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Narrative Science transforms data into stories and insight. It has developed a configurable horizontal platform that takes in data from various domains like media, big data, social media and structures it into facts, angles, and stories. The process involves both engineers and writers to derive meaningful insights from data and present them in an engaging narrative form. The company aims to bridge the gap between raw data and human understanding by automatically generating stories from structured and unstructured data sources.
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- 1. Kristian J. Hammond Narrative Science 1
- 2. We Transform Data into Stories and Insight Transforming Data into Stories
- 3. Data and Domains • Media (sports, finance, real estate) • Big Data (performance, client services, education) • Social Media(politics, companies, products) Transforming Data into Stories
- 4. February 9, 2012, Hockey Recap: Rio Grande Valley rolls over Laredo, 6-3 The Rio Grande Valley Killer Bees were firing on all cylinders against the Laredo Bucks, and when the final buzzer sounded Killer Bees emerged with a 6-3 win. Zac Pearson was all over the ice for Rio Grande Valley, as he tallied two goals and one assist in the win. Pearson scored the first of his two goals at 5:23 into the first period to make the score 1-0 Rio Grande Valley. Brandon Campos picked up the assist. Pearson's next tally made the score 2-0 Rio Grande Valley with 12:44 left in the first period. David Marshall assisted on the tally. The punch line… Special teams units factored heavily in the game's outcome, as there were 14 penalties called on the two teams. The busiest period in the sin bins was the first period, which saw 18 minutes of penalty time combined between the two teams. The Killer Bees' goal total was higher than their season average. Rio Grande Valley averages two goals per game. The Killer Bees could not stay out of the penalty box, as the team accrued 17 minutes in penalties during the game. The leading offender was Jason Beeman, who totaled five minutes in penalty time with one major. With 48 shots on target during the contest, Rio Grande Valley exceeded the 22 shots it averages per game this year. Rio Grande Valley additionally got points from Aaron Lee, who had one goal and one assist, Marshall, who registered one goal and two assists, and Dan Gendur, who racked up one goal and one assist. Dan Nicholls also scored for Rio Grande Valley. Others to record assists for Rio Grande Valley were AJ Mikkelsen, who had two and Adam Bartholomay and Marc-Andre Carre, who each chipped in one. Transformingin penalty trouble, as it ended withnine minors and penalty time with two minorspenalty time. Laredo was often Data Justin Styffe, who totaled six minutes in one major for 17 minutes in and one The leading offender was into Stories
- 5. How does it work? The Data The Facts The Angles The Structure Stats Tests Calls T/F Language Transforming Data into Stories
- 6. Start with sports Finance Transforming Data into Stories
- 7. Start with sports Real Estate Transforming Data into Stories
- 8. Configurable horizontal platform The Data The Facts The Angles The Structure For each new content type we ask: Stats Tests Calls T/F – What is the data? – What facts can be derived from the data? – What are the angles? – How is the story structured? – Finally, how do we say it? Language Transforming Data into Stories
- 9. A partnership between engineering and editorial Transforming Data into Stories
- 10. From the engineer’s perspective Transforming Data into Stories
- 11. From the writer’s perspective Transforming Data into Stories
- 12. The Outline Transforming Data into Stories
- 13. The Data Transforming Data into Stories
- 14. The Derivations Transforming Data into Stories
- 15. The Angles Transforming Data into Stories
- 16. The Structure Transforming Data into Stories
- 17. Transforming Data into Stories
- 18. Big Data Transforming Data into Stories
- 19. The Notebook Transforming Data into Stories
- 20. “I don’t need a shelf full of folders… I just need a two paragraph summary of the stuff that is important for me.” Transforming Data into Stories
- 21. In story form… “We collect everything on how each account is performing. But we only have the people to explain it to our ten biggest customers.” “You don’t get the game from the stats. You get the game from the story they tell.” “If we could spend a half hour each week with each of our students and their results, we could improve all of their grades.” Transforming Data into Stories 21
- 22. Performance reporting Transforming Data into Stories
- 23. Transforming Data into Stories
- 24. Education Transforming Data into Stories
- 25. Transforming Data into Stories
- 26. The story is the last mile in understanding Big Data Transforming Data into Stories
- 27. Real Estate Pharma Sales Politics Finance Sports Transforming Data into Stories
- 28. Wherever there is data, we can tell the story Transforming Data into Stories
- 29. What about the unstructured world? Transforming Data into Stories
- 30. We track it and tag it Transforming Data into Stories
- 31. We structure it Transforming Data into Stories
- 32. And use it to write stories Transforming Data into Stories
- 33. We Transform Data into Stories are the bridge between numbers and knowing. Stories and Insight Transforming Data into Stories
- 34. Kristian J. Hammond Narrative Science @whisperspace 34
Editor's Notes
- McD’s: world’s largest chain of fast food restaurants
- McD’s: world’s largest chain of fast food restaurants
- McD’s: world’s largest chain of fast food restaurants
- McD’s: world’s largest chain of fast food restaurants