How to do Data Storytelling?

Data storytelling is one of the most important soft skills that any data scientist should have. It means presenting the story behind the numbers generated by a business so that we can conclude the future course of action. If you want to learn how to tell stories as a Data Scientist, this article is for you. In this article, I’ll walk you through how to do Data Storytelling step by step.

What is Data Storytelling?

Data storytelling is a non-technical skill that every data scientist should have, just like communication. Simply put, this means presenting the story behind the numbers in a dataset in the form of data visualizations and presentations. Suppose you are a Data Scientist and your business has a small budget, so managers don’t know what steps they need to take to get their new product to market. As a data scientist, you need to find the most profitable customers for the new product so that the amount you spend on marketing the product is easily recouped if the product is only marketed among the most profitable customers.

Presenting this kind of strategy in the form of data visualizations and presentations is nothing but data storytelling. The only idea is to find out the story behind the numbers generated by a business so that the conclusion you draw about future decision making looks like the need of the hour.

How to do Data Storytelling?

Hope you now understand what Data Storytelling is. Below are the steps to follow when creating data visualizations and presentations for data storytelling.

  1. Problem Statement: As a data scientist, you must know the problem statement very well. Just like that, all the professionals who are in the meeting should also be clear about the problem for which you have proposed a solution. The first step is therefore to explain the problem.
  2. Explain About The Data: The next step is to explain your data. Here you need to focus on the features of the dataset that everyone needs to focus on. You should also explain the most important features that say the most about the performance of your business.
  3. Explain Insights that you found: This is the most important step in data storytelling. Here you have to tell the story behind the numbers so that everyone understands the context based on which you have defined a solution to the problem.
  4. Present a Solution: So far, all you’ve done is just present a solution so that everyone can understand why you are choosing your solution. Your solution should look like a recommendation, not a decision, because after making many recommendations, you may find more suggestions based on your data storytelling.

Summary

So this is how you can practice the art of telling stories as a data scientist. It means finding out the story behind the numbers generated by a business so that you can present a solution based on the problem. Hope you liked this article on how to do data storytelling in data science. Please feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
Articles: 1132

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