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If you’re looking into becoming a data scientist, or are already a data scientist - you will have had a read or know the skills required. You will need a programming language, an understanding of mathematical statistics, the ability to create data visualizations, and more. 

If you’re looking into becoming a data science professional and need some guidance, have a look at this article: Become a Data Science Professional in Five Steps.

Although the majority of your time will be spent during the data preparation stage trying to find and clean data - there are other important elements to data science. 

Once you have found your valuable insights, if it’s trends, patterns, or put into visualizations - you will need to be able to explain these. As a data professional, it can be difficult for non-technical people to understand technical language. 

If you are a technical person, it can be challenging to convey your message to non-technical people. Not only will you come across non-technical people, but you may be dealing with someone who prefers explanations through visualizations, or project run-throughs. 

Therefore, once you have your findings, you will need to cater to a variety of people - and mastering how to do that can be difficult, but it can be achieved. 

Let’s get started…

Non-technical Language

As a data scientist myself, I understand that a lot of stakeholders or managers will not come from a technical background. Therefore, some of the terminology used in your everyday team will be foreign to them. For example, F1 score or cross-validation. 

Think about how a teacher explains a topic to a student, and keep that at the front of your mind when you’re explaining to your audience. Translate your data science terminology in a language that everybody can understand. If there is no way you can replace a specific data science term, there is no harm in explaining what it means. You will do more harm by losing your audience's attention to technical words. 

Data Visualizations

Different people learn in different ways. Some can read a textbook once and get it. Some need it to be color coded. Some need visualizations. When presenting your findings, don’t limit yourself and put yourself in a rut where you have to answer 1000 questions. Visualizations can answer questions for you. 

Data visualizations will allow your audience to have a visual understanding of the steps you took and your findings. Whilst you are talking in the background about the visualizations, their eyes are learning and making sense of what you are saying. 

Summary

At the end fo your presentation, ensure to have a summary page of all your important points and data visualizations for your audience to see. During this time, you should be open to questions in which your audience can continuously look at the summary board to sprak new questions. 

Your audience asking questions is not a bad thing, it shows that they have been listening, they are interested, and they want to learn and understand more. 

Three-act Storytelling

The above points are elements of your storytelling which will make it effective. However, a structure is what will make your data storytelling a success. 

The three-act storytelling is a popular model used in narrative fiction that divides a story into three parts:

Setup

Aim: state in the clearest terms the problem you are trying to solve.

This includes an introduction to your project, stating the purpose of the project, what you're trying to solve, etc. During the setup, from a data science perspective you will go further into the problem or issue in more depth to give context to the aim of the project. The aim of your project will equate to your Point 1. 

Confrontation

Aim: explain to your audience why it’s important to solve this problem and the different paths you went down to solve the problem. 

During the confrontation part, you can continue speaking about the task at hand, and why the company was facing this issue in the first place. You want to keep your audience interested and intrigued, therefore speaking on the problems that the company is facing will always get stakeholders hooked. 

Explain to your reader step-by-step the different paths you went through and your outcome for each, in order to complete the task at hand. The different steps you took during the data science project will reflect different points, e.g. Point 2, Point 3,…

Giving your audience context to the failures and obstacles you encountered and why, will help build trust and understanding between you and the audience once you come to a resolution. 

Resolution

Aim: Explain the solution you can offer to solve the problem and ensure the audience are satisfied. 

This is where the audience goes from being concerned to relieved. Your resolution should state how it overcomes your previous failures and obstacles. Open this section up for questions, as your audience will want to have full trust in your data insights and believe this is the right way to go. 

Once the audience is at ease, you can start wrapping up and speaking on the actions that need to be taken, in order for the task to be a success. 

The Pyramid Principle

Another structure that is very effective is the pyramid principle. This is an effective communication tool used to clearly communicate complex issues to busy executives. The aim is that ideas in writing should always form a pyramid under a single thought.

So let me explain this a bit more. When dealing with busy executives that want to learn about your data insights, but are short on time or are eager to know the solutions - the pyramid principle is the way to go. 

It is broken up into 3 parts:

Your Answer

In this case, your answer will be the solution to the task at hand. This is the main point you want your audience to take away. This is the key message and you want the focus to be surrounded around this main point - the solution. 

Supporting Arguments

Once you have stated the solution, your next step is to convince your audience that this is the way to go. In order to do this, you will have to take them through a journey of supporting arguments, with high level insight. During this part, your audience may have a few questions lingering in their mind.

Supporting Facts/Data

During this part, all of the possible questions that your audience may have will be answered here. Each of your supporting arguments needs to be backed up by data and facts to ensure your audience that you have done your homework and that your initial answer/solution did not come out of thin air.

Wrapping it up

Using the skills of using non-technical language and visualizations in either structure: three-act storytelling or the pyramid principle will allow you to master the art of data storytelling. 

Your choice on which structure you choose is dependent on how well you know your audience. You can always trial and error both structures to see which one is most effective. A good way to measure how effective the structure is for your audience is by noting which structure had less questions. The less questions your audience has, the more successful your storytelling was.
 
 
Nisha Arya is a Data Scientist, Freelance Technical Writer and Community Manager at KDnuggets. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.