Applications of business analytics and data mining

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Reference no: EM132298708

Research Report

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.

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.

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 analyticscan 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.

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

Note: Need Research report along with presentation slides as mentioned in the assignment requirements

Attachment:- Business Intelligence and Data Warehousing.rar

Verified Expert

The current assignment is about business intelligence and data mining.The application of these aspects on various industries have been evaluated.The banking industry, education industry and customer relationship management have been considered to determine the usability of its applications.

Reference no: EM132298708

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