1 of 3 : Data Storytelling : Obvious to All Analysis
Anjali Sharma
Director of Narrative
Published Date
November 20, 2020
If you have not read the introduction to this blog series, we recommend you read it here .
This blog is a part of 3 part blog series where we have learnt a sequence of analysis method used by radiologists and using that knowledge created a sequence of analysis method for data analysts.
In this blog post we cover how best to data story-tell when we our analysis is obvious to all.
Obvious to All Analysis
Minimal things to consider like in a simple fracture of the finger. Only 1 or 2 abnormal findings. Obvious to everyone its a fracture and a radiologist can be definite about diagnosis. Reported in either of the ways below depending on the situation.
Simple fracture after fall
Fracture after fall but underlying bone abnormality made the fracture more likely worse. Need to address the fracture and the underlying bone abnormality. Needs further analysis
Minimal things to consider like sales increase in a particular month. You can be definite about the analysis
Increase in sales due to promotions
Increase in sales due to promotion but a particular item like summer floral dresses contributed to 75% of the revenue generated. Need to address the increase in sales and interrogate why the dress sold more. Needs further analysis.
In this case it is important to note that as a data analyst you can present with the information you have on hand and establish the need for further analysis. The responsibility can be either given back to the sales division to find out or be brought up as a discussion point in the meeting to find out why the dress sold more or at-least come up with some hypothesis for further investigation.
It is worth remembering that you can be presentation ready without actually finding out what caused the floral dress sales to increase.
As a data analyst, it is not your sole responsibility to find out everything but it is your responsibility to point in the right direction and trigger further analysis to generate insights that can draw better business outcomes. In absence of the actual finding, directional data storytelling is very valuable.
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