Training course

Overview

Qualitative Data Analysis for Professionals is a practical workplace-focused training course designed to equip researchers, analysts, programme professionals, consultants, academics, and other evidence-focused practitioners with the skills required to analyse qualitative information systematically and turn it into credible, actionable professional insights. The course addresses the complete qualitative data analysis workflow, from defining analytical questions and preparing research data through coding, thematic interpretation, validation, reporting, and presentation. It is particularly relevant to professionals working with interviews, focus groups, observations, open-ended questionnaires, field notes, documents, case studies, and stakeholder feedback.

The programme establishes strong professional foundations in qualitative research methodology, analytical alignment, sampling, data preparation, transcription, anonymisation, data organisation, coding, and documentation. Participants learn practical approaches for managing qualitative datasets generated through workplace research, programme evaluation, customer research, employee studies, market research, policy analysis, community engagement, and organisational assessments. Practical tools such as NVivo, ATLAS.ti, MAXQDA, Dedoose, Microsoft Word, Excel, and structured manual coding workflows are incorporated to help participants select appropriate approaches for different project requirements and levels of analytical complexity.

Participants progressively develop professional skills in thematic analysis, framework analysis, content analysis, narrative analysis, case study analysis, comparative analysis, and structured qualitative interpretation. Emphasis is placed on creating defensible codebooks, identifying meaningful patterns, developing themes, analysing differences across groups, documenting analytical decisions, and connecting findings directly to research questions and professional objectives. Practical exercises and realistic case studies address common workplace scenarios involving customer satisfaction, employee experience, programme performance, stakeholder engagement, service delivery, market research, policy implementation, and organisational change.

The advanced component develops professional capabilities in qualitative rigour, triangulation, reflexivity, negative-case analysis, member checking, peer review, analytical audit trails, mixed-methods integration, qualitative visualisation, and evidence-based reporting. Participants learn how to assess the credibility of qualitative findings, recognise analytical bias, communicate uncertainty and limitations, and transform qualitative evidence into professional reports, management briefs, presentations, dashboards, and decision-support outputs. Through practical software exercises, real-world scenarios, case studies, and an integrated capstone, the course enables participants to complete a structured qualitative analysis and communicate findings effectively to professional and stakeholder audiences.

Course Duration

5 Days (40 Hours)

Target Participants

This course is suitable for:

• Research officers, research analysts, and research assistants

• Monitoring, Evaluation, Research, and Learning (MERL) and Monitoring and Evaluation (M&E) professionals

• Programme, project, and development professionals conducting qualitative assessments

• Market research, customer insights, and consumer research professionals

• Human resources, employee experience, and organisational development professionals

• Policy, planning, and institutional research professionals

• Operations, service delivery, and performance professionals working with qualitative evidence

• Consultants and advisory professionals conducting workplace and client research

• Academics, lecturers, postgraduate researchers, and professionals undertaking applied research

• Community engagement and field research professionals

• Professionals responsible for analysing interviews, focus groups, observations, documents, and open-ended survey responses

• Research managers and professionals responsible for reviewing qualitative research outputs

• Professionals transitioning from quantitative analysis to qualitative and mixed-methods research

• Professionals seeking practical experience with NVivo, ATLAS.ti, MAXQDA, Dedoose, Excel, and manual qualitative analysis

Course Objectives

By the end of the training, participants will be able to:

• Apply a structured professional workflow for qualitative data analysis from research questions through final reporting

• Translate workplace and research objectives into appropriate qualitative analytical questions and frameworks

• Select appropriate qualitative research designs, sampling approaches, and data sources for professional studies

• Prepare, organise, anonymise, document, and manage qualitative research datasets effectively

• Develop practical codebooks, coding protocols, metadata structures, analytical memos, and audit trails

• Apply descriptive, open, focused, inductive, deductive, and pattern coding approaches

• Conduct thematic, framework, content, narrative, case study, and comparative qualitative analysis

• Identify patterns, relationships, differences, contradictions, participant perspectives, and contextual explanations

• Develop themes and analytical interpretations that remain clearly grounded in qualitative evidence

• Use NVivo, ATLAS.ti, MAXQDA, Dedoose, Excel, Word, and manual coding methods appropriately

• Apply triangulation, reflexivity, member checking, peer review, negative-case analysis, and other quality assurance techniques

• Evaluate credibility, dependability, confirmability, and transferability of qualitative research findings

• Identify researcher influence, confirmation bias, selective interpretation, and other threats to analytical quality

• Integrate qualitative findings with quantitative evidence within practical mixed-methods research projects

• Create qualitative data displays, matrices, thematic networks, conceptual diagrams, and evidence summaries

• Produce professional qualitative research reports, management briefs, presentations, and stakeholder communications

• Apply ethical principles relating to informed participation, confidentiality, anonymisation, privacy, and responsible data management

• Establish reproducible and well-documented qualitative research workflows

• Conduct an integrated qualitative analysis project using a realistic professional research dataset and scenario

Course Content

Day 1: Professional Qualitative Research Foundations, Data Preparation, and Analytical Workflow

Module 1: Professional Qualitative Research Methodology and Data Management

1.      Role of Qualitative Data Analysis in Professional Research, Programme Evaluation, Business, Policy, and Organisational Decision-Making

2.      Translating Professional Problems into Qualitative Research Questions, Objectives, Analytical Questions, and Frameworks

3.      Qualitative Research Designs: Case Study, Phenomenology, Ethnography, Grounded Theory, Narrative, and Participatory Approaches

4.      Professional Qualitative Sampling: Purposive, Criterion, Maximum Variation, Convenience, Snowball, and Theoretical Sampling

5.      Qualitative Data Sources: Interviews, Focus Groups, Observations, Documents, Open-Ended Surveys, Field Notes, and Stakeholder Feedback

6.      Transcription, Translation, Anonymisation, Data Cleaning, Context Preservation, and Preparation for Analysis

7.      Qualitative Data Management: File Structures, Naming Conventions, Metadata, Data Dictionaries, Version Control, and Documentation

8.      Data Familiarisation, Repeated Reading, Initial Reflections, Analytical Notes, and Researcher Memos

9.      Practical Qualitative Analysis Tools: NVivo, ATLAS.ti, MAXQDA, Dedoose, Excel, Word, and Manual Coding Workflows

10.  Case Study and Exercise: Preparing, Organising, Documenting, and Familiarising With a Professional Interview, Focus Group, or Stakeholder Dataset

Day 2: Professional Coding, Categorisation, and Thematic Analysis

Module 2: Applied Coding and Development of Evidence-Based Themes

1.      Principles of Qualitative Coding: Meaning Units, Data Segments, Codes, Labels, and Analytical Decisions

2.      Descriptive, Open, In Vivo, Process, Values, and Initial Coding Techniques for Professional Research

3.      Focused Coding, Pattern Coding, Categorisation, Code Consolidation, and Developing Analytical Categories

4.      Building Professional Codebooks: Code Definitions, Inclusion and Exclusion Criteria, Coding Rules, and Examples

5.      Inductive, Deductive, and Hybrid Coding Approaches for Workplace and Applied Research

6.      Thematic Analysis: Familiarisation, Coding, Theme Development, Theme Review, Definition, and Reporting

7.      Identifying Patterns, Relationships, Differences, Contradictions, and Contextual Meaning Across Qualitative Data

8.      Analytical Memo Writing, Reflexive Notes, Coding Decisions, Analytical Questions, and Evidence Tracking

9.      Software-Based Coding, Data Retrieval, Querying, Coding Comparison, Case Classification, and Dataset Organisation

10.  Case Study and Exercise: Coding Professional Interview or Focus Group Data and Developing an Evidence-Based Thematic Framework

Day 3: Applied Qualitative Analysis, Comparison, and Professional Interpretation

Module 3: Professional Interpretive Analysis and Evidence Development

1.      Framework Analysis for Programme Evaluation, Policy Research, Organisational Studies, Customer Research, and Service Assessment

2.      Qualitative Content Analysis: Categories, Manifest and Latent Content, Context, Patterns, and Interpretation

3.      Narrative Analysis: Participant Stories, Experiences, Chronology, Turning Points, Identity, and Meaning

4.      Case Study Analysis: Within-Case Analysis, Cross-Case Comparison, Pattern Matching, and Contextual Explanation

5.      Comparative Qualitative Analysis Across Departments, Locations, Customer Groups, Stakeholders, Programmes, or Time Periods

6.      Matrix Analysis, Data Displays, Evidence Tables, Conceptual Mapping, and Relationship Mapping

7.      Identifying Negative Cases, Contradictions, Deviant Evidence, Alternative Explanations, and Analytical Exceptions

8.      Moving From Description to Interpretation: Developing Professional Explanations and Connecting Findings to Research Objectives

9.      Evidence Grounding, Quotation Selection, Analytical Claims, Contextual Interpretation, and Avoiding Unsupported Conclusions

10.  Case Study and Exercise: Conducting Comparative or Framework-Based Analysis to Identify Professional Patterns, Differences, Drivers, and Explanations

Day 4: Advanced Professional Qualitative Rigour, Validation, and Mixed-Methods Analysis

Module 4: Qualitative Quality Assurance, Research Validation, and Evidence Integration

1.      Trustworthiness in Professional Qualitative Research: Credibility, Dependability, Confirmability, and Transferability

2.      Triangulation Across Data Sources, Methods, Stakeholder Perspectives, Researchers, Cases, and Contexts

3.      Researcher Reflexivity, Positionality, Assumptions, Interpretation, and Managing Researcher Influence

4.      Intercoder Processes, Collaborative Coding, Coding Comparison, Disagreement Resolution, and Analytical Consistency

5.      Member Checking, Participant Validation, Peer Debriefing, Expert Review, and Stakeholder Validation

6.      Analytical Audit Trails, Decision Logs, Version Control, Research Memos, and Transparent Documentation

7.      Identifying Analytical Bias, Confirmation Effects, Selective Interpretation, Over-Generalisation, and Weak Evidence Claims

8.      Integrating Qualitative and Quantitative Evidence in Mixed-Methods Research and Professional Evaluation

9.      Qualitative Visualisation: Thematic Networks, Matrices, Concept Maps, Process Maps, Timelines, and Evidence Displays

10.  Case Study and Exercise: Validating Professional Qualitative Findings Through Triangulation, Reflexivity, Peer Review, Negative Cases, and Mixed-Methods Evidence

Day 5: Professional Qualitative Reporting, Governance, and Applied Capstone

Module 5: Professional Qualitative Research Practice, Reporting, and Capstone

1.      From Codes and Themes to Professional Findings, Interpretations, Conclusions, and Practical Implications

2.      Selecting and Presenting Participant Quotations, Evidence Excerpts, Context, Themes, and Analytical Support

3.      Writing Professional Qualitative Methodology, Analysis, Findings, Discussion, Conclusions, and Recommendations

4.      Developing Research Reports, Management Briefs, Executive Summaries, Policy Briefs, Presentations, and Stakeholder Outputs

5.      Qualitative Research Ethics: Informed Participation, Confidentiality, Anonymisation, Sensitive Information, and Participant Protection

6.      Data Governance and Security: Access Controls, Secure Storage, Data Retention, Responsible Sharing, and Research Accountability

7.      Reproducible Qualitative Research Workflows Using Codebooks, Memos, Audit Trails, Software Projects, Structured Files, and Version Control Principles

8.      Integrated Case Study: Completing an End-to-End Professional Qualitative Analysis From Raw Research Data to Validated Findings and a Professional Report

9.      Professional Exercise: Reviewing a Qualitative Analysis for Coding Quality, Evidence Support, Analytical Rigour, Bias, Transparency, and Trustworthiness

10.  Capstone Exercise: Designing the Analytical Framework, Preparing and Coding Professional Qualitative Data, Developing Themes, Validating Findings, Interpreting Evidence, and Presenting a Professional Qualitative Research Report