Data Storytelling - Art to Science

The storytelling toolkit for corporate data analytics

What you'll learn
Application of story telling to the corporate world
Best practices to tailor your story as per different learning styles, audience and message
Visual Encoding :: The language of visualization and hence applying the learnings to selection of optimal chart types
3 golden ways to create drama and hence increase stickiness of our stakeholders
Case study implementation on data story telling

Requirements
None for theory, Basic Microsoft Excel for implementation
Description
"Data science is as much an art as science".

This masterclass delves into converting the art of data storytelling into scientific chunks that are easy to implement, keeping in mind the corporate audience.

The intended audiences include Analytics leaders, business and data professionals as well as students.

It will help understand best practices to tailor your story as per different learning styles, audience and message.

There is focus on using multiple touchpoints to drive the message home. The focus will be on processes rather than visualization tool, since the hidden 80% of the ice-berg of any story is understanding the 3Cs - the characters, the context and the conflict/challenge!

There is no doubt that better storytelling is the need of the hour. It is interesting how an HBR article on 'A Data Scientist’s Real Job: Storytelling' and Forbes on 'Data Storytelling: The Essential Data Science Skill Everyone Needs' only strengthen the argument.

This masterclass would also be delving into visual encoding - the language of visualization and applying the learnings to selection of optimal chart types.
Finally this session will help develop the 3 golden ways to create drama and hence increase stickiness of our stakeholders.

The methodology comprises learning through case studies, stories, and concepts. The masterclass ends with implementation of a dashboard for a marketing case study.

Who this course is for
Analytics leaders
Business professionals
Data professionals
Students

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