Data Storytelling

Track: Enterprise Data Practitioner (EDP)
Data Storytelling is suited towards any professionals that work with data and charts. If you need to tell better stories with your data, then this course is for you. The curriculum challenges participants to communicate effective and impactful data-driven narratives, focusing on principles of effective data storytelling.

Effectively communicate insights from Data

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Participants will learn to meaningfully articulate findings through both narrative and visual strategies. This module will enable participants to drive change through effective communication of Data insights.

Learning outcome:

Upon completion, participants should be able to demonstrate each of the following;
  1. Make stories that highlight value from data-driven insights
  2. Design intuitive visuals that are easy for the audience to interpret
  3. Present findings through stories

Who should attend:

Professionals that work with Data

2 days of in depth learning

Face to face with experienced Data Scientist.

Course Methodology

This course will utilize a combination of Lectures, Presentations & Workshops.

CADS Certification​

Earn certification upon completion.

Minimum Qualification:
Undergraduate Degree

Training Track

Enterprise Data Practitioner (EDP)

Data Storytelling is one of the modules under our Enterprise Data Practitioner (EDP) programme. EDP is a nine-day training program that super-charges Business Intelligence analysts with new skills to analyse and communicate insights effectively.

Details of Subject

Day 1
  1. Why Data Storytelling –  Data is ubiquitous. Many organizations have spent a fortune on developing talent capable of competent data analysis but not many have equipped their workforce with the ability to communicate the insight they generate effectively to decision-makers. Unlock insights trapped with your analysts through lessons in Data Storytelling.
  2. Explore or Explain –  There are two reasons we perform Data Visualization. Data exploration is the first step for many data analysts and is a skill that has been religiously cultivated in response to the rise of Big Data. Explanatory Visuals are used to convey the outcome of an analysis to the audience and is thus the focus for this course.
  3. Who, What, How –  The first step to crafting a Data Story is to consider three key questions. Who is your audience? What do you want to tell them? How can you bring this story to life with your data.
  4. Insights & The Big Idea –  Putting together the ‘Who, What, How’ enables us to form the ‘Big Idea’. This ‘Big Idea’ serves as a guide to ensure we have a consistent narrative in our visuals.
  5. Storyboarding –  Stories help us make sense of information in a clear and structured way. This section will illustrate the different ways we can organize a story such as through the Three Act Structure, or from a Toe-to-Head approach.
  6. Graphical Integrity –  Misleading visuals are everywhere. We see them in newspapers, annual reports, news channels to name a few. Protect yourself from misinformation (or from spreading it) by learning about Graphical Integrity.
  7. Activity: Part 1 –  Put your newfound skills together to create and organize a story from scratch.
  8. Graphical Perception –  The human eye has evolved to distinguish certain graphical cues better than others. Hack into the human brain and design visuals that are accessible to your audience.
Day 2
  1. Choosing a Visual –  Bar Graphs, Tree Maps, Pie Charts, Slope Graphs – the list of charts we can use never ends. Learn about common pitfalls for popular chart types to avoid making them yourselves. We will also talk about the ‘best’ charts to use when trying to convey certain types of information.
  2. Gestalt Principles of Visual Grouping –  There are six Gestalt Principles of Visual Grouping that help us as humans make sense of visual information we pick up. Design intuitive visuals by applying these concepts to your charts.
  3. Visual Hierarchy –  Design a hierarchy of information on your visual by leveraging concepts such as pre-attentive attributes, multi- functional chart elements and supporting chart elements.
  4. Chart Junk –  Data is boring. This is a (mistaken) design philosophy that many people have when they approach data visualisation. Maximise your data-to-ink ratio to create visuals where form follows function, and not the other way around.
  5. Dissecting Model Visuals & Chart Redesign –  The best way to learn Data Storytelling is to dissect what makes model visuals great. We can also learn by trying to improve poor visuals that fail to adhere to our Data Storytelling lessons.
  6. Design Thinking –  Fonts, formats and colours are key elements to any visual. Leverage colour with purpose to create stunning visuals that minimize cognitive load.
  7. Activity: Part 2 –  Work in teams to design your own presentation using all the concepts covered in the two days of Data Storytelling. Present your findings to discuss concepts covered.

Lead Instructor

Darren Chong
Darren is an MSc. Management graduate with Distinction from Warwick Business School transitioning into Data Science from the world of business. His prior work experience spans a broad range of industries including management consulting, education and public relations. At the Center of Applied Data Science, Darren helps organizations unlock latent value hidden in their data by generating and communicating actionable insights to decision-makers. As a trainer, Darren uses his business management background to provide business context to theoretical concepts covered in class. He provides training in Functional Programming and Machine Learning but mainly specializes in Data Visualization & Storytelling.

CADS Certification

EDP CADS Certified Data Vizualization & Storytelling

This exam certifies job-ready knowledge and skill. Those that pass are recognized as being able to distill an insight from data and communicate its value to a decision maker. Enter the world of Data Professionals.

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Data Storytelling