22 Jun Why Storytelling in Data Analysis is Important

Storytelling with data is one of the effective skills a Data Scientist or Data Analyst must possess. This is simply the act of communicating insights and patterns in data using the data combination, visual or narrative form. Whenever Data Scientist works with a data, his ability to produce high-quality story is crucial. While not just that, forming opinions and arguments about the data is also essential in making key business decisions.

Now, let’s discuss why this is a must-have skill for everyone.

Why Storytelling with Data is Important

With the amount of data available to us, only data storytelling can give human knowledge what the data connotes and some form of coherence. With a compelling story behind the data, we can engage people’s emotions and intellects by creating a deeper understanding of what they need to know.

A good example we can relate to is a weather forecaster who provides weather reports. He also issues advanced warnings for potentially severe weathers and hurricanes. Without him providing the viewers an interactive graphics or visuals, there is no way many could have understood his report. It would mean that storytelling on his part was inadequate.

These and many numerous reasons are why many organizations put a lot of efforts into data visualization and storytelling because it prevents them from making bad decisions in business. Also, on the part of the Data Scientist, lack of Storytelling reduces the quality of his work which makes decision making a guessing game.

Let’s move further and discuss how exactly we can carry out an effective Storytelling for our Data.

How to Do Effective Data Storytelling

Understand your Audience

The major key thing to always consider is the audience we are working with. We must know what they want and the goal/target that needs to be reached. This is also telling us that the inference generated in a data or let’s say a visualization Dashboard communicates well-detailed information to the audience whereby they understand what the content is and also meet up with their business demand.

Make Sure your Story is Concise and Transparent

When working with your data, you must have a deeper understanding of what you want to do, having that, communicating your result will be much easier. This result must be concise which means you have a well detailed information in few words. The result also has to be transparent enough for the Audience whereby giving them clear necessary details they need.

Understand the Whys

When communicating your result to the audience, you must understand the whys; this means you must be able to explain factors responsible for market rising and falling in your data. You can also make this interactive by producing numbers in your data which will make your findings solid.

Ensure your Story is Clear

When presenting to your audience, you also need to be very clear. You should be able to express yourself in a layman’s language which isn’t too technical for them to understand. You also need to be well engaging so that the information you are giving to them can be memorable.

Ensure your Story has a Significant Context

The context we mentioned here is a very key point all Data Scientist must not do without. Working with context is what builds value from insights generated. This means the result generated provides a sense of clarity and every essential information required.

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