Senior Design Project
Timeline
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January 13, 2020Experience start
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January 21, 2020Project Scope Meeting
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January 28, 2020Data Understanding/Data Preparation
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February 11, 2020Modeling
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May 9, 2020Final Report
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May 9, 2020Experience end
Timeline
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January 13, 2020Experience start
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January 21, 2020Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
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January 28, 2020Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
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February 11, 2020Modeling
Students should generate documentation outlining the intended/exercised data modeling technique used on the data to generate insight and recommendations.
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May 9, 2020Final Report
Students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
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May 9, 2020Experience end
Experience scope
Categories
Information technology Data analysis Product or service launchSkills
business analytics data analytics data analysis software development software designA group of 20 senior design students from North American University will help your organization with data analysis projects. Students are trained in data extraction and transformation as well as data preparation, data modeling and reporting on pre-existing data gathered by the organization. These students will work with your organization to analyze data sets and provide any recommendations they may have as a result of the analysis.
Learners
The final project deliverable will include:
- A 10 to 20-page report outlining the work they performed, any analysis they conducted including visualizations and any recommendations they may have as a result of analysis.
- A 20-minute presentation of the project and results to the industry partner and classmates.
Project timeline
-
January 13, 2020Experience start
-
January 21, 2020Project Scope Meeting
-
January 28, 2020Data Understanding/Data Preparation
-
February 11, 2020Modeling
-
May 9, 2020Final Report
-
May 9, 2020Experience end
Timeline
-
January 13, 2020Experience start
-
January 21, 2020Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
January 28, 2020Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
-
February 11, 2020Modeling
Students should generate documentation outlining the intended/exercised data modeling technique used on the data to generate insight and recommendations.
-
May 9, 2020Final Report
Students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
May 9, 2020Experience end
Project Examples
Requirements
Once the project begins in January student teams will begin assisting your organization by providing analytical research and making educated suggestions on some of your companies data opportunities of challenges.
Examples may include but are not limited to
Assist organizations in data gathering research and/or prepare data for future use by the organization. Students can help design and model databases to gather and store data for future analysis.
- Help with analyzing existing data. Students may perform data quality checks, data cleaning, and data transformation exercises on existing data to ready data for analysis by the organization.
- Using organizational data, students may conduct data analysis and design data analytics reports to be delivered to the firm.
Project examples include but are not limited to:
- Students can provide analysis of customer segmentation relative to different products and services. This process will help improve your organization's marketing campaigns and refocus your products/services.
- Help with Investigating predictive models to understand trends in sales, attrition rates, and profits that impact your business.
- Propose new ways to visualize data through tables and plots that will managers gain new insights and make better decisions.
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
Provide a member of your organization to discuss to the class the project scope at the start of the project and be available for the final presentation in May. Could be in person or remote.
Be available for a quick phone call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the course.
Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address students' questions.
Timeline
-
January 13, 2020Experience start
-
January 21, 2020Project Scope Meeting
-
January 28, 2020Data Understanding/Data Preparation
-
February 11, 2020Modeling
-
May 9, 2020Final Report
-
May 9, 2020Experience end
Timeline
-
January 13, 2020Experience start
-
January 21, 2020Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
January 28, 2020Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
-
February 11, 2020Modeling
Students should generate documentation outlining the intended/exercised data modeling technique used on the data to generate insight and recommendations.
-
May 9, 2020Final Report
Students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
May 9, 2020Experience end