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Data Analysis and Visualization

This guide was created to support Tulane faculty, staff, and students as they undergo data analysis and visualization tasks. If you have any questions about this guide or any suggestions for improved content, reach out to scholarlyengagement@tulane.edu

Defining Data Analysis and Visualizations

What is Data?

Data is information that can be analyzed to meet a business or research need. Data can include information that is ready for analytical processing, such as tabular data, and that which can be transformed for analytical processing. Analyzing data provides insights that can drive decision-making and policy making. Learning how to analyze and visualize data could prove useful in any professional or academic environment as stakeholders become increasingly interested in metrics.


What is Data Analysis?

Data analysis is the process of determining trends and features of the information provided in one or more data sets. Whether you are employing descriptive or inferential processes to your data, conducting data analysis allows you to understand your data in ways that are not apparent to your eyes. Data analysis should always be conducted ethically, paying special attention to who has access to sensitive or personal information. For more information on data analysis, explore the pages to the left.


What is Data Visualization?

Data visualization is the creation of tables, graphs, and other visual aids to represent the trends, features, and other information gleaned from data analysis. Data visualizations should be selected based on data type and business/academic need. While there is no "right" way to visualize data, there are best practices to follow. For more information on data visualization, explore the pages on the left. 

GIFs courtesy of GIPHY.com

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.