6 points to help navigate the world and daily technical practices to become better data communicators. So, here are six points that I think are valuable and some resources I have used when considering presenting my projects.
Reflecting back on the various roles I have had in a Data Science team, it has occurred to me that I am one of the few people who is often asked to present.
From a whole host of meeting invites, to slides in various Teams channels and countless versions of presentations on my laptop, I realised that I had presented more than 120 versions of 18 projects over the last six years — that’s roughly one presentation every three weeks! Through this, I can safely say that I have sat through and given presentations that did not land well with various audiences.
One would argue that this many presentations were unnecessary for technically apt stakeholders in a data literate organisation, but these individuals are few and far between where I work.
Many of my presentations have been time-consuming and cumbersome to prepare, but they have been invaluable in my attempt to become a better Data Science communicator. Regardless, I am thankful of my introspective moments which have led to confidence in my content and communication skills.
To date, being a keynote speaker and attending a panel at Financial Times Energy Summit on ML in the energy industry has been a highlight. Whilst I have so much more to learn, I now know that I can drive an engaging conversation with those who are listening.
So, here are six points that I think are valuable and some resources I have used when considering presenting my projects.
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How to use graphs effectively while working on Analytical problems. Data visualization is the process of creating interactive visuals to understand trends, variations, and derive meaningful insights from the data. Data visualization is used mainly for data checking and cleaning, exploration and discovery, and communicating results to business stakeholders.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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