Introduction:

This experience invites learners who have completed the foundational modules of the Data Analysis program at Calbright College to engage in real-world projects. Learners will apply their knowledge of data analysis, SQL, and data storytelling to solve industry-relevant challenges. Our learners are equipped to present data-driven solutions that address the needs of your organization, helping inform better decision-making through their analysis and research.

Learners will work individually or in small groups of 2-4 students, based on the number of students enrolled at the time.

*Project start date is flexible, but projects need to be submitted before June 15 and projects must be finished before June 30 2025*

Expectations from Partners:

Partners are expected to provide clear project objectives, datasets (if applicable), and a point of contact for communication and feedback. We anticipate active engagement throughout the project. In return, partners will gain fresh insights into their data and actionable recommendations tailored to their business needs.

1. Data Quality Assessment Report

• Description: A comprehensive report assessing the quality of a given dataset, using three dimensions of data quality (completeness, validity, accuracy). The report will include a written explanation of how each criterion was evaluated, alongside relevant examples.
• Deliverable: A report assessing the dataset’s suitability for analysis and recommendations for improving data quality where necessary.
• Skills Developed: Data analysis, critical thinking, attention to detail, quality assurance.

2. Data Analysis Presentation

• Description: A final presentation that synthesizes the analysis of data, utilizing key techniques for effective data presentation. The student will include data visualizations (e.g., charts, graphs) and a video presenting their findings to inform and inspire an audience.
• Deliverable: A 4-6 slide presentation with a recorded video/audio component (3-6 minutes) showcasing data analysis and visualization, including sources and techniques used for effective data presentation.
• Skills Developed: Data presentation, storytelling with data, use of presentation tools like Canva, Google Slides, or Zoom.

3. Data Management Plan

• Description: A detailed data management plan outlining how sensitive data (e.g., SSNs, health information) should be handled, stored, and accessed. This deliverable will include sections on data types, access roles, metadata standards, and recommendations for data quality checks.
• Deliverable: A structured plan document (2-3 pages) identifying sensitive data, data roles, and documentation standards, accompanied by recommendations for data handling and quality assurance.
• Skills Developed: Data stewardship, data privacy, project management, and documentation.