Purpose

QDA Miner is a qualitative data analysis software designed to assist researchers in organising, coding, annotating, retrieving, and analysing textual and visual data. Its purpose is to facilitate systematic and rigorous qualitative analysis for a variety of research domains, such as social sciences, healthcare, journalism, and market research. By combining qualitative coding with integrated quantitative content analysis and statistical tools, QDA Miner enables mixed-methods research that leverages comprehensive data exploration and interpretation.

Release Date

QDA Miner was first released in 2004, developed by Normand Péladeau and Provalis Research. It has undergone progressive enhancements, with the latest major version (version 6) released in 2020, incorporating advanced features such as improved visualization tools, integration with content analysis software WordStat, and statistical functionalities. The software has established itself as a mature, reliable tool widely adopted in qualitative and mixed methods research globally.

Features

QDA Miner offers a broad range of powerful features tailored for efficient qualitative data handling:

• Support for importing multiple file formats including text documents (PDF, Word, RTF), spreadsheets (Excel, CSV), images, audio, and video files.
• Advanced coding tools to mark and classify data segments with intuitive code trees, annotations, and memos.
• Automatic coding assistance with keyword search, cluster extraction, and proximity operators facilitating rapid qualitative coding.
• Integration with WordStat for quantitative content analysis and SimStat for statistical analysis enabling mixed methods workflows.
• Visualization capabilities including thematic maps, word clouds, heatmaps, correspondence plots, and multi-dimensional scaling.
• Retrieval and query functions allowing complex text searches and data segmentation by codes, cases, or variables.
• Geographic information system (GIS) mapping and geotagging features to link spatial data with qualitative content.
• Collaborative project management with exportable reports, tables, graphs, and project files supporting teamwork and dissemination.
• Track changes and project versioning ensuring data integrity during long-term analyses.

Student Usability