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When Presenting data, make sure you are completely unbiased in your opinion. A clear mind is absolutely needed when you start mining your data. If you are pre-occupied with a notion of what your data may (or should) reveal, it is likely that you manipulate the data to suit that.
Whether you choose to use Average or Mode of a distribution to demonstrate your finding could have a significant impact on the way information is grasped by your audience.
Remember, “Data will confess to anything, if you torture them enough”
Be clear about your use of colours, axes and trend lines
The Colours have meanings. If you highlight your data series in “Red”, it calls for attention.
Same data on a linear scale and logarithmic scale look entirely different, and can give a wrong meaning to the unsuspecting end user.
Whether you draw a linear trend line or a polynomial trend line changes the way someone perceives information.
COVID-19 Total cases (Global) Linear Scale vs Logarithmic Scale – Image Creditshttps://www.worldometers.info/coronavirus/coronavirus-cases/
Be Savvy with Domain Knowledge
Clarity about the domain you analyse is absolutely crucial, whether you just visualize your data, or move into more advanced analytical functions like Machine-Learning.
It is absolutely necessary understanding how the data points in your specific domain behave, the constraints it has, and what kind of relationship they have with each other.
In my caption image, the data analyst seem pretty skilled in his technical domain, but lacks the simple understanding that a woman stops thinking about another husband (at least within a dozen week) once she gets one! (Too much work already!)