Explain the relevance to the industry

Assignment Help Business Management

Reference no: EM132985397 , Length: word count:2000

BUSI 650 Business Analytics - University Canada West

IDEA
The idea of this project is familiarize MBA candidates with the industry and area of expertise. The project allows students to create their own team (maximum 5 people per team) with mixed skillsets and work closely together to tackle business problems or opportunities in various facets of industry domains as well as fields of interest (Finance, Marketing, Operations, HR, etc.).

EXPECTATIONS
Teams will be expected to use data to identify the problems or trends and patterns in their area of interest. The process of identifying patterns or trends would be primarily based on the use and analytics of data using various tools and techniques discussed in the class. The candidates should be able to explain the significant changes in their data. Teams may use other techniques (subject to approval).

1.0 Introduction (~500)

1.1 Introduction
• Discuss the background of the analysis/research
• Explain the relevance to the industry or company used in the analysis in conjunction with the current business environment
• In a paragraph explain the purpose of the research, the relevance of the problem to the current business environment

1.2 Scope and Objectives (deliverables)
• Scope: Clarify the scope of the analysis or research
• Objectives: clearly state the objective (similar to a research statement)

2.0 Background Research/Literature Review (~800)

2.1 Business
• Use more than peer-reviewed papers or/and reputable media articles/opinions
• The papers/articles/opinions must be associated with the area of analysis/research and should be cohesively analyzed

3.0 Methodology (~700)

3.1 Data
• Discuss the data** collected
• There must be at least 1,000 observations
• Explain how does it relate to the research/Analysis
• Mention the time frames and sources of the data

3.2 Tools/Analytics
• Mention the tools and techniques used to analyze the data, including
o Data Visualization using Tableau (required)
o Clustering/Unsupervised Learning using Excel/R/Python (required)
o Classification/Supervised Learning using Excel/R/Python (optional)
o Neural Networks/Deep Learning using Excel/R/Python (option)
• Explain how it addresses the analysis or research

4.0 Analysis (~2500)
• Align this section with 3.2 and explain how the data was analyzed
• Note changes in tools or methodology (if any)

4.1 Analysis
• Elaborate the results found in 4.1 and explain how it addresses the objectives
• Explain how the results are in conjunction to section 2.0
• Graphs and explanation

5.0 Conclusion (~500)
• Use sections 2, 3, and 4 and provide conclusive remarks
• Provide solution to the problem along with some empirical evidence

WORD LIMIT
5,000 words (excluding tables, graphs, bibliography and appendix) (± 10%)
APA style paper and referencing

Attachment:- Team Project.rar

Reference no: EM132985397

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Reviews

len2985397

9/9/2021 9:55:26 PM

I only need part 4. In part four please use excel for data cleaning, K-Mean clustering, Logistic regression, Naive byes, Tableau for data visualization, and then analysis of which model is best. This process is called CRISP-DM. Please do not write in general. I need an excel sheet for cleaning, clustering, logistic regression, naive byes, also need Tabkeaue files for all 8 steps. I also need PPT slides for the presentation for step 4. I am Business Student, not an IT. so I don''t need coding.

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