be divided into two tastes.
Quantitative data: - It is known with the
name measurement data. These data works
in numbers and the things which can be
measured. For example area, volume,
height, length, temperature, profit, loss etc.
It is again divided into two categories:
Discrete and Continuous Data
 Discrete data- It is associated with
certain values. They are
particularly numeric or integers. In
these data gap between the values
are present. Examples of the
student in the class, the number of
employees working more than
from one year. It comes after the
counts.
 Continuous data – It is the data
which takes a value between the
particular ranges. There is no gap
between the measured values.
Examples Age, height time, etc. It
comes after the measurement
Qualitative data: - They are also known
as categorical data. These data deals with
the characters and can't be measured in
numbers. For example, colour, taste, these
data are subjectively observed. They are
categorised into the following category.
 Binomial data- They have only two
values which can be true/ false,
1/0, right/wrong and good/bad,
yes/no.
 Nominal data- In this data objects
or items are present in
(Barkhordari, M. & Niamanesh,
M., 2017) unordered form. They
don't have a structured sequence.
For example, gender and race.
 Ordinal data- In this type of data
variables are present in the ordered
format. For example, short-medium
tall, the scale of 1 to 10. They are
generally used for creating bar
charts
Big data is the methodology used to deal
with large and complex data which can't
be handled with the traditional system.
Five V’s of big data are veracity, variety,
volume, velocity and value. Big data helps
in understanding the distribution of task. It
provides the computing architecture with
advanced analytical techniques (machine
learning) and managing platform for data
e.g. cloud service. Big data has ACID
characteristics: atomicity, Consistency,
isolation and durable.
Different types of Big Data available are
as follows:

Structural data: These are the type of
data which have pre-set formats for
example add. books, products etc.
Unstructured data: These are the type of
data which has no pre-set format.
Webpages, movies, audios, include in this.
Semi-structured data: These types of
data (Fazal, T., 2017) can be put into
structures by available format description.
Real-time Data: Data that is present in
motion, streaming data need to be
analysed.
Database
A database is the group of structured data
stored in a computer which can be
accessed in many ways. A database is
what sums up to “storage or collection of
data or information”. Data can be stored in
text files, spreadsheet and database
software. Databases are classified into
three categories according to the structure
which is navigational, relational and
Structured Query Language and posts
relational databases. The database
management system is used to access the
data which consist of a set of functions
that helps the user to gain access to
database and data in it. DBMS has the
following four functionalities:
 Defining data- It involves the
building of data including
creation, deletion and modification
of data.
 Upgradation- It works on the
actual data (Ghani, M. K. A.,
Jaber, M. M., & Suryana, N.,
2015) including actions of
insertion, alteration and deletion.
 Recovery- It is the processed data
which is present in the usable form
 Monitoring- It involves
monitoring and maintenance
performance, controlling
concurrency and error handling.
Databases are classified into following
depending upon the content of the
data:
 Operational database.
 Relational database.
 Object-oriented database.
 Graph database.
 NoSQL database.
 Centralised database.
 Distributed database.
 End-User database.
 Personal database.
 Spatial database.
 In-memory database.
Database languages
Types of database languages present are
which helps in performing the task are.
 Data definition language (DDL)

 Data Control language (DCL)
 Data Manipulation language
(DML)
 Data Query language (DQL)
Data warehouse
A data warehouse is first coined by Bill
Jnmon in 1990. It provides generalised and
consolidated data in the multi-dimensional
view. A data warehouse is a collection of
computer-based information that is critical
to the successful execution of enterprise
initiatives. It integrates operational data
from various sources into single and
consistent architecture.
Key features of a data warehouse: -
Subject-oriented- It provides information
around the subject rather than focusing on
the organisational ongoing projects.
Subjects include product, customers, sales,
revenues etc.
Integrated- A data warehouse is
constructed by (Idreos, S.,
Papaemmanouil, O., & Chaudhuri, S.,
2015) integrating data from heterogeneous
sources such as the relational database. It
enhances the effective analysis of data.
Time-Variant- Data collected is identified
with a time period. It provides information
from the historical point of view.
Non- volatile- Previous data is not erased
when new data is erased. Frequent changes
in the operational database don't reflect in
the data warehouse.
Functions of a data warehouse: -
 Data extraction- It is gathering data
and extracting information from
multiple heterogeneous sources.
 Data cleaning- Finding and
removing the unwanted
information and errors from the
data.
 Data transformation- Converting
data from legacy data format to
warehouse format.
 Data loading- It involves sorting,
summarizing, consolidating,
checking the integrity and
maintaining indices.
 Refreshing- It involves updating
data from data sources to the
warehouse.
Data warehouse Benefits: -
 The more cost-effective
decision-making tool
 Provide Better enterprise
Intelligence
 Enhances Customer Services
 Helps in Business and
information system re-
engineering

 It provides Online Analytical
processing tool (OLAP)
 Helps in consolidating
historical data analysis.
Data warehouse structure
 Physical data warehouse- In this,
all data for the data warehouse is
stored along with the metadata and
processing logic for scrubbing
organising packaging.
 Logical data warehouse- It contains
data stored (Marjani, M., 2017) in a
physical warehouse but does not
contain the actual information
necessary to extract the data.
 Data Mart- It is the subset of an
enterprise-wide data warehouse
and supports an enterprise element.
Data warehouse components
 Summarized data- They are of
two types Lightly summarized
data are the hallmark of a data
warehouse, all enterprise
elements do not have the same
informational requirement.
Highly Summarized data comes
from current details. They are
primarily for enterprise
executives.
 Current details- It is the heart
of a data warehouse where the
bulk of data resides. It comes
from the operational system. It
is (Witten, I. H., 2016) the
lowest level of data granularity.
 System of records- It is the
source of data that feeds the
data warehouse.
 Integration and Transformation
process- reforming,
recalculating or modifying the
structure, identifying default
values and adding time
elements.
 Archives- It contains old data
of significant value. It is used
for forecasting and trend
analysis.
 Metadata- It is defined as data
about data. It is summarized
data that leads to detailed data.
It acts as a directory and
defines warehouse objects.
Data Mining
Data Mining supports knowledge
discovery by finding hidden patterns and
association, constructing analytical
methods, performing classification and
predictions. The mining can be represented
by using visualisation tools. Data mining
(Ghani, M. K. A., Jaber, M. M., &
Suryana, N, 2015). has its application in
many fields which includes database
technology, information science, statistics,
machine learning, visualization, finance,

telecommunication, stock markets and
emails.
Key properties of Data Mining
 Helps in the automatic discovery of
patterns.
 Focuses on large datasets and
databases.
 It creates actionable information.
 Helps in predicting the likely
outcomes.
 Helps in predicting previously
unknown patterns.
 Help in detecting (Tan, P. N.,
2018) fraud which occurs in the
credit card service and
telecommunication.
 It helps incorporate analysis and
risk management.
Data mining Architecture
 Knowledgebase- This is the
domain knowledge that is used
to guide the search. It includes
knowledge such as user brief,
metadata and threshold
constraints.
 Data Mining engine- It is an
essential part of data mining. It
consists of a set of functional
modules for the task such as
characterization, clustering,
classification, correlation and
evaluation analysis.
 Pattern Evaluation- It involves
necessary measures to interact
with the data mining module to
focus the search toward
(Zhang, Y., Ren, S., Liu, Y., &
Si, S., 2017) interesting
patterns. It helps to filter out
the discovered pattern.
 User Interface- It modules the
communication between users
and the data mining system. It
helps users to interact with the
system by specifying a query. It
evaluates and visualizes the
patterns.
 Database warehouse servers-
Servers are responsible for
fetching the relevant data based
on user's data mining request.
 Database repository- It is a set
of databases, data warehouse,
spreadsheets. It helps in data
cleaning, integration and
selection of the process.
Data Mining Task
 Descriptive data mining- It
provides information to
explain what is happening
inside the idea without a
predetermined idea.
Clustering, Association
Rule Discovery and
Sequential Pattern

Discovery are some of its
technique.
 Predictive data mining- It
allows a user to submit
records with unknown field
values and system will
guess unknown (Yoon, K.,
Hoogduin, L., & Zhang, L.
2015) value based on the
previous pattern discovered
from the database.
Classification, regression
and deviation detection are
some of its technique.
Data Mining Process
The data mining process is a process of
discovering various model, summaries and
derived values from a collection of data.
The process has the following steps:
 State the problem and
formulate the
hypothesis.
 Collect the data.
 Pre-process the data.
 Estimate the model.
 Interpret the model and
draw a conclusion.
Conclusion
Data forms the basis of every organisation.
It is the information which is
communicated between two companies or
organisation. Every organisation has its
own data, but handling such data is not
that easy. But these data to be stored
somewhere and hence the concept of
databases, data warehouse and data mining
comes. Databases is an umbrella term
which contains a collection of data under
it. First, it highlights the definition of data
and its various type. Next, it goes on the
database which is used to store the data in
various form. Third, it explains about Data
warehouse which provides generalised and
consolidated data in the multi-dimensional
view, describing its key features, benefits,
components and structure. Lastly, it gives
the highlights on data mining and data
mining process which are being used.