Big Data Day LA 2016/ Data Science Track - Data Storytelling for Impact - Dave Goodsmith, Data Scientist, Datascience Inc.

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How can our data make the biggest impact? How do we find the stories worth sharing buried in our analytics? How important are visuals, hooks, connections, content? As data science and journalism have co-evolved, the potential for effectively communicating with data has skyrocketed. We'll look at case studies of impactful data stories and share the process for developing data stories that drive action.

Technologie

Data Storytelling for Impact
A Case-Study Approach to Best Practices for
Successful Data-Driven Communication

Outline
● Why Data Storytelling?
● The Framework
● Examples
● Your Data Stories

Anatomy of a Successful Data Story
● Origination
● Data Diving
● Story Weaving
● Impact

Origination
● Ideation: Where did the idea come from? When was the
'aha' moment for the project?
● Resolve: When, and how, did the decision get made to
move forward with the project?
● Target Impact: What was the ultimate public or
organizational impact, or impacts, that the project intended
to make?

Data Diving
● Data Collection: What was the source of the data? How
was the data collected? What unexpected challenges or
opportunities arose during the data collection process?
● Data Analysis: How was the data analyzed? Who did the
analysis?

Story Weaving
● Narrative: How were insights drawn from the data? How
was the narrative crafted? What were the narrative goals?
● Design: Is the data portrayed visually? Narratively? Both?
What were the formats of the end product, and why?
● Press: How was the story communicated to the press?
Unintentionally? Methodically?

Impact
● Launch: How was the story ultimately launched?
● Response: What was the impact of the story?

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