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Assessment item 1Assessment Item 1Value:15%Due date:13-Aug-2017Return date:04-Sep-2017Submission method optionsAlternative submission method Task Report Task Task 1 (5%) Title: Data Mining in...

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Assessment item 1Assessment Item 1Value:15%Due date:13-Aug-2017Return date:04-Sep-2017Submission method optionsAlternative submission method
Task

Report Task

Task 1 (5%)

Title: Data Mining in Business. Recommended word length for this posting is 500 words.

In this task you will need to:

1. Briefly summarise why data mining is used in business.
2. Share a recent article/news item relating to data mining in business (include a link to the article).

Briefly summarise the article, identifying the business requirements for which data analysis is being used in this case.

Task 2 (10%)

Title: Security, Privacy and Ethics. Recommended word length for this posting is 1000 words.
For this activity you will need to:
Read the following articles:

  • Ryoo, J. ‘Big data security problems threaten consumers’ privacy’ (March 23, 2016) theconversation.com http://theconversation.com/big-data-security-problems-threaten-consumers-privacy-54798
  • Tasioulas J. ‘Big Data, Human Rights and the Ethics of Scientific Research’ (December 1, 2016) abc.net.au http://www.abc.net.au/religion/articles/2016/11/30/ XXXXXXXXXXhtm

Post a response based on the following:

  • Identify the major security, privacy and ethical implications in data mining
  • Evaluate how significant these implications are for the business sector
  • Support your response with appropriate examples and references
Rationale

As this is a postgraduate subject, student opinions are actively sought to demonstrate that the reading material has been engaged with. Regular posting on the Discussion Board also provides students with an opportunity to share their insights and experience as part of a learning community.

In addition, it assesses your progress towards meeting Learning Outcomes 1, 6 and 7:

1. Be able to identify and analyse business requirements for the identification of patterns and trends in data sets

6. Be able to identify and evaluate the security, privacy and ethical implications in data mining;

7. Be able to explain the importance of current and future trends likely to affect data mining and visualisation.

Marking criteria
HDDICRPSFL
1.Concept & Knowledge of topicsDemonstrates breadth and depth of understanding and has insights and awareness of deeper more subtle aspects of the topic content. Evidence of having researched/read more widely beyond the core materials.Demonstrates breadth and depth of understanding and has insights and awareness of many of the deeper more subtle aspects of the topic content.
Evidence of having read beyond the core materials.
Demonstrates thorough understanding of material presented in core texts and readings.Demonstrates evidence of having read material presented in core texts and reading. However, literature is presented uncritically in a purely descriptive manner. Content acknowledged but not really taken into account.Demonstrates very little evidence of having read material presented in core texts and readings. Inaccurate or inconsistent acknowledgement of sources.
Limited knowledge of key principles and concepts.
2.Clarity of expression & presentation of response, while fully utilising the word count limitHighly developed skills in expression and presentation of response.
Fluent writing style appropriate to assignment task/document type.
Grammar and spelling accurate. Well-organised use of the word-count limit.
Well-developed skills in expression and presentation of response.
Fluent writing style appropriate to assignment task/document type.
Grammar and spelling accurate. Word limit maintained.
Good skills in expression and presentation of response.
Mostly fluent writing style appropriate to assignment task/document type. Grammar and spelling accurate. Word limit maintained
Some skills in expression and presentation of response.
Meaning apparent but writing style not always fluent or well organised.
Grammar and spelling contain errors. Exceeded or fell short by more than 10% of word limit.
Rudimentary skills in expression and presentation of response.
Not all material is relevant and/or is presented in a disorganised manner.
Meaning apparent but writing style not fluent or well-organised.
Grammar and spelling contain errors. Ignored word count completely.
3.Referencing and citationReferencing is consistently accurate and according to the APA standard. All references are cited in the text.Referencing is mainly accurate and according to APA standard. Most of the references are cited in the text.Some attempt at referencing and according to the APA standard. Few references are cited in the text.Attempt at referencing but not exactly according to APA standard and only few references are cited in the text.Referencing is absent.
Presentation
  • Assignments are required to be submitted in either Word format (.doc, or .docx), Open Office format (.odf), Rich Text File format (.rtf) or .pdf format. Each assignment must be submitted as a single document.
  • Assignments should be typed using 10 or 12 point font. APA referencing style should be used. A reference list should be included with each assessment item.

This activity's final mark will be provided prior to the final assessment item.
Use APA referencing.

Answered Same Day Dec 26, 2021

Solution

Robert answered on Dec 26 2021
104 Votes
Data Mining in Business
1. Data mining is a process of discovery of knowledge from a large set of structured and non
structured data. It is performed by the help of tools to get the relevant information from large
source of data repository such as data warehouse. The businesses are directly related with
product and services with their customers. Data mining provides the business decision
makers to analyze the past performance of the business from the existing sales, customer
eviews, product positions, and profits stored into the data repository. These all relevant data
are mined from the central data repository of the business entity to provide the input for
analysis. The executives and decision makers take the decisions about the pricing of the
products, preference of the customers, impacts of sales and future forecast of the products
and services through the help of available data from transaction data sources of the business.
The proper and effective business decisions are taken if the past business performance data
are being analyzed by the co
ect and proper methods. Data mining supports the decision
makers by enabling them to get all relevant data from the transactional and non transaction
sources of data of the business. Today, a corporate business entity always finds the solution
of the business growth by employing the central data repository that stores both transactional
and non transactional data elements from every aspects of the business procedures. These
centralized version of data repository facilitates the efficient data mining process to provide
accurate relevant details that required. Therefore, the cu
ent competitive arena of business
world all the business entities are formulating the Information system to cater the better
usiness decisions through the use of information technology framework such as data mining
2. Tim ray and Chips Wells in their article (Ref. - http:
analytics-magazine.org/integrating-
data-mining-and-forecasting/) , state that data mining in business forecasting provides the
abundant opportunities to the time series data stored from both external and internal sources
of the business (Rey & Wells, 2013). These data are readily being available for the decision
makers of the business. Mining and making decision about the forecast impacts the profit of
the business. A chemical company Dow targeted to achieve cost reduction, agility in the
market, accuracy improvement and visualization of its products and services through the help
of data mining. With help of data mining Dow Chemical Company interested to make better
forecast model demand volume of its products, net sales, costs of the inventory, utilization of
assets, net sales and earnings before the tax and interest. Decision makers of Dow directly
mines the transactional source of data of the company to mine the relevant data to forecast
the mentioned company interest.
Pui Mun Lee (Ref. https:
www.cluteinstitute.com/ojs/index.php/RBIS/article
viewFile/7843/7904 ) states that e-business companies dedicated to its information
technology framework to make growth of the business globally (Lee, 2013). Companies
egularly tries to employ depth analysis to the available data to take more proper and
effective decision for the sales and service. The predictive knowledge is discovered by the
usiness data mining. The business analyst functions like a detective of data to cater the more
accurate business decision. There are basically four phases of the business data mining to get
elevant and useful data to make analysis. The main aim of these all phases of the data
mining to discover the knowledge from the available data by analysis processes.
References
Rey, T., & Wells, C. (2013). Integrating data mining and forecasting - Analytics
Magazine. Analytics Magazine....
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