Student Assessment and Feedback Review

This assignment is a comprehensive review of a student's assessment process in a BSBMKG528 unit. The student provides an evaluation of the training received, the realism of the tasks, and their understanding of the assessment instructions. They also offer feedback on the assessor's professionalism, fairness, specificity, comprehensiveness, and timeliness. Additionally, they suggest changes to the assessment process and provide overall comments about their experience.

Assessment Workbook
BSBMKG528
Mine Data to Identify Industry Directions

1. Assessment Information
Welcome to your Student Assessment Workbook for BSBMKG528 Mine Data to Identify Industry
Directions.
This Workbook is where you will write all your responses for the knowledge questions and simulation tasks.
Please refer to the Student Assessment Guide for more information.
This assessment has the following two events:
To complete the Simulation, you will need to refer to the following resources:
Please note that your responses for both assessment events can (where appropriate) use dot point format. See
below for an example of a dot point response and a full sentence response:
To Achieve Competence
To be deemed competent for this unit, you will need to meet the following requirements:
 complete all of the questions and tasks listed in this Student Assessment Workbook
 meet all the requirements listed in the Student Assessment Guide
 your responses to the questions and tasks must be relevant, accurate and specific
Assessment Event 1 – Knowledge Questions
There are five questions that will provide us with the evidence of your general knowledge of the current
data mining concepts, applications, tools, practices, and the regulatory context within the marketing
industry field.
Assessment Event 2 – Simulation: Momentum College
You will complete a number of tasks in developing and presenting a well-structured data analysis report.
These tasks will be based on your role of a Market Analyst in a simulation for a digital marketing agency,
DigiGeek, where you will be assisting a new client, Momentum College, an Australian registered training
organisation (RTO) that offers nationally accredited courses seeking to expand its business.
Data Mining Policy and
Procedures
DigiGeek’s policy and procedures for data mining. You will abide these
organisational requirements when performing data mining activities and
producing the required report in Assessment Event 2.
Market Analysis
Project Brief
Document that provides background information about the agency DigiGeek,
the client Momentum College, and other relevant information for the client’s
data mining requirements. You will conduct their data mining project on the
basis of the requirements specified in the Brief.
Dot point format Presentation Plan includes the following:
 outcomes
 needs of the audience
 context.
Full sentence format When you are preparing for a Presentation, there are a number of tasks that must
be carried out. These are; listing the outcomes that you want to achieve, followed
by the identification of the needs of your audience. When you have completed
these two tasks you then check on the room that you will be conducting the
simulation in etc.

 submit your completed Student Assessment Workbook to your Assessor within the set timeframes
 your work must be in your own words
 where you use an external source of information, you must provide citation.
2. Pre-assessment Checklist
Your assessor will go through the assessment for this unit, BSBMKG528 Mine Data to Identify Industry
Directions. It is important that you understand this assessment before taking on the questions and tasks. To
confirm that you have been given this overview, we ask you to complete the following Pre-Assessment
Checklist.
You are required to carefully read each checklist item provided below and tick either ‘Y’ to confirm your
understanding or ‘N’ if you disagree. In case you disagree with an item, please provide your reason under
the ‘Comments’ column.
When you have done this, we ask you to sign this Pre-Assessment Checklist. This acknowledges that your
Trainer/Assessor has discussed all of the information with you prior to undertaking this assessment.

Pre – assessment Checklist
C
o
m
m
e
n
t
s
Y   N I, the student, understand the purpose of the assessment. Y
Y   N
I understand when and where the assessment will occur, who
will assess and in what format the assessment will be
submitted. Y
Y   N I understand the methods of assessment. Y
Y   N I understand what resources are required to complete this
assessment. Y
Y   N I understand the performance level required for each
assessment event. Y
Y   N
I understand that it must be my own work. I have been
explained and understand the serious consequences in case this
work is found plagiarised. Y
Y   N I understand the process if I am deemed not yet competent. Y

3. Assessment Event 1 – Knowledge Questions
The information contained in this assessment event lists the questions that you will need to develop a written
response. These questions are theoretical and provide evidence of your understanding of data mining
concepts and principles.
Note you must answer these questions in your own words. Remember, you must get a satisfactory result
with each question to be deemed satisfactory for the whole of Assessment Event 1.
1.Question 1
Using the table below, outline the various uses of data mining in the context of marketing communications.
Write your response into the table below:
2.
Q
uestion 2
Explain the terms 'data validity', 'reliability' and 'completion'.
Write your response here:
Data life cycle is termed as various stages of data unit which is considered from initial stage to
deletion of data at end. The data life cycle management is important as with the increase in exploration of
big data and development of internet on things. It is important for every organisation to adopt various data
protection for increasing trust and satisfaction of service users. In case of given college, it is important for
this organisation to provide valid, reliable and accurate data for users so that they can get all authentic
information regarding college. The concept of data validity, data reliability and data completion are
explained below -
 Data validity – This is termed as correctness and accuracy of data. The data collected from mining
must provide valid and correct data. The validation of data simply means how accurate data is. In
Uses of Data Mining Explanation
Cluster analysis This gives an opportunity for identifying a single user target group in
accordance to similar features within database like education level, age,
class, course, etc.
Regression analysis This helps in enabling to study habits, changes, customer satisfaction level
for making marketing forecasts. This will help in analysing the market
effectively.
Classification analysis This helps in allowing to classify various information that is received from
potential clients and customers while identifying patterns within a database.
Intrusion detection System security is the most important concept of an organisation so data
mining is helpful in protecting data from various intruders.
Fraud Detection This will be used in detecting any fraud within the organisation.
There is requirement of perfect fraud detection system so that

context of college, it is important to provide useful information of data to people so that there will
not be any issue.
 Data Reliability – Data reliability means that data is reasonably complete and accurate and it fulfils
intended purpose. Reliability helps in assessing way which data mining model has to perform on
various data sets. Model of data mining is said to be reliable when it creates similar kind of
predictions.
 Data completion – This is defined as data is finally completed and it includes all important and
valuable information about the topic. This includes different metrics which will explain completion
of model that provides useful information. Data regarding college courses and students is available to
different websites, social media sites and e-portals.
3.Question 3
Using the table below, compare the characteristics of public, client and organisational datasets.
Write your response into the table below:
4.
Q
uestion 4
Identify and list the uses of current industry tools used in data mining.
Write your response here:
Data mining is effective for valid, hidden and all the possible patterns in datasets. Data mining is
defined as a technique that serves as a primary purpose of introducing patterns among large data and
transformation of this data from into a more refined information. The major objective of data mining is
Characterist
ics
Public Client Organisational
The public datasets are those
which are available to whole
population around the world.
These are available for only
specific clients and
customers.
Such datasets are for organisation
only.
Security The public datasets are those by
which college will market it's
courses and facilities. It is less
secure than other two datasets.
This is more secure dataset
and information in this data
is more secured.
Organisational dataset is available to
individuals who are authentic to know
organisation's data.
Validity and
legitimacy
This data is less valid and
legitimate.
Data of clients is more valid
and legitimate.
Organisational dataset has more valid
and legitimate data.
Accessibility This data can be used by all
public.
This data is limited to
only particular clients
and customers.
This data is accessible to
individuals to organisation.

extracting useful information from data sets and converting to understandable structure. The different
industry tools used in data mining are listed below -
RapidMiner – This is known as best predictive analysis system that is developed by a company
naming Rapid Miner. This is written in Java programming.
Strength Weakness
 This gives an integrated environment for text
mining, predictive analysis, deep learning
and machine learning.
 This tool is useful for wide range of business
application and education.
 This offers server on premise as well as
public and private cloud infrastructure.
 Coding is not used in this application.
 For using this tool, expensive and
commercial tool is required.
 Use case of this application is limited to set
of modules and processors.
Orange – This is a software suite for data mining and this helps in data visualisation and this is a
component based software. This is written in python language.
Strength Weakness
 Orange application helps in bringing more
interactive vibe in analytical tool.
 Data that is coming to Orange is quickly
transformed to requisite pattern.
 This application helps users to make smart
decisions in less time.
 The installation of this application is big as
there is need of installing QT.
 It contains limited list of learning algorithms.
 This application is limited to exporting
representing data visually.
Weka – Waiketo Environment is used for analysis of knowledge. This is a collection of algorithm of
machine learning used for data mining activities. This is supported by Java and this consists of collection of
different tools for data analytics.
Strength Weakness
 This is suitable for making schemes for
machine learning.
 It is open source , extensible and free and it
can be integrated to other Java packages.
 This is a secure way of using data.
 This application lacks adequate and proper
documentation.
 It has bad connectivity with Excel
spreadsheet and database with non Java
programs.
 This application is weaker in classical
statistics.

KNIME – Konkstanz Information Miner is an open source data analytics, integration and reporting
platform which is used in research. This is generally used in different fields like business intelligence, CRM
customer data analytics and financial data analysis.
Strength Weakness
 It integrates different analysis modules.
 This is an easy data mining tool which offers
access to different statistical routines.
 This has ability for interface with programs
which allows for visualisation and analysis of
data.
 Limited error measurement method.
 There is no wrapper method for descriptor
selection.
 There is no facility for parameter
optimisation.
KEEL – This is Knowledge extraction based on Evolutionary which is an application of machine
learning software tools. This is used for data manipulation in research.
Strength Weakness
 This consists of classification, regression,
pattern mining and clustering.
 This includes huge collection of
preprocessing techniques and knowledge
extraction algorithms.
 The main limitation of this is that efficiency
is restricted by a number of algorithms.
 This is less used in organisations.

5.Question 5
Using the table below, identify and list the uses of current industry techniques used in data mining.
Write your response into the table below:
Techniques Explanation Application in Real-life
Tracking Patterns This is a technique in data mining used for recognising
patterns in datasets.
Organisations can use this for analysing sales of particular product
on website.
Classification This is a complex type of data mining which forces for
collecting different attributes.
Financial background or purchase histories are classified as low,
medium or high credit risks.
Association This is associated with tracking patterns. When customers buy a particular item, they sometimes buy another
product with it and this leads to increase the section of people also
brought. to
Clustering This is similar to classification but it also
consists of grouping data chunks.
Various demographics can be clustered and how much
income individuals have.

4. Assessment Event 2: Momentum College
Simulation
In this assessment, you will undertake a number of tasks associated with mining data for an educational
institution, Momentum College. The focus is on undertaking data mining practices to help
Momentum College to identify new directions in accordance with its proposed
initiative.
6.Task 1: Determine Purpose of Data Mining
In this task, you will review client requirements for the data mining activity and suggest which areas it can
bring solution to the client. Also, you will summarise the regulatory and organisational requirements that are
closely linked to the data mining activity. These will involve you to review and analyse the documents
provided (see separate attachments: the ‘Market Analysis Project Brief’ and ‘Data Mining Policy and
Procedures’), and conduct external research on relevant legislative requirements.
7. 1.1 Identify and review relevant client and organisational
requirements for data mining
Insert your response here: There is a need of protecting data provided by the organisation. In the present
scenario, personal information and client data is present which can be public or private. DigiGeek
organisation wants to manage, protect, collect and allow access to information of employees to them. Thus
data mining is used.
8. 1.2 Confirm potential uses of data mining outcomes and
recommendations
Insert your response here:
The potential uses of data mining are mentioned below - Market segmentation – This includes identifying the similar characteristics of individuals working
in the organisation. Customer churn - This predicts which customers are going to leave the organisation. Fraud Detection - Determines transactions that are fraudulent. Direct Marketing – This determines those prospects which are included in a mailing list. Interactive marketing - This predicts what an individual access at website.
9. 1.3 Recognise legislative and organisational requirements
Insert your response here:

The three type of legislations that are currently in force are listed below-
 This policy is related to communicate with staff of DigiGeek. This helps in managing, collecting,
dealing with and allowing access to personal data according to Privacy Act 1988 and Australian
Privacy Principles.
 Data mining activities are conducted without violating copyright in alignment with Copyright Act
1968.
 Data and information are accessed by Australian Government agencies according to Freedom Act
1982.

10. Task 2: Identify Data Sources
In this task, you will identify and access public and private data sources relevant to their project in
compliance with privacy and copyright requirements. You will then evaluate these sources in terms of their
validity, reliability, and completion rate.
11. 2.1 Identify available data sources
Insert your response here:
There is a student database in MC that is named as 'MCSDB'. This contains data of each and every
student. DigiGeek is given all snapshots of student's data. This project needs external data for ensuring
precision in recommendation to the organisation. It is responsibility of market analyst for identifying and
obtaining data of international students and overall enrolment level.
12. 2.2 Negotiate access rights and intellectual property release
for relevant data sources
Write the email to the client here:
To all students and staff
It is requested by all students to provide their information and data as this is required for maintaining
data. You can provide information about your name, age, date of birth, course and batch, enrolment
number,contact numbers, email address. Data provided by you must be valid and reliable.
Draft the email to Austrade here:
To all staff of Autrede
Market Information Package will provide valuable and timely market analysis, intelligence,
opportunities and data for supporting International education and training sector of Australia. MIP includes
information of International students, MIP Orbis Interactive data which helps in discovering insights through
interactive visualisations, availability to source data, ability to create, share and save interactive charts. This
includes information from Australian Government department which impacts on International education.

Write the FOI request email here:
FOI
It is requested that student's data and information must be authentic and reliable. This information
should be kept secure. Various issues like copyright and confidentiality issues must be considered. Student’s
information and data is recorded and kept safe.
13. 2.3 Rank and prioritise data sources for validity, reliability
and completion rates
Insert your response here:
Data sources is defined as any system which sends data to Universal data hub. These systems
consists of websites, mobile applications, etc. The data sources are platform specific and they give necessary
instructions and codes for completing an installation. The different data sources available are websites,
mobiles, Java and HTTP API. The policy of organisation is applied to different practices throughout
lifecycle of data mining and this includes data collection, analysis, exploration, documentation and
reporting. The data source which is mostly used by people is website. They can easily grab information
about student's data from website. Another used data source can be mobile application. This is used by
every individual and information can be taken from this.

14. Task 3: Apply data mining techniques
In this task, you will select and apply appropriate tools and techniques to analyse data collected in earlier
tasks, then visualise the outcomes of your analysis accordingly.
15. 3.1 Select appropriate tools and techniques for data analysis
Insert your response here:
Clustering is a data mining tool that includes grouping of data chunks together who are having
similarities. In case of student's data and information clustering will help in differentiating students who are
having same kind of attribute or characteristics.
Two techniques that can be used in data mining are RapidMiner and Weka
The Rapidminer helps students, researchers and professors at different levels. For instance, this will
help students to share innovations and leverage analytical processes. Professors are able to certify students
using RapidMiner exams. Weka helps in different standard mining tasks, clustering, classification,
visualisation, regression and data processing. Weka provides access to deep learning and SQL databases.
16. 3.2 Classify data for analysis
Insert your response here:
Mc has own database for students which is known as MCSDB. The data is collected from various sources
like student's register, enrolment number, courses allotted and college allotted. When an individual is going
to find data about information of student then he can get it from data present at database, MCSDB.
17. 3.3 Analyse and visualise data to identify patterns, clusters
and relationships
Insert your response here including your visualisations:
The data sources is MCSDB which is a database that includes information associated with every
student. DigiGeek is given all snapshots of student's data. This is useful in identification and obtaining data
of various international students. The Rapidminer is data mining technique which helps students,
researchers and professors at various stages.

Student Name
Student last name
Student Address
Contact number
Year of enrolment
Student number
Course
Batch
Lecturer name
Lecturer contact no.
Lecturer email
Course 1
Semester
Lecturer Id

18. Task 4: Report and Recommend on Findings
In this task, you will evaluate the outcomes of their analysis to draw insights and make recommendations to
the client in accordance to their data mining objectives. You will then assess the validity and reliability of
your insights and conduct an interactive session with the client to verbally report their outcomes. Finally,
you will reflect on what you have experienced throughout the lifecycle of your data mining process.
19. 4.1 Assess results of data mining to draw insights
Insert your response here:
DigiGeek is an agency that is involved in providing high level of professional service to
stakeholders. This includes data mining activities according to client requirements. The main purpose of this
policy is to collect, manage and protect personal information of students. The policy aims to ensure lawful
activities of data mining and promoting high standards of professional conduct. This helps in improving the
outcomes of data mining. This policy is applied to different practices throughout lifecycle of data mining.
This consists of data collection, data documentation, analysis, exploration, documentation, etc. this policy
helps in outlining requirements of DigiGeek for managing data mining activities. This is applicable to all
staff members and external subcontractors who modify, collect, analyse, document, evaluate and applied to
external data under investigation. The stakeholders of DigiGeek ensures that asset collected must be
accurate and complete. They must take appropriate steps for protecting information about misuse,
interference, unauthorised access, etc. The stakeholders have to access and process data from different
public and private data sources using programs. The stakeholders have to request the owner before initiating
the activities of data mining. DigiGeek follows ethical and social principles through data mining. From the
above discussion, it is concluded that student database must be secured and it should contain accurate and
reliable data.
20. 4.2 Weight insights for reliability and validity
Insert your response here:
The record of student's information is an important and frequently searched data in an education
organisation. A good maintenance of relationship between student and relationship is achieved by having a
proper data base management of student's information. The data provided at different public and private user
interface helps in knowing about information of students.

21. 4.3 Report data mining process and outcomes
In this task, you will interact with the Marketing Manager. See your Student Assessment Guide for more
information.
Printed and attach your slideshows to your Student Assessment Workbook.

22. 4.4 Document lessons learnt
R1. capture lessons learned for continual improvement, explaining the following:
 what went well?
While accessing data mining techniques and tools everything went well.
 what were the critical success factors for achieving the data mining outcomes?
There were issues like mishandling of data of students, classification of students,etc.
 what were the barriers to success?
The main barrier to success is that I lack in technical skills and thus it was not easy to operate the
database system.
 what should be improved for the betterment of data mining activities in future?
There is need for improving the data mining activities by following latest techniques.
 how to make these suggested improvements?
The database management system must be improved by using new techniques.
R2. explanations must:
 not be generic
 include specific examples to reflect on your own experience
R3. word count is approximately 250 words in total.
5.
T
ask Outcome Sheets
The Outcome Sheet below is the assessment questions and tasks for each of the assessment events that the
student is required to complete. Assessors, tick ‘S’ if the student achieved a satisfactory outcome for an
assessment task and ‘NYS’ if the student does not meet these requirements. Also, you are required to write
comments on the quality of this evidence under the ‘Comments’ column. For your judgement on the
student’s overall performance, tick ‘Satisfactory’ if the student achieves a satisfactory outcome for all of the
tasks or ‘Not-Yet-Satisfactory’.
For Assessor Use Only

23. Assessment Event 1 – Knowledge Questions
Assessment Event 1
Knowledge Questions S NY
S Comments
Question 1
Question 2
Question 3
Question 4
Question 5

N
o

24. Assessment Event 2 – Simulation
Assessment Event 2 S NYS Comments
Task 1:
Determine
Purpose of Data
Mining
Sub Task
1.1
Sub Task
1.2
Sub Task
1.3
Task 2:
Identify Data
Sources
Sub Task
2.1
Sub Task
2.2
Sub Task
2.3
Task 3:
Apply data
mining techniques
Sub Task
3.1
Sub Task
3.2
Sub Task
3.3
Task 4:
Report and
Recommend on
Findings
Sub Task
4.1
Sub Task
4.2
Sub Task
4.3
Sub Task
4.4

N
o

25. Assessment Outcome Sheet

Student
ID Family Name First
Name
Course
Code Course Title
Unit Code BSBMKG52
8 Unit Title
Mi
ne
Da
ta
to
Id
en
tif
y
In
du
str
y
Dir
ec
tio
ns
Assessmen
t Outcome
Assessor,
please tick
and date the
student’s
final outcome
of this
assessment:
Initial
Submission
Date Re-
submission 1
Date Re-
submission 2
Date
C NYC ___/___/
____ C NYC ___/___/
____ C NYC ___/___/
____

Assessor’s Feedback
Assessor, please provide your comments on the student’s final outcome of this assessment:
Assessor Full
Name
Signatu
re
Date
Receipt
of
Student
’s
Assess
ment
Assessor,
you must
provide the
completed
copy of this
receipt to
the student
as an
evidence of
submission
of their
assessment
to you.
Student ID Family
Name
First
Name
Course Code Course
Title
Unit Code BSBMKG52
8 Unit Title
Mine
Data to
Identify
Industr
y
Directi
ons
Due Date __/__/___ Date
Received __/__/___
Extens
ion
Approv
ed
Y  N 
Date
Approv
ed
__/__/___
Initial Submission  Re-submission 1

Re-submission 2

Assessor’
s
Signatur
e