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Why Data Storytelling is
Essential in the Age of Big Data
David Stack 
1. Stories make data meaningful
Stories bridge the gap
between data science,
analytics, and your audience.
Whether that audience includes
consumers, potential partners
or investors, a narrative
takeaway is essential to convey
how your product or service will
solve a particular need. 
Stories tell to sell
The goal of analytics is often to change
how someone makes a decision or takes
an action. A story can convey how to get
from point A to B more clearly than raw
data can—think of it like giving someone a
map instead of just a set of coordinates.
By showing the destination and how to get
there, you are able provide a bridge
between raw data and the users who
stand to benefit from it. 
While raw data can be complex and hard to process, putting it
in the context of a story boils it down to simple, memorable
truths. Data analytics can be too complex for the average
audience to digest. Instead, frame those figures in an
engaging narrative, and the message will be received loud and
clear.
Negotiation & Closing
Stories crystalize
takeaways
Investors are not necessarily
interested in complex data analysis,
but rather in the takeaways that
speak to a company’s future health.
Similarly, consumers don’t care
about the back end analytics behind
your app; they are interested in how
your service can improve their own
life in a real and meaningful way.
Use data storytelling to put into
context the problem that your
product solves.
Visit http://david-
stack.com/ for more
information 

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Why Data Storytelling is Essential in the Age of Big Data

  • 1. Why Data Storytelling is Essential in the Age of Big Data David Stack 
  • 2. 1. Stories make data meaningful Stories bridge the gap between data science, analytics, and your audience. Whether that audience includes consumers, potential partners or investors, a narrative takeaway is essential to convey how your product or service will solve a particular need. 
  • 3. Stories tell to sell The goal of analytics is often to change how someone makes a decision or takes an action. A story can convey how to get from point A to B more clearly than raw data can—think of it like giving someone a map instead of just a set of coordinates. By showing the destination and how to get there, you are able provide a bridge between raw data and the users who stand to benefit from it. 
  • 4. While raw data can be complex and hard to process, putting it in the context of a story boils it down to simple, memorable truths. Data analytics can be too complex for the average audience to digest. Instead, frame those figures in an engaging narrative, and the message will be received loud and clear. Negotiation & Closing
  • 5. Stories crystalize takeaways Investors are not necessarily interested in complex data analysis, but rather in the takeaways that speak to a company’s future health. Similarly, consumers don’t care about the back end analytics behind your app; they are interested in how your service can improve their own life in a real and meaningful way. Use data storytelling to put into context the problem that your product solves.