How To Create A Successful Data Presentation | by Rashi Desai | Mar, 2024


Present your data like a pro in six easy steps…

Photo by Teemu Paananen on Unsplash

In the rapidly expanding technological world of today, when data is the cornerstone of every conversation, including business decision-making, data professionals must know how to best present the data they work with.

I met a fellow data professional over coffee the other day and coincidentally, we both were making decks for executives and in one breath we said “Making data presentations for an executive audience is so different”. The way we present our data and insights differs so much per the audience. From an extremely high-level overview to raising the smallest of a potential red flag, the same data can be narrated in so many different ways, the mere art of adapting when storytelling with data motivated me to write this blog.

Everyone knows how to use PowerPoint, Prezi, Canva, Visme, and other such tools to create compelling presentations but what matters the most is the way that the data is presented!

People understand stories better than raw data

Knowing how to develop and deliver a data-driven presentation is a quintessential skill for data professionals today. Data alone cannot hold a great presentation. Storytelling with data is a highly valued skill in the workforce today and translating data and insights for a non-technical audience is rare to see than it is expected.

Here’s my five-step routine to make and deliver your data presentation right where it is intended —

Data slides aren’t really about data; they’re about the meaning of that data.

As data professionals, everyone approaches data differently. Some like to look through the entire dataset before mentally visualizing whereas some like to wireframe the solution first and then manipulate and structure the data to meet the visual picture. Regardless of the approach, it is quintessential that the data is understood, thoroughly.

Before creating a story, I like to lay out the business context and understand the nuances within the data. That helps me make assumptions or create hypotheses…



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