
Explore the fundamentals of data storytelling and the role of data visualization. Explore case studies to learn how to extract data and place it in proper context.
Develop the ability to drive data presentations by introducing data, setting up your session, and delivering the key message for industry audiences.
Data storytelling combines reliable data with a compelling narrative tailored to the audience, using data visualization to illuminate insights and drive action.
Set the context for data storytelling by defining the audience, what details they need, and how data acts as evidence to support a narrative.
Use a low-tech storyboard with whiteboard, post-it notes, or plain paper to outline your data story, revise ideas, and map the big idea to audience needs before crafting slides.
Gain a deeper understanding of storytelling, recognize that the story is more than data visuals, and apply assets, context, and a clear message to craft your data narrative.
Explore the second section of data storytelling, where visualization highlights key data points. Identify core components, choose the right graph, and practice fundamental bar charts before more creative visuals.
Learn how to translate raw data into meaningful charts and graphs by focusing on four components: labels, data encoding, spatial layout, and categorization skills to let the data speak clearly.
Create chart titles that reveal the subject and convey the data-driven message; use visual cues mapping data to geometry within a layout system so viewers map back to the data.
Use position as a visual cue in scatterplots to compare two numerical variables using x and y coordinates, revealing trends, clusters, and outliers.
Learn how line plots show time-based data, connecting points along the y-axis to the x-axis, and compare categories A–D while noting changes with axis scaling and min, max, and average.
Learn to use bar charts for categorical data, with a zero baseline, multiple data series, and horizontal or vertical layouts to highlight changes while avoiding overload.
Learn how pie charts use area to represent value and show the breakdown of a whole, and recognize when pie charts are used or misused.
Explore how to choose the right data visualization for your data, from bar and histogram charts to bubble charts, scatter plots, and line charts, guided by relationships, time, and distribution.
Learn practical visualization tips to communicate data clearly by prioritizing infographics over dense tables, using numbers directly, avoiding pie charts, and using readable bar charts with proper baselines.
Recognize when to use specific chart types for Asia’s big cities, and apply feedback that suits each visualization, while outlining good practices and avoiding common pitfalls.
Highlight guidelines and principles for clean, appealing wine charts, avoid unnecessary heaviness, discuss perceptions, and show how to create concise, effective data storytelling visuals.
Demonstrates how to improve data visualizations by maximizing the data-to-ink ratio, removing clutter, and simplifying charts, using examples like bar charts of calories to show clear, interpretable visuals.
Identify clutter as any item that adds no informative value and reduce cognitive load by creating purposeful visuals for data storytelling, avoiding disorganized layout, weak contrasts, and excessive white space.
Explore common visual clutter and learn how alignment, white space, and clear contrast create readable, focused data visualizations.
Gestalt's principles of visual perception help reduce visual clutter in data visuals by organizing elements into wholes using figure-ground, proximity, similarity, closure, continuity, and order.
Explore how similarity, proximity, and subtle enclosure group visuals by shape, size, orientation, spacing, and text, and learn to guide viewer attention with minimal bordering.
Explore the closure principle in data visualization, showing how borders and simplicity keep data cohesive. Apply continuity and connection to guide viewers' eyes and reveal trends.
Explore design concepts to elevate enhancements in your data storytelling, identify attributes, and create charts that are easy to use and appealing to a diverse set of fonts.
Explore how design concepts for enhancement balance function and form, emphasize accessibility, information hierarchy, and affordances to make data charts clear and easy to use.
Explore how pre-attentive processing guides attention to the one element that differs within a group, and learn how to encode information using attributes like slide length, spatial position, and intensity.
Master how position, color, and size guide viewer attention to key data in visualizations. Apply intentional placement, strategic color choices, and proportional sizing to highlight insights and avoid misinterpretation.
Eliminate distractions to maximize affordances in data visuals by removing non-critical data and using a clean line graph to highlight the bachelor's degree as the main focus.
Explore how to design accessible data visualizations that are simple, well labeled, and annotated for diverse audiences. Learn strategies to clarify graphs, reduce bias, and improve interpretability.
Explore how visualization aesthetics improve data storytelling through intentional decisions on alignment, white space, color highlighting, and cohesive layout to reduce clutter and clarify key signals.
Understand how to use the right kind of chart and track, and apply concept guidelines to create a good story that resonates.
Reintroduce the foundations of a data storytelling narrative and storyboard online content for the site, and learn how ethos, honesty, art, and film shape your story.
Craft a compelling story arc by outlining a clear beginning, rising tension, and a resolution with action or hope, highlighting characters, dilemmas, and audience motivation.
Create a compelling narrative structure and flow for data storytelling by outlining a problem, gathering data, and presenting a solution with executive summary and vertical and horizontal logic.
Conclude the course by using data storytelling to simplify and structure information, turning insights into a clear, compelling narrative that communicates key points effectively.
The unprecedented evolution and progress of technology in the recent past decades has led to the ease of capture and surge of storage capacity for data for everyone. With the saying that ‘data is the new oil’, we have witnessed organizations undergo transformation in their business models, new companies built on data platforms and the rise of various data products that has become part and parcel of our everyday life.
In light of all these head spinning developments there is one truth that needs to be remembered: data captured and stored but not processed is wasteful and useless. All the developments mentioned above became possible because data was made sense of- that is it was turned to information upon which insights were generated which were in turn used to drive better business-decision making, improve business operations or to craft new business strategies.
This course focuses on fundamental concepts and best practices for effective communication with data- something that sits between the crosshairs of science and art. It seeks to enable you to tell the story of your data and not just merely to show data. It is primarily designed for beginners in the field of business analytics or data science who quickly wants to learn how to effectively and efficiently communicate the insights they have discovered from a data exploratory analysis and be able to significantly contribute to the improvement or transformation of their respective organization.
The course is deliberately designed to be succinct and straight forward as it seeks to develop your data storytelling skill in the quickest way possible and get you up to speed. Thus, it is unencumbered and agnostic of any visualization platform or software. Though know how of a certain platform or software will be a big help in doing some of the exercises and case study, it is unnecessary for this course. If you are not familiar with a platform or software, you can revert to the traditional way of pen and paper. This is not to say visualization platform or software are unimportant. In fact, know how on it will greatly help with completing your data story presentation and becomes more critical as you deal with increasing volumes and size of data and in finishing your story presentation in a shorter time. What is vital to begin with however is that you learn the key principles of data storytelling. Learning a certain visualization software or platform can subsequently follow because being an expert of one does not automatically make you a good data communicator or storyteller. Technology does not know the story of your data, it is your job as the communicator and analyst to bring it out contextually and show it visually. This course intends to familiarize you the process to do so.
To achieve the goals mentioned, this course is composed of several lectures, in non-technical language, laced with actual examples so that the concepts can be easily understood and grasped. It is also interspersed with case study practices and exercises. The design is as such because we believe in the learning by doing educational approach and philosophy.