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Data Literacy





Credit Hours


Introduction to the methods, tools, and techniques for working with “quant” data in the design process

Data literacy – the ability to confidently evaluate, interpret, and craft compelling stories with data – is a critical skill for designers working with data-smart products and interdisciplinary teams. But as a new skill for many, data analysis and interpretation can be intimidating – not only what to do with the data, but how.

This 7-week bootcamp-style course offers a tactical introduction to the methods, tools, and techniques for working with “quant” data in the design process. Students will use analytic software (Excel, Tableau, etc.) to describe and transform a wide range of common data types, gain exposure to advanced and applied analytics in the workplace, and develop perspectives on evaluating “good” from “bad” data.

Learning Objectives

  • Beyond basics with common analytic software, including cleaning and formatting data for analysis, pivot tables, writing functions and custom formulas, and creating advanced data visualizations
  • Bridging theory and practice to evaluate what makes both data and data representations “good” or “bad” – technically, analytically, and socially
  • How to work with typical data structures seen in the design process, like time series, census, and geospatial
  • How and where data is impacting the design process in business

Learning Outcomes

This class will get students working with data quickly – providing a foundation for new designer/data “translator” roles in business.  Students will gain useful best-practice skills they can apply to practice and future courses, developing a foundation for approaching data problems in the design process.

Format & Grading

Each week will explore a different aspect of working with data, supported by discussion, in-class tutorial, and homework assignments. We will use a variety of software (e.g. Excel, Tableau) in class each week, so bring your laptop with software installed.

No prior experience working with quantitative data is required for this course. Student evaluation will be based on participation and contribution to class activities, and by demonstrating mastery of discussed techniques.

Enrollment Restrictions

No prerequisites. This course is open to all Institute of Design students