Research, Data Collecting & Visualisation & Storytelling

This DIXONTECH course equips professionals with essential skills to conduct data-driven research, master data collection techniques, and create impactful visual stories for communication and decision-making. Participants learn how to transform data into meaningful narratives using visualization tools and storytelling frameworks that engage and persuade diverse audiences effectively.

TRAINING TOPICS:

• Research Design and Data Collection Principles

• Quantitative and Qualitative Data Techniques

• Data Analysis and Visualization Tools

• Data Storytelling and Communication Strategies

• Presenting Insights for Business and Policy Impact

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

By the end of this DIXONTECH training, participants will:

• Design and conduct professional data-driven research

• Apply effective data collection and analysis techniques

• Use visualization tools to present findings clearly

• Create narratives that inspire decision-making

• Translate complex data into simple, visual stories

• Engage audiences with evidence-based storytelling

• Communicate insights that influence policies and outcomes

TRAINING IS TAILORED TO:

This course is designed for:

• Researchers and data analysts

• Policy and strategy officers

• Business and marketing professionals

• Communication and media specialists

• Project and program managers

• Data visualization designers

• Anyone presenting analytical findings to stakeholders

TRAINING METHODOLOGY:

DIXONTECH integrates hands-on research exercises, data analysis labs, and storytelling workshops using real-world cases. Participants apply professional research methods and visualization tools such as Power BI, Tableau, and Canva to create dynamic data stories. Group collaboration and feedback sessions reinforce learning through practice and creativity.

DAY 1: Research Design and Data Collection Principles

• Understanding research objectives and methodologies

• Differentiating quantitative and qualitative approaches

• Designing effective data collection instruments

• Identifying primary and secondary data sources

• Sampling strategies and population selection

• Ensuring reliability and validity in research

• Case study: defining a business research question

DAY 2: Quantitative and Qualitative Data Techniques

• Collecting quantitative and qualitative data effectively

• Using surveys, interviews, and observation tools

• Coding and categorizing qualitative data

• Organizing and cleaning quantitative datasets

• Data entry and management best practices

• Using Excel and SPSS for data handling

• Practical exercise: combining qualitative and quantitative insights

DAY 3: Data Analysis and Visualization Tools

• Introduction to descriptive and inferential analysis

• Choosing appropriate visualization methods

• Using Power BI and Tableau for visualization

• Designing data dashboards for clarity and insight

• Interpreting trends and patterns in data visuals

• Communicating uncertainty and limitations in visuals

• Workshop: creating effective visual summaries

DAY 4: Data Storytelling and Communication Strategies

• Fundamentals of storytelling with data

• Structure of a compelling data narrative

• Crafting key messages and story flow

• Balancing visuals and narratives for engagement

• Common mistakes in data storytelling

• Emotional and cognitive impact of visual stories

• Group activity: presenting a story-driven visualization

DAY 5: Presenting Insights for Business and Policy Impact

• Turning data findings into strategic recommendations

• Communicating research to decision-makers

• Creating visual reports and executive summaries

• Using storytelling in policy and organizational contexts

• Aligning data stories with goals and KPIs

• Case study: impactful data presentation to leadership

• Final presentation and feedback session