Dedoose

Dedoose is a cloud-based software platform designed for qualitative and mixed-methods research. It enables users to import and analyse a wide variety of data types — including interview transcripts, focus-group audio/video, images, survey‐data, and quantitative spreadsheets — and combine them within unified analytic workflows. 

Who it serves & how
Dedoose is aimed at researchers, evaluators, and teams working in fields such as social science, health research, market research, education, and public policy. As a web-accessible tool, it supports real-time collaboration and cross-site access, meaning team members can work from different locations and devices.
Use-cases include.

• Coding qualitative data (text, audio, image) and linking to quantitative variables (e.g., demographics, survey responses)
• Visualising data through interactive charts, filters, and dashboards to explore patterns or segments
• Team collaboration: sharing projects, applying codes across datasets, reviewing inter-rater consistency
• Mixed-methods integration: merging numeric data with textual or multimedia content to support comprehensive analysis

Key features & value proposition

• Multi‐format data support: Dedoose handles spreadsheets, text files, audio, video, images and more. 
• Cloud-based platform with cross-platform compatibility (Windows/Mac/Linux via browser) and real-time collaboration. 
• Visualisation tools: bar charts, bubble charts, time-series, code‐co-occurrence matrices and filters for exploring coded data. 
• Integrating qualitative and quantitative: ability to import numeric variables alongside coded qualitative data, enabling mixed-methods analytics rather than separate workflows. 
• Flexible pricing & subscriptions: Dedoose offers individual, team, organisational plans with trial options. 

Considerations

• As a web/cloud service, user experience depends on network connectivity and browser compatibility. Some institutions may prefer locally hosted software for sensitive data.
• While Dedoose simplifies many mixed-methods workflows, users must still exercise rigorous research design, coding frameworks, inter-rater reliability and transparent analytic decisions. The software facilitates but does not replace good practice.
• Mastering advanced features (e.g., filters, matrix displays, mixed-variable integration) may require a learning curve, especially for research teams used to simpler tools or spreadsheets.
• Data security and compliance should be reviewed: although Dedoose advertises high standards, teams handling sensitive or identifiable data in regulated settings should ensure local policies are satisfied.