ITC516 Data Mining and Visualisation for Business Intelligence

This assignment solution for ITC516 Data Mining and Visualisation for Business Intelligence includes a written exercise addressing security, privacy, and ethics in data mining, covering human rights, ethical issues, and the impact of big data. The practical component involves data preprocessing using WEKA, including handling missing values, data discretization, and visualization techniques such as scatter plots. The solution provides detailed steps and figures illustrating the application of WEKA filters and the resulting changes in the dataset. The assignment uses the WEKA tool to replace missing values and analyze a dataset related to student marks, including data preprocessing steps like replacing missing values with the mean value of the respective attributes, and visualisation using scatter plots to understand relationships between variables.

ITC516
Data Mining and Visualisation for Business
Intelligence
Assessment-2
Student Name: Gurwinder Singh
Student ID: 11633263

Gurwinder Singh 11633263
Table of Contents
Part 2 - Written Exercise........................................................................................................................2
Journal 1:...........................................................................................................................................2
Journal 2:...........................................................................................................................................2
Part 3: Practical......................................................................................................................................4
Part a.................................................................................................................................................4
Part b.....................................................................................................................................................6
Part c.................................................................................................................................................7
Part D.................................................................................................................................................8
References...........................................................................................................................................10
List of figure
Figure 1: view........................................................................................................................................6
Figure 2: Scatterplot..............................................................................................................................6
Figure 3: unsupervised Discretize filter.................................................................................................7
Figure 4: Replace values........................................................................................................................8
Figure 5: Before the filter......................................................................................................................8
Figure 6: After the filter.........................................................................................................................9
1

Gurwinder Singh 11633263
Part 2 - Written Exercise
Topic: Security, Privacy, and Ethics in Data Mining.
Journal 1:
Introduction: Refers to the current scenario of the market then there is a lot of the big data analysis
for any calculation and for any analysis. With the use of the big data analysis, it is easy to analyse a
large amount of the data and predict any result. There are several of the human rights for the data
management and the information safety; all the data that are collected by the websites are to be
stored safely.
Human rights and ethical issues: Refers to the human rights then there are four common points that
help in better understanding of the human rights. Here, the grounding, content, duty bearers and
incompleteness are discussed. Refers to the human rights and the big data then both have some sort
of dynamic relationship among them. In the electronic health record, then this is become the
standard practice into the healthcare, before any kind of the treatment of the patient there are
collect the patient personal data that are stored over the server of the particular health care. Over
the server whole data of the other patients are also stored and in the healthcare, there are multiple
users of the data set of the patients.
Conclusion: Due to this, the authorization of the data access increases and the changes of the data
mismatch and the data loss is also increased. This will increase the risk factor of the data and the
failure of the big data analysis (Tasioulas, 2016).
Journal 2:
Introduction: Big data is one of the approaches that help in collecting the data and then analyse the
data as per the demand of the user. There are some of the positive impact and the some of the
negative impact of this on the user and the organization in which this analysis is performed.
Ethical issues and negative & positive impacts: In the positive sense the data is collected and
analysed, after the analysis, the desired output comes. But the negative impact is coming in terms of
the security and the privacy of the data and the analysis. While the data collection has lot of
personal information of the user is collected and then analysis than to get the required result. Refers
to the current market scenario then there are a lot of issues of the data leakage arise, professional
development system at Arkansas University was breached in 2014, just 50,000 people were affected.
One of the best tool or the technique to overcome this is the access control. By the help of this, the
2

Gurwinder Singh 11633263
organization can control the access to the number of users and this will help in protecting the data
and the information.
Conclusion: A lot of the data and the information are taken by the different online server to provides
the access of details, at that point of time the user wants only one thing from the server that the
information will be secure, the information that is provided to the server will have to be secure from
the unwanted access. Another problem with the big data is related to the organizations that are
eager to provide the targeted advertising to users and tracking the user every user move (Ryoo,
2016).
3

Gurwinder Singh 11633263
Part 3: Practical
Part a
@relation Marks
@attribute Assignment1 numeric
@attribute Assignment2 numeric
@attribute Assignment3 numeric
@attribute Assignment4 numeric
@attribute Final numeric
@data
?, 94, 34, 28, 42
35,92,85,33,45
31,46,22,38,48
46,90,60,36,50
52,94,47,48,50
58,94,30,32,51
47,90,?,23,52
36,94,25,?,52
35,94,45,31,54
57,94,100,29,54
50,94,5,32,54
45,94,31,34,55
44,0,35,36,55
52,95,58,42,56
35,94,?,36,57
4

Gurwinder Singh 11633263
57,97,57,42,57
45,90,71,38,57
39,94,54,33,57
31,94,64,31,57
45,94,?,26,59
35,90,84,49,59
37,90,40,50,61
84,97,26,38,61
68,97,55,45,62
50,95,56,46,62
77, 93,?, 41, 63
82,48,18,35,63
45,90,21,38,63
62, 95, 38, ?, 63
38,94,42,39,64
50, 90,?, 29, 64
30,90,38,32,64
44,90,43,36,65
57,94,52,37,68
50,94,39,42,70
55, 90, 66,?, 71
43,94,54,36,72
50,90,30,30,74
54,90,82,28,77
64,95,5,8,78
5

Gurwinder Singh 11633263
Part b
Figure 1: view
Figure 2: Scatterplot
6

Gurwinder Singh 11633263
Part c
Figure 3: unsupervised Discretize filter
As this shows that there are no changes in the major values of the outcomes, the missing values of
the all the assignments are some. Distinct is 24 and unique is 17.
7

Gurwinder Singh 11633263
Part D
There is need to fill the missing values of the dataset, for that there is need to use the filter that
replaces the missing values, by the use of this all the values are got replaced by some values.
Figure 4: Replace values
Figure 5: Before the filter
As the above figure shows that all the values are got replaced and the value of missing become zero.
The value of the distinct and value of unique also changes from the previous one.
8

Gurwinder Singh 11633263
Figure 6: After the filter
The values that are coming from the missing place are the mean value of the particular assignments.
Due to this, the value of mean remains same for overall assignment.
9

Gurwinder Singh 11633263
References
 Ryoo. J, (2016). Big data security problems threaten consumers’ privacy. The Conversation.
Retrieved from, http://theconversation.com/big-data-security-problems-threaten-
consumers-privacy-54798
 Tasioulas.J, (2016). Big Data, Human Rights and the Ethics of Scientific Research. Religion and
ethics. Retrieved from, http://www.abc.net.au/religion/articles/2016/11/30/4584324.htm.
10