About the course
Extracting insights from data is only half of the job: bridging the gap between data and decision makers requires communication and design skills. In this course you will learn tools and techniques that will allow you to design and deliver technical presentations to a non-technical audience. The purpose is to present the results of your analysis to your stakeholders, in order to provide business value and gain trust.
This course goes beyond technical analysis to focus on the crucial final step: effectively conveying findings to influence decisions and drive action. Participants will learn to transition from exploratory data analysis (finding insights for themselves) to explanatory data analysis (packaging those insights clearly and persuasively for others). The training provides practical guidance on structuring compelling narratives around data, designing clear and impactful visualisations that resonate with the audience, and delivering presentations with confidence and clarity to stakeholders who may not share your technical background.
Through a blend of theoretical concepts, real-world examples, interactive discussions, and practical hands-on exercises, attendees will develop the confidence and skills needed to translate complex analytical results into understandable, memorable, and actionable stories. The course equips you to build credibility and trust with your stakeholders by presenting data insights in a way that directly highlights their business relevance and value, ensuring that your hard-earned analysis translates into meaningful outcomes and informed decisions.
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- Distinguish between exploratory and explanatory data analysis and understand the importance of the latter for effective communication.
- Effectively understand the context of a data analysis and identify the needs and background of the target audience.
- Critically review and evaluate the effectiveness of visual graphics used in data presentations.
- Choose appropriate and effective visualisations to convey specific data insights to a non-technical audience.
- Apply best practices for the clear and compelling delivery of data-driven presentations.
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This 2-day hands-on training course is designed for anyone who needs to communicate data analysis findings, technical information, or complex concepts effectively to non-technical audiences or decision-makers. It is ideal for:
Data Analysts and Scientists
Researchers and Statisticians
Business Intelligence Professionals
Consultants and Technical Presenters
Managers and team leads who need to effectively communicate data insights within their organizations.
Anyone who regularly creates or delivers presentations based on technical or data-driven work.
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Participants should have:
Experience performing data analysis and extracting insights from data.
The ability to use tools to generate basic charts and graphs.
Note: This course focuses on communicating data insights, not on teaching specific data analysis techniques or how to use particular visualization tools. Participants are expected to be able to perform the analysis and create initial visuals using their tools of choice.
We can customise the training to match your team's experience and needs - for instance by prefacing this workshop with a technical data analysis course focusing on a technology such as Python (Pandas, Numpy...), Power BI, or R.
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This Data Storytelling course is available for private / custom delivery for your team - as an in-house face-to-face workshop at your location of choice, or as online instructor-led training via MS Teams (or your own preferred platform).
Get in touch to find out how we can deliver tailored training which focuses on your project requirements and learning goals.
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Introduction to Data Storytelling
What is Data Storytelling and why is it essential in today's data-driven world?
The problem: The communication gap between technical analysis and business decisions.
Understanding the purpose of data communication: Providing business value and gaining trust.
The role of communication and design skills in bridging the gap.
Exploratory vs. Explanatory Data Analysis
Exploring data: Discovering insights for yourself.
Explaining data: Packaging and presenting insights for others.
The crucial shift in mindset and approach.
Identifying the key message(s) from your analysis.
Understanding Context and Audience
Understanding the business context: The problem you are trying to solve or the question you are answering.
Identifying and understanding your target audience(s).
What are their goals, priorities, and existing knowledge?
What action do you want the audience to take based on your insights?
Tailoring your data story, language, and level of detail to resonate with the audience.
Principles of Effective Visuals
The power and purpose of data visualisation in storytelling.
Choosing integrity: Avoiding misleading or confusing visuals.
Key principles of effective design: Clarity, accuracy, efficiency.
Minimizing clutter and 'chartjunk'.
Leveraging preattentive attributes (colour, size, position) to guide the audience's attention.
Cognitive load and how to reduce it in your visualisations.
Examples & Discussion: Critiquing examples of effective and ineffective data visualisations.
Choosing Effective Visuals
Reviewing common chart types and their appropriate uses (e.g., bar charts, line charts, scatter plots, histograms, maps).
Choosing the right chart type based on the data type and the message you want to convey.
When tables are more effective than charts.
Using text effectively within visuals.
Practical Exercise: Given different data scenarios and messages, choose the most appropriate visualisation type.
Designing Clear Visuals
Best practices for designing specific chart elements: titles, labels, legends, axes.
Using colour strategically and effectively, considering accessibility.
Annotating charts and graphs to highlight the most important insights directly.
Arranging multiple visuals (dashboard design principles - simplified).
Ensuring consistency in visual design.
Hands-On (Tool Agnostic) Lab: Redesigning existing charts to improve clarity and impact.
Structuring the Data Narrative
The power of storytelling: Why narrative is effective for communication.
Structuring your data story: Beginning (context), Middle (analysis/insights), End (conclusion/call to action).
Defining the core narrative and supporting points.
Ordering information logically for maximum impact and flow.
Using transitions effectively between slides or points.
Crafting a compelling opening and a clear call to action.
Practical Exercise: Outline a data narrative based on a provided dataset or scenario.
Presentation Delivery
Key principles of effective presentation delivery.
Connecting with your audience: Building rapport and credibility.
Explaining complex visuals clearly and concisely.
Pacing and flow of your presentation.
Handling questions and addressing challenges from the audience effectively.
Conveying confidence and enthusiasm for your insights.
The importance of practice and preparation.
Putting it all Together & Practice
Integrating your understanding of audience, effective visuals, and narrative structure into a cohesive presentation.
Brief overview of tools commonly used for creating data presentations (e.g., PowerPoint, Google Slides, Keynote, potentially mentioning data-specific tools like Tableau Dashboards, RMarkdown presentations etc., focusing on applying principles regardless of tool).
Mini-Presentation Practice Sessions: Participants deliver a short data story presentation and receive constructive feedback.
Review of key concepts and next steps for applying data storytelling skills.
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"Storytelling with Data: A Data Visualization Guide for Business Professionals" by Cole Nussbaumer Knaflic: A widely recommended book on the subject.
"DataStory: Explain Data and Inspire Action Through Story" by Nancy Duarte: Another valuable book focusing on narrative structure.
Effective data visualisation principles: Resources from experts like Stephen Few or concepts derived from Edward Tufte's work focus on display accuracy and efficiency. (Search online for "Stephen Few data visualization" or "Edward Tufte principles").
Good presentation design practices: https://www.presentationzen.com/presentationzen/.
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