HMIS data analysis doesn’t stop at CSV exports — today’s administrators need the tools to automate reports, visualize trends, and perform deep data validation. R and Python offer powerful, free, and flexible ways to make that happen.

This course introduces HMIS Administrators to the practical use of R and Python for homelessness data. You’ll learn how to import, clean, and analyze HMIS datasets; build simple dashboards; and automate recurring reports like the APR, SPMs, or custom agency metrics. The focus is on real-world workflows — not theory — giving you the confidence to move beyond Excel and use data science tools to improve your system’s performance and efficiency.

What You’ll Learn

• The benefits of using R and Python for HMIS data analysis
• How to install, configure, and set up RStudio or Jupyter Notebooks
• Importing and cleaning HMIS CSV exports (e.g., APR, SPM, or custom reports)
• Data validation and quality checks with code-based workflows
• Basic analytics: summaries, counts, and visualizations
• Building automated dashboards and recurring reports
• Writing scripts to streamline data prep for submissions
• Ethical and secure handling of HMIS data using code-based tools
• Where to find libraries, templates, and sample scripts for reuse