Business analytics and Data mining in the following three industries:1. Transport Industries2....

Question

Business analytics and Data mining in the following three industries:1. Transport Industries2. Banking Industries3. Customer Relationship Management.
I need one Report of upto 3000 words and a PPT presentation relating to the report about all the three industries .

1 ITECH7406- Business Intelligence and Data Warehousing Research Report Group Assignment Sem1-2019 Overview For this assignment, the students will work in team and create a written report that will review the applications of business intelligence analytics and Data Mining in different industry domains in decision making contexts. The purpose of this assessment is to enable students to understand how business intelligence analytics and Data Mining techniques revolutionize businesses today. Timelines and Expectations Percentage Value of Team Report: 15% Percentage Value of Team Presentation: 10% Group Presentation Due Date - Week 08 –Timetabled Tutorial Group Report Due Date – Week 09 (Sun, May 19, 2019 - 17:00) Assignment Details Background Business analytics and Data Mining techniques can help organizations make sense of -- and gain a competitive advantage from -- all the data that they have in their systems. Business analytics includes “decision management, content analytics, planning and forecasting, discovery and exploration, business intelligence, predictive analytics, data and content management, stream computing, data warehousing, information integration and governance” (IBM, 2013, p. 4). There are different types of business intelligence analytics that an organization can take advantage of, including predictive analytics, text analytics and text mining, sentiment analysis, customer analytics and business intelligence data mining. Data Mining is the process of analyzing large data-sets to identify trends and patterns in the data. The data can be generated through different sources such as social media, websites, transactions, mobile devices, sensors, etc. The information extracted from this data helps organizations to derive their real business value and generate new business opportunities. In the light of above information write a 3000 words research report on specific business analytics and Data Mining techniques applications that derive business value and generate new business opportunities in any of the following three (3) industry verticals. Illustrate the impact of these techniques on businesses with examples of application from the chosen domain. 2 Choose only any THREE (3) domains from the following list: 1. Transportation industry – in this domain the business analytics help stakeholders in making effective decision in Traffic control, route planning, intelligent transport systems and congestion management (by predicting traffic conditions). Also, could be useful for route planning to save on fuel and time, for travel arrangements in tourism etc. revenue management, technological enhancements, logistics and for competitive advantage (by consolidating shipments and optimizing freight movement), etc. 2. Banking industry - Data mining techniques can be used to detect financial fraud, including credit card fraud, corporate fraud and money laundering. 3. Health Care industry - Health care applications include discovery of patterns in radiological images, analysis of microarray (gene-chip) experimental data to cluster genes. Moreover, chronic disease states and high-risk patients can be tracked. 4. Manufacturing industry - Large volumes of data from the manufacturing industry are untapped. The underutilization of this information prevents improved quality of products, energy efficiency, reliability, and better profit margins. Business analytics can be used in solving today’s manufacturing challenges and to gain competitive advantage among other benefits. 5. Education industry - Major challenge in the education industry is to incorporate big data from different sources and vendors and to utilize it. Business analytics can be used to measure teacher’s effectiveness, overall progress of a student over time and effectiveness of curriculum, etc. 6. Customer Relationship Management - Data mining and analytics provides efficient tools to analyze customer data for the purpose of decision-making. Moreover, data mining aids analysis of buying patterns, determination of marketing strategies, segmentation of customers, stores or products. Requirements In this assignment, you will be required to form teams of approximately three (3) people. The findings of your research study will be presented through: • A group research report • Interactive presentation. 3 The report The report will take the form of a well-researched academic report of approximately 3000 words. Diagrams or tables are encouraged to be used to support your statements. The report should be well supported with appropriate references from reliable sources. You should include academic journals, books, theses, trade magazines and well-respected sources of related Internet materials that you find relevant. Please note – Wikipedia is NOT considered a reliable source to quote in an academic document of this type, without backup from other well reputed sources. Your report should present as a collective effort, not a series of submissions by various team members. It is expected to FLOW as one document. Each team member’s contribution should be clearly identified in the report, with a notation about which section he/she wrote about. Table of contents, reference list and contribution statements do not count towards the final words count. All reports must use the APA referencing style The Presentation Duration: 20 minutes for each team For the presentation component of this assessment, your team will focus on the following: 1. Business analytics and Data Mining techniques specific to the chosen domains 2. Illustration of applications of the above business analytics and Data Mining techniques within the chosen domains 3. Explanation on how these specific business analytics and Data Mining techniques added business value and generated new business opportunities within the chosen domains 4. Any Challenges that associated with the application of the above business analytics and Data Mining techniques for the chosen domains 4 Submission Submit your report as either a word or PDF document via Moodle. Marking Criteria/Rubric Refer to the attached marking guide. Feedback Feedback will be supplied through Moodle. Authoritative marks will be published through FdlGrades. Plagiarism: Plagiarism is the presentation of the expressed thought or work of another person as though it is one's own without properly acknowledging that person. You must not allow other students to copy your work and must take care to safeguard against this happening. More information about the plagiarism policy and procedure for the university can be found at http://federation.edu.au/students/learning-and- study/online-help-with/plagiarism. http://federation.edu.au/students/learning-and-study/online-help-with/plagiarism http://federation.edu.au/students/learning-and-study/online-help-with/plagiarism 5 ITECH7406- Business Intelligence and Data Warehousing Research Report Marking Guide Sem3-2018 Criteria Marks Significance of Business analytics and Data Mining applications for the chosen industry areas /5 Research findings on Business analytics and Data Mining techniques specific to the chosen domains /10 Discussion on how business analytics and Data Mining techniques added business value and generated new business opportunities within the chosen domains /15 Report challenges that associated with the application of the business analytics and Data Mining techniques in the chosen domains /5 Introduction and Conclusion - An interesting, well written summary of the main points. For conclusion, an excellent final comment on the subject, based on the information provided. /5 References - Correct referencing (APA). All quoted material in quotes and acknowledged. All paraphrased material acknowledged. Correctly set out reference list. /5 Report Presentation Style – Spelling &grammar, length, originality, report layout , (Points will be deducted for exceedingly long or short reports. /5 Total /50 Marks /15 General Comments: 6 ITECH7406- Business Intelligence and Data Warehousing Research Presentation Marking Guide Sem3-2018 Criteria Marks Introduction - chosen industries and significance of analytics for the them /10 Industry specific Business analytics and Data Mining techniques /10 Applications of the business analytics and Data Mining techniques that added business value and generated new business opportunities within the chosen domains /15 Challenges that associated with the application of the above business analytics and Data Mining techniques for the chosen domains /5 Conclusion - an excellent final comment on the subject based on the research findings. /5 Presentation Style e.g. layout, clarity, engagement /5 Total /50 Marks /10 General Comments:

researchreportgroupassignment-semester1-2019-mdztwep2.pdf

Archana · Accepted Answer

Data Mining and Big Analytics
Contents
Introduction	2
Significance of business analytics and data mining in the industrial areas	2
Research findings on data mining and business analytics	5
Discussion on values added by data mining and business analytics procedures for the generation of new opportunities in business	7
Challenges associated with application of data mining techniques and business analytics	11
Conclusion	11
References	13
Introduction
Business analytics can be explained on the basis of attaining and implementing skills as well as technologies of practices to investigate and understand the business strategies of the past within an organization, and there after use this understandings and analysis to improve and evaluate future business strategies and develop better business plans (Duan & Xiong, 2015). There are various techniques of implementing business analytics in these organizations which can help to improve business tactics (Gupta, Goul & Dinter, 2015). These include clustering with predictive analytics, descriptive analytics, and affinity grouping. With the use of data mining, various companies and organizations are able to collect information from several sources and integrate them to be put to use in solving relevant business issues in their organization for better strategic marketing. The reports will understand and explain the significance of business analytics and data mining on three industries, namely education, banking and Healthcare. Data mining and Data analytics techniques have made activities within the education sector, the banking sector and the health care sector much more achievable and workable anthem allowed for the progress in these industries with their tools. 
Significance of business analytics and data mining in the industrial areas
With the changing scenario of Technology and organizational setups, several adapted measures need to be undertaken by these industries to follow new emerging trends and adopting business intelligence and data mining techniques (Dubey & Gunasekaran, 2015). The use of these techniques will allow improvement of these strategies and significant progress with the expected outcomes. The significance of data mining and business intelligence in the education sector, banking sector and Healthcare sector will be hereby discussed:
Education sector: data mining procedures within the educational industry is an up and coming sector because of various techniques that are required by educational departments to understand activities within the educational industry (reyess, 2015). Educational department require these tools to store and extract various information and data from various records about examinations, student records, online and offline logs as well as examination results so that this data can be taken out for reference at any time without any glitches. Educational data mining or EDM also aids in the understanding of use and check means of collection of large scale information from the settings to further improve the delivery of education (Roiger, 2017_This can ultimately help the students in educational organizations where these institutes get the chance to analyse assess and improve learning patterns of students based on the collected data. Use of data mining and business analytics in educational sectors has gained momentum over the years and it makes use of civil procedure such as clustering, classification and association. These techniques that are used in the educational industry may be Partitioning Methods, Impressive Association and Bayesian Classification (Lausch, Schmidt & Tischendorf, 2015). 
Banking sector: analytics and data mining techniques are very commonly and largely used in the banking sector. This is due to the fact that collection and storage of large number of personal data is required in banking sector which needs maintenance of confidentiality without losing any important data (Moro, Cortez & Rita, 2015). Account details, transaction details, personal details of purchase or transaction histories are stored with these banking sectors and modern technologies are required to store these data to avoid any kind of fraudulent activities. Due to the transaction of data the banking sector can identify and understand the trends of borrowers who are regular consumers and helps to disintegrate these was from non-regular individuals (Shmueli et al., 2017). Data mining tools can also help in understanding the financial feasibility of this customers by which day can take and pay loans through the bank. various algorithms in the use of analytics have been used in the banking sector for the purpose of data mining. These processes may be supervised and unsupervised functions and include various techniques. Supervised functions include Minimum Description Length, Generalized Linear Models, Support Vector Machine and Naïve Bayes. Unsupervised functions include K-Methods, Apriori, Non negative Factor Matrix Factorization, and One Class Support Vector Machine. All these mention techniques use regression techniques, classification techniques along with attribute importance, clustering, anomaly detection and feature extraction to solve various issues and stress related to data mining and data analysis.
Healthcare sector: The importance of data mining procedures within the Healthcare industry is a post importance because safekeeping and tabulation of data provides a lot of support to patient as well as health care professionals. Patient satisfaction as well as patient care depends on the use of proper data mining techniques. Tabulation of costs, proper storage of all relevant allergic and drug histories that might affect the patient’s treatment process as well as other personal and private information can be done in a proper and structured manner with the help of Data analytics and data mining techniques. Confidentiality within these personal files special should be maintained and as a result, modern techniques should be used and applied along with different strategies for favourable outcomes. Descriptive data mining techniques and predictive models are most commonly used in the Healthcare sector. Data analytics and data mining has grown as a large aspect of in various industries due to user friendly interface, and applicability. Several techniques that are used as descriptive data mining and predictive techniques solve different purposes and function under several circumstances within this sector to further evolve the progress and usability of the Healthcare sector.
Research findings on data mining and business analytics
Data mining and data analytical tools have a wide range of applicability in several industries due to easy benefits and values. Several researchers have been conducted and their findings have shown more light on the applicability of these tools in the selected industries of education, banking and Healthcare sectors. The research findings have been understood in detail to stress on the various values that have been added to the business due to the use of these tools within various aspects of the industries. These research findings highlight the positive aspects that these industries derive by applying data analysis and data mining tools:
Education sector: the applicability of Data analytics and various data mining tools in the education sector has been researched on a large scale but all impacts have not been understood by research.

1 ITECH7406- Business Intelligence and Data Warehousing Research Report Group Assignment Sem1-2019 Overview For this assignment, the students will work in team and create a written report that will...

Answer To: 1 ITECH7406- Business Intelligence and Data Warehousing Research Report Group Assignment Sem1-2019...

Answer To This Question Is Available To Download

Related Questions & Answers

Submit New Assignment