Data Literacy at Lehigh

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Data Literacy is the ability to read, understand, analyze and communicate with data effectively.

Effective Components of Data Literacy

Data Awareness

Understanding what data is, the different types (structured and unstructed), and how it is generated, collected and stored.

Data Sources

Knowing where to find data, whether in internal databases, public repositories or third-party sources.

Data Collection

Skills in collecting data ethically, accurately, and efficiently, including designing surveys, setting up data collection systems, etc.

Data Cleaning and Preprocessing

Ability to clean, preprocess, and wrangle raw data into usable formats for analysis, including dealing with missing values, outliers and inconsistencies.

Data Analysis

Skills in using tools like Excel, SQL, Python, or R to analyze data, perform statistical tests, create visualizations, and derive insights.

Data Visualization

Communicating data insights effectively though charts, graphs, dashboards and other visual means to make complex information more understandable.

Data Interpretation

Interpreting data results accurately, understanding correlations, causation, statistical significance, and limitations of the data.

Data Ethics and Privacy

Knowledge of ethical considerations in handling data, including privacy, security, bias, and responsible data use.


Ability to communicate data findings and insights to different stakeholders, translating technical jargon into layman's terms.

Continuous Learning

A mindset of continous learning and adaptation as data technologies, tools and practices evolve.

These components collectively empower individuals to leverage data effectively for decision-making, problem-solving, innovation and creating data-informed strategies. Below are resources that are available to our Lehigh community.

This page is constantly being updated, bookmark it and check often for new additional resources.