Data Analytics Capstone Project
Timeline
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October 18, 2023Experience start
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April 30, 2024Experience end
Experience scope
Categories
Data visualization Data analysis Data modelling Competitive analysis Data scienceSkills
power bi python (programming language) sql (programming language) deployment project tableau (business intelligence software) data analysis r (programming language) data collectionThis capstone course is aimed at enriching student success by combining the knowledge skills and tools students have learned throughout their program. The skills are used to complete a project on a real-world challenge presented by an instructor or an industry partner. Students will use appropriate analytics techniques and tools and best practices to present results to stakeholders. Students are familiar with Excel, Python, R, SQL, Power BI, Tableau and variety of other tools from prior coursework.
Learners
The course provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into a data analytics problem. The project can be an end-to-end application, including data collection & preparation, analysis, visualization, evaluation against success criteria and possible methods for deployment. Project results/ recommendations will be communicated in a final report.
Employers should submit a high-level proposal/business problem statement including a clear connection to data analysis, relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The course instructor will review the documents to confirm the scope and timing of the proposed problem and its alignment with the course requirements.
Project timeline
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October 18, 2023Experience start
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April 30, 2024Experience end
Project Examples
Requirements
- A final report detailing the problem, attempted solutions, and results, including benchmarks, if applicable.
- Ideas for next steps in the process based on project outcomes.
Timeline
-
October 18, 2023Experience start
-
April 30, 2024Experience end