A short review of the four layers for storytelling with data.

1. The Power of Data-Driven Storytelling:
Unveiling the Layers of Insight

2. 1. Introduction
2. The Factual Layer
3. The Intentional Layer
4. The Structural Layer
5. The Presentation Layer
6. Assignment
Agenda

3. Introduction

4. The key elements of effective data storytelling are the factual layer, intentional layer,
structural layer, and presentation layer.
By addressing key elements in each layer, data storytellers can create compelling
narratives to effectively communicate complex data insights and drive meaningful
action.
Guided Notes are available here
Introduction

5. Mind Map

6. Facts Build
the
Foundation
Structure is
Built
Intention is
Defined
Presentation
has visual
appeal
Writing a Data-Driven Story

7. The Factual
Layer

8. Data Collection
The foundation of data-driven
storytelling lies in the meticulous
collection of raw data, encompassing
various sources and formats. This
stage sets the foundation to deriving
meaningful insights and narratives.
Data Preprocessing
Before the data can be transformed
into a compelling story, it undergoes
preprocessing, including cleaning,
transformation, and normalization.
This ensures that the data is
accurate, consistent, and ready for
analysis.
Importance and Accuracy
The accuracy and reliability of the
raw data are paramount, as any
flaws at this stage can significantly
impact the credibility and
effectiveness of the subsequent
layers.
Understanding Raw Data
Facts Build the
Foundation

9. Statistical Insights
Data analysis unveils patterns,
trends, and correlations within the
raw data, providing the basis for
deriving meaningful insights and
narratives. Statistical tools and
techniques play a pivotal role in
extracting valuable information.
Trend Identification
Through data analysis, trends and
anomalies emerge, offering a deeper
understanding of the underlying
dynamics. Identifying these trends is
crucial for crafting a compelling and
impactful narrative.
Real-World Example
The relationship between COVID-19
and the Great Resignation serves as
a poignant real-world example,
demonstrating the power of data
analysis in uncovering societal and
economic shifts.
The Role of Data Analysis
Facts Build the
Foundation

10. Case Study: The Great
Resignation

11. Data Analysis Insights
An analysis of resignations during the COVID-19 epidemic unveils the main causes and predictors of quitting, shedding light on the
societal and economic factors at play. This case study exemplifies the power of data analysis in understanding real-world
phenomena.
Impact on Organizations
The Great Resignation has reverberated across industries, prompting organizations to reevaluate their approaches to talent
management and employee engagement. The interplay between COVID-19 and the Great Resignation underscores the
significance of the factual layer in interpreting complex trends.
Lessons Learned
Extracting insights from the Great Resignation case study, we uncover valuable lessons that highlight the transformative potential
of data-driven storytelling in addressing contemporary challenges.
Case Study: The Great
Resignation

12. The
Intentional
Layer

13. Deriving Insights
The intentional layer focuses on distilling
the wealth of statistical data into
meaningful insights and messages that
resonate with the audience. It involves
translating raw numbers into compelling
narratives that convey the underlying
significance.
Storytelling with Data
The intentional layer emphasizes the art
of storytelling, weaving a narrative that
goes beyond numbers to evoke
emotions, convey meaning, and inspire
action. It involves infusing data with
context and purpose.
Real World Impact
By delving into the intentional layer, we
uncover how data-driven storytelling
has real-world implications, driving
decision-making, shaping perceptions,
and fostering understanding.
Conveying Meaning Through Insights
Intention is
Defined

14. Insights Into Human Behavior
The intentional layer delves into the behavioral aspects
illuminated by data analysis, shedding light on the
motivations, preferences, and trends that underpin human
actions. This human-centric approach adds depth to the
storytelling process.
Navigating Complexity
Navigate the complexity of the data, transforming it into a
coherent and impactful narrative that resonates with diverse
audiences.
Statistical Analysis and Trend Identification
Intention is
Defined

15. Meaningful Interpretation
The intentional layer emphasizes the
importance of meaningful interpretation,
where data is transformed into a narrative
that captivates and informs. It involves
infusing data with context, relevance, and
purpose.
Empowering Decision Making
By crafting compelling narratives, the
intentional layer empowers decision-
makers to glean actionable insights,
fostering a deeper understanding of the
implications and opportunities embedded
within the data.
Real World Example
The impact of COVID-19 on workforce
dynamics, as evidenced by the Great
Resignation, serves as a compelling real-
world example of the intentional layer in
action, showcasing the transformative
potential of data-driven storytelling.
Crafting Compelling Narratives
Intention is
Defined

16. The
Structural
Layer

17. Sequence and Pacing
The structural layer focuses on crafting a narrative structure
that ensures a seamless sequence, pacing, and flow of
information. It involves orchestrating the data-driven story to
captivate and engage the audience.
Contextual Framing
By contextualizing the data within a coherent narrative
structure, the structural layer enhances the audience's
understanding and emotional connection to the insights
presented.
Crafting a Compelling Narrative Structure
Structure is
Built

18. Strategic Sequencing
The structural layer delves into the strategic sequencing of
insights, ensuring that the narrative unfolds in a manner
that maximizes impact, comprehension, and retention. It
involves aligning the sequence of insights with the
audience's journey.
Engagement and Retention
By strategically sequencing insights, the structural layer
enhances audience engagement and retention, fostering a
deeper connection with the data-driven story and its
implications.
Sequencing Insights for Impact
Structure is
Built

19. The
Presentation
Layer

20. Visual Storytelling
The presentational layer emphasizes the art of visual
storytelling, where data is transformed into visually
appealing representations that enhance clarity,
comprehension, and engagement.
Infographics and Media
Leveraging infographics, charts, and multimedia elements,
the presentational layer enriches the data-driven story,
making it more accessible and impactful for diverse
audiences.
Visual Appeal and Clarity
Presentation has visual
appeal

21. Multifaceted Engagement
The presentational layer explores the multifaceted
engagement offered by multimedia representation,
leveraging visuals, audio, and interactive elements to
captivate and immerse the audience in the data-driven
story.
Interactive Data Visualization
By incorporating interactive data visualization, the
presentational layer fosters a dynamic and participatory
experience, enabling the audience to explore and
comprehend the insights on a deeper level.
Engaging Through Multimedia Representation
Presentation has visual
appeal

22. Aesthetic Appeal
The presentational layer places emphasis on aesthetic
appeal, ensuring that the design elements enhance the
visual experience and evoke an emotional connection with
the data-driven narrative.
Functional Clarity
Balancing aesthetic appeal with functional clarity, the
presentational layer optimizes the design elements to
convey the data-driven story with precision, coherence, and
impact.
Aesthetic and Functional Design
Presentation has visual
appeal

23. Assignment

24. Discussion Assignment
Research at least two different sources to collect data related to COVID and the Great Resignation. Using data from your
research, describe how using storytelling can help convey the message if COVID did or did not have a role in the Great
Resignation.
Discussion Assignment
Due
Sunday