LESSON HIGHLIGHTS:

• Data Literacy: the ability to understand and communicate or share data effectively.

• It is essential in today’s Data Economy.

• As our dependence on data for insights increases, so the need for greater data literacy also increases.

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LESSON HIGHLIGHTS:

• Definitions of INSIGHT (Gary Klein):

  • Discoveries based on data analysis and interpretation

  • Unexpected shifts in our understanding and examination of data

  • Transform thinking to create business value

  • Shift us toward a new and better story

• If the insight isn’t compelling, no change will occur.

  • Without action, insights are just empty numbers.

  • Insights serve as the compass that translates data into actionable strategies.

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LESSON HIGHLIGHTS:

• In presenting data, it’s more than just informing; it’s communicating.

• Effective communication explains insights in a way that is understood and motivates action.

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LESSON HIGHLIGHTS:

• The Key Steps to Transform Data into Value:
  Data ➜ Information ➜ Insight ➜ Decision ➜ Action ➜ VALUE

• But when you present your insights as data stories, you’re more likely to influence decisions and drive actions that create value:
  Data ➜ Information ➜ Insight ➜ Data Story ➜ Decision ➜ Action ➜ VALUE

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LESSON HIGHLIGHTS:

• The 3 Elements of a Data Story: Data, Story, Visual

  • Story + Data = clarifies what's happening in the data and why an insight is important

  • Visual + Data = capitalizes the insights that wouldn't be seen without charts or graphs

  • Story + Visual = captivates or entertains audience with an insight

• Combined, Data + Story + Visual influences action that results in CHANGE.

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LESSON HIGHLIGHTS:

• Many of us struggle to bring storytelling into our everyday business lives.

  • We load our presentations with bulleted text, and cluttered charts and photos—missing the opportunity to make an impact, influence decisions, and drive your business forward.

• We can change that through storytelling.

  • Storytelling: a powerful way to humanize the communication of information.

  • Data storytelling: uses the same core concepts to better communicate data insights.

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LESSON HIGHLIGHTS:

• Reasons Why Stories are Effective:

  1. Storytelling is the oldest form of teaching in history.

  2. Human brains are hardwired to understand information primarily through stories.

  3. Stories are more persuasive statistics.

  4. Data stories drive action.

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LESSON HIGHLIGHTS:

• Data Storytelling: uses the persuasiveness of storytelling to make complex data understandable to a wider audience

  • Uses data and analytics to deliver a compelling story

  • Strengthened by visuals that emphasize what's important

  • Simple and bias-free

  • Creates a deeper understanding of the insight

  • Inspires action and leading to desired results

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LESSON HIGHLIGHTS:

• Storytelling is necessary when it falls within the Story Space

• Various criteria can influence the approach to Data Storytelling based on the nature of the insight:

  • Within the Story Space: insight is highly valuable, but hard to understand.

    • Hard Insight + Mid-High Value = Data Story is required

  • Outside the Story Space: insight is hard to grasp but low in value, OR easy enough to understand without a data story.

    • Hard Insight + Low Value = Data Story NOT required

    • Easy Insight + Mid-High Value = Data Story NOT required

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LESSON HIGHLIGHTS:

• The 3 Elements of a Data Story (data, story, visual) must not only work together, but also follow the Data Story Sequence: Data ➜ Story ➜Visual

• When Story is not extracted based on Data, and Visual is not designed to tell the Story, you’ll run into different sorts of problems.

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LESSON HIGHLIGHTS:

• Think of your data insight as a rare pearl. Good Data Storytelling ensures that you show your audience the pearl, instead of all the oysters you opened to find it.

• Good Data Storytelling clarifies the message of your data, changes how you communicate your insight to your audience, and inspires them to take action more effectively.

  
  

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LESSON HIGHLIGHTS:

• The 3 C’s of Building Your Data Story are as follows:

  1. Crowd: observing and profiling the audience

  2. Content: components that make-up the data storyline structure

  3. Core: short but powerful thesis statement that captures the data story

     
     

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LESSON HIGHLIGHTS:

• Often there is a gap between you, your data, and your crowd.

• Audience profiling is key to crafting compelling data stories that resonate with your listeners on a deeper level.

• Know your A.U.D.I.E.N.C.E.:

  • A – nalyze: history/background
    U – nderstand: commonalities, expertise, knowledge, temperament
    D – emographics: size, average age, gender profile
    I – nterest: common interests, relevance
    E – nvironment: business environment, culture
    N – eeds: looking for/need from the presentation/need to achieve
    C – ustomization: prejudices or opinions
    E – ngagement: expectations, fears, standards

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LESSON HIGHLIGHTS:

Having decoded the meaning of the AUDIENCE profiling tool and learned how using this can strengthen your data storytelling impact, it's time to revisit our Core Example to see how the concepts are applied!

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LESSON HIGHLIGHTS:

• Anablep: a unique “four-eyed fish” that is able to see both below and above the water surface at the same time—giving it a wider field of vision that helps it detect potential threats or prey from any direction.

• Strive to be “anableptic” with your Audience:

  • Alert and aware of surroundings

  • Observant and perceptive of the situation

  • Mindful of opportunities

  • Non-linear, big picture thinking

    
    

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LESSON HIGHLIGHTS:

• The content is the heart, soul, and plot of your data story.

• Data can be organized as a captivating sequence of events--just like in a story or movie.

• Data S.T.O.R.Y. Line Framework:

  S – ituation: background/context, characters involved
  T – ake-Off: hook/problem, rising action or insights
  O – pportunity: Climax, AHA moment
  R – esolution: solutions, recommendations, call to action
  Y – ield: desired result/outcome

  
  

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LESSON HIGHLIGHTS:

Having explored the Data S.T.O.R.Y. Line Framework and its five stages, we apply this once again to our Core Example to see the framework in action.

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LESSON HIGHLIGHTS:

• The core is the Main Point of your data story

• The Main Point:

  • Thesis statement that summarizes findings

  • Helps audience understand insight at a glance

  • Supports findings represented in the visual

• Key Elements of the Main Point:

  1. Problem: hook/issue

  2. Stakes: outcome if problem is not addressed

  3. Steps: steps to address the problem

  4. Call to Action: appeal to audience for a decision

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LESSON HIGHLIGHTS:

• Visual Economy: today’s data-driven era as defined by the increasingly visual world we live in

• Majority of business leaders believe visuals carry more authority over other forms of communication (Canva’s Visual Economy Report, 2023)

• Visuals play a crucial role in conveying complex information clearly and efficiently

No part of this program may be reproduced without due Permission from Convergent Experience Management Consulting Inc.

LESSON HIGHLIGHTS:

• Visual communication: the most impactful way to communicate—now a business imperative.

• Design Literacy: ability to understand and interpret visual elements and their purpose in communication.

  • This skill is more critical than ever for all employees, including those in non-design roles

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LESSON HIGHLIGHTS:

• Numbers, on their own, can be limited in telling the entire story of your data.

• Data Visualization: presents analytical information in a visual format, making data comprehension easier and more efficient

  1. Captivates your audience

  2. Conveys key points efficiently

  3. Enhances decisions and influences others

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LESSON HIGHLIGHTS:

• The 6 Types Data Stories:

  1. Rankings: arranges numerical/ordinal values by on importance

  2. Distributions: frequency and spread/patterns of different values

  3. Proportions: relative size or share of values in a dataset

  4. Correlations: strength and direction of the variable relationships

  5. Comparisons: contrast different sets of data to identify similarities or differences

  6. Change Over Time: how variables evolve and vary over a specific period of time

  
  

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LESSON HIGHLIGHTS:

• Hans Rosling’s Wealth and Health of Nations:

  • Measures economic prosperity (income per person and life span) of 200 countries over 200 years.

  • Key insight unlocked: After 200 years, majority of countries have become wealthier and healthier!

• Bottomline: Today, the world of is much better off than it used to be--heading toward healthier lifestyles, longer life spans, and higher income.

  
  

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LESSON HIGHLIGHTS:

• Graphical Perception: visual decoding of information encoded on a graph based on visual factors called “perceptual tasks”

  • Position, Length, Slope, Angle, Area, Intensity, Color, Shape

• Perceptual Tasks are arranged based on how efficiently they can get the audience to understand the data

  • Charts that use position and length are easier for the human-eye to interpret vs. charts that use slope and angle.

    
    

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LESSON HIGHLIGHTS:

• Types of Data Visuals (Part 1):

  1. Bar Charts: uses rectangular bars or columns

  2. Line Graph: uses lines to connect data points, showing trends or change

  3. Stacked Bar Chart: stacks bars on top of/beside each other to represent multiple data categories

  4. Pie Chart: circular chart divided into slices representing parts of a whole

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LESSON HIGHLIGHTS:

• Types of Data Visuals (Part 2):
  5. Treemap: display hierarchical data as a set of nested rectangles
  6. Scatterplot: displays individual data points as a cloud of dots to show relationship

  7. Table: organizes and presents data in rows and columns
  8. Text: written or textual information used to highlight key insights

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LESSON HIGHLIGHTS:

After exploring the 6 types of data stories and the different types of visuals, we apply what we learned to our Core Example and see how our graph transforms into a more captivating data story.

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LESSON HIGHLIGHTS:

• Hybrid Title: contemporary approach to titling that encapsulates context, key insights, and actionable takeaways.

  • 3 Components: Insight, Call to Action, and Legend

    
    

• Hybrid Title vs. Main Point: What’s the difference?

  • Hybrid Title: concise main title seen in your data visual

  • Main Point: summarizing conclusion statement that explains the entire insight

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LESSON HIGHLIGHTS:

• Visual Grouping: how our minds naturally organize and group visual elements that share similar characteristics or are located close to each other.

• The 6 Gestalt Principles of Visual Grouping:

  1. Proximity: objects that are physically close to each other

  2. Similarity: objects with same color shape, size, or orientation

  3. Closure: our minds can perceive incomplete shapes or patterns as whole recognizable objects

  4. Continuity: elements forming smooth and continuous lines or curves

  5. Connection: objects that are physically connected

  6. Enclosure: objects that are physically enclosed together

     
     

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LESSON HIGHLIGHTS:

• Pre-Attentive Attributes: visual characteristics that our brains can quickly and automatically perceive without conscious effort (e.g. color, size, orientation, shape, curvature, length, and more)

  • These help users find what they never expected to see, and guide their attention to important information

• Visual Hierarchy: arrangement of elements in a design or layout to create a clear and organized visual structure

  1. Placement of elements from top to bottom

  2. Grouped elements

  3. Distinct use of colors

  4. Varied font sizes and styles

  5. Diverse visual techniques

     
     

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LESSON HIGHLIGHTS:

• Chart Junk: all visual elements in charts and graphs that are not necessary to comprehend the information represented.

  • They distract the viewer from what's important.

  • They waste space or graphics on a visual.

• Data to Ink Ratio: emphasizes the efficient use of ink or pixels in a visual that conveys meaningful data

  • The more of the ink in your visual that is related to conveying the message in the data, the better.

  • Limiting chart junk increases the data to ink ratio.

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LESSON HIGHLIGHTS:

• Design Thinking: a creative and strategic approach to crafting visuals that effectively convey information.

  1. Use clean sans-serif fonts

  2. Use color purposefully

     • Multiple colors only if they provide value

     • Take advantage of the color wheel

     • Tones that are color blind-friendly

  3. Leverage white space

• Design thinking builds a stronger connection between your message and your audience.

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LESSON HIGHLIGHTS:

• With a better understanding of visual grouping, pre-attentive properties, chart junk, and design thinking, you can design data visuals that drive results.

• In this last lesson, you’ll see how skillfully designed data stories can make basic visuals brilliant.

  
  

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