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Data 101: Analyzing Data

In this LibGuide, we introduce you to the wide world of data, including data types (qualitative, quantitative, ethnographic, geospatial, etc.), finding data, visualizing data, and managing data.

                                                                     Image Description: Dual-monitor computer with computer code on one screen being used to analyze data.

What is Data Analysis?

Data analysis involves inspecting, cleaning, transforming, and (often) computationally modeling data to find information and trends within a dataset, and inform decision-making and lend insight towards hypotheses. Data analysis helps us turn data into meaningful information about the objects represented through the data. 

For an introductory view of data analysis using mean, median, and mode, check out this video: 


Helpful Resources at CMU Libraries

Learning About Tools for Data Analysis at CMU Libraries

CMU Libraries provides individualized training and group workshops to dozens of useful data analysis tools! Check out our list of (free!) workshops each semester that are open to anyone in the CMU community:

Examples of data analysis-themed workshop topics we regularly offer include: 

  • Cleaning Messy Data with OpenRefine
  • Introduction to Data Visualization in R 
  • Data Analysis in Jupyter Notebook
  • Text Analysis in R 
  • Network Analysis
  • Getting Started with Zotero

Data Analysis Engagement at CMU Libraries

CMU Libraries offers several opportunities for hands-on help and collaboration with your data analysis needs and general data education. These opportunities involve working with our very talented group of librarians and specialists, most of whom have several years of hands-on experience with data analytics! Check out some of our programs below for more information:

Data, Gaming, and Popular Culture Librarian

Profile Photo
Hannah Gunderman
410A Hunt Library
4909 Frew Street
Carnegie Mellon University
Pittsburgh, PA 15213
Office Phone: 412-268-7258


Data Collaborations Lab



The CMU Libraries Data Collaboration Lab (DataCoLAB) connects the research community across disciplinary borders, and facilitates collaborations between data producers and data scientists. The program connects researchers who want more from their datasets with individuals who have data and computer science skills, creating opportunities for people with different technical and disciplinary backgrounds to work together.

Want to learn more or ask questions? Email

Credits and Acknowledgements

Banner image courtesy of Fotis Fotopoulos on Unsplash, found here: Design made in Canva.