A design approach that uses data analysis to inform and enhance design decisions, ensuring user needs are met.

A collection of work showcasing a designer's skills, projects, and ability to incorporate data into design.

The process of inspecting, cleansing, and modeling data to discover useful information for decision-making.

Software applications used to create visual representations of data, making insights easier to understand.

Fundamental concepts that guide the creation of effective and aesthetically pleasing designs.

Non-numeric data that describes qualities or characteristics, often gathered through interviews or open-ended surveys.

Numeric data that can be measured and analyzed statistically, often collected through structured surveys.

Requirements and preferences of end-users that inform design decisions to enhance usability.

The systematic gathering of data from various sources to support analysis and decision-making.

Meaningful interpretations derived from data analysis that guide design choices.

Creating preliminary models of a design to test ideas and gather feedback before final implementation.

A design process that involves repeated cycles of prototyping, testing, and refining based on feedback.

Basic visual guides that represent the skeletal framework of a digital product, outlining structure and functionality.

In-depth examinations of specific instances where data-driven design principles were successfully applied.

The practice of using data visuals and narratives to communicate insights effectively.

A process where designers gather feedback on their work to inform future iterations and improvements.

A document outlining the objectives, target audience, and constraints for a design project.

Principles guiding the responsible collection and use of data, ensuring privacy and consent.

Mathematical techniques used to analyze and interpret data, often fundamental for data-driven design.

Patterns or tendencies observed in data over time, which can inform design strategies.

The aesthetic and functional aspects of a design that enhance user experience and engagement.

The reasoning behind design decisions, often supported by data insights and user feedback.

The appeal and potential success of a designer's skills and portfolio in the job market.

Conversations aimed at understanding user needs and preferences, often used as a data collection method.

Methods used to process and interpret data, such as statistical analysis and data visualization.