Kristian J. HammondNarrative Science               1
We Transform Data into                   Stories and InsightTransforming Data into Stories
Data and Domains   • Media (sports, finance, real estate)   • Big Data (performance, client services, education)   • Socia...
February 9, 2012, Hockey Recap:Rio Grande Valley rolls over Laredo, 6-3The Rio Grande Valley Killer Bees were firing on al...
How does it work?    The Data             The Facts           The Angles            The Structure               Stats     ...
Start with sports                            FinanceTransforming Data into Stories
Start with sports                           Real EstateTransforming Data into Stories
Configurable horizontal platform    The Data             The Facts   The Angles     The Structure    For each new content ...
A partnership between engineering                   and editorialTransforming Data into Stories
From the engineer’s perspectiveTransforming Data into Stories
From the writer’s perspectiveTransforming Data into Stories
The OutlineTransforming Data into Stories
The DataTransforming Data into Stories
The DerivationsTransforming Data into Stories
The AnglesTransforming Data into Stories
The StructureTransforming Data into Stories
Transforming Data into Stories
Big DataTransforming Data into Stories
The NotebookTransforming Data into Stories
“I don’t need a shelf full of folders…        I just need a two paragraph summary of the        stuff that is important fo...
In story form…    “We collect everything on how each account    is     performing. But we only have the people     to expl...
Performance reportingTransforming Data into Stories
Transforming Data into Stories
EducationTransforming Data into Stories
Transforming Data into Stories
The story is the last mile in                understanding Big DataTransforming Data into Stories
Real Estate                    Pharma                      Sales                   Politics                    Finance    ...
Wherever there is data, we can tell                    the storyTransforming Data into Stories
What about the unstructured world?Transforming Data into Stories
We track it and tag itTransforming Data into Stories
We structure itTransforming Data into Stories
And use it to write storiesTransforming Data into Stories
We Transform Data into          Stories are the bridge between numbers                        and knowing.                ...
Kristian J. HammondNarrative Science@whisperspace 34
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Scaling Content Development Through Automation
02/15/2012 8:30am - 9:15am
Kris Hammond

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  • 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
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    1. 1. Kristian J. HammondNarrative Science 1
    2. 2. We Transform Data into Stories and InsightTransforming Data into Stories
    3. 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. 4. February 9, 2012, Hockey Recap:Rio Grande Valley rolls over Laredo, 6-3The Rio Grande Valley Killer Bees were firing on all cylinders against the Laredo Bucks, and when the finalbuzzer 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. Pearsons next tally made the score 2-0 Rio Grande Valley with 12:44left in the first period. David Marshall assisted on the tally. The punch line…Special teams units factored heavily in the games outcome, as there were 14 penalties called on the twoteams. The busiest period in the sin bins was the first period, which saw 18 minutes of penalty time combinedbetween the two teams.The Killer Bees goal total was higher than their season average. Rio Grande Valley averages two goals pergame. The Killer Bees could not stay out of the penalty box, as the team accrued 17 minutes in penaltiesduring the game. The leading offender was Jason Beeman, who totaled five minutes in penalty time with onemajor. With 48 shots on target during the contest, Rio Grande Valley exceeded the 22 shots it averages pergame this year.Rio Grande Valley additionally got points from Aaron Lee, who had one goal and one assist, Marshall, whoregistered one goal and two assists, and Dan Gendur, who racked up one goal and one assist. Dan Nichollsalso scored for Rio Grande Valley. Others to record assists for Rio Grande Valley were AJ Mikkelsen, who hadtwo 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. 5. How does it work? The Data The Facts The Angles The Structure Stats Tests Calls T/F LanguageTransforming Data into Stories
    6. 6. Start with sports FinanceTransforming Data into Stories
    7. 7. Start with sports Real EstateTransforming Data into Stories
    8. 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? LanguageTransforming Data into Stories
    9. 9. A partnership between engineering and editorialTransforming Data into Stories
    10. 10. From the engineer’s perspectiveTransforming Data into Stories
    11. 11. From the writer’s perspectiveTransforming Data into Stories
    12. 12. The OutlineTransforming Data into Stories
    13. 13. The DataTransforming Data into Stories
    14. 14. The DerivationsTransforming Data into Stories
    15. 15. The AnglesTransforming Data into Stories
    16. 16. The StructureTransforming Data into Stories
    17. 17. Transforming Data into Stories
    18. 18. Big DataTransforming Data into Stories
    19. 19. The NotebookTransforming Data into Stories
    20. 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. 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. 22. Performance reportingTransforming Data into Stories
    23. 23. Transforming Data into Stories
    24. 24. EducationTransforming Data into Stories
    25. 25. Transforming Data into Stories
    26. 26. The story is the last mile in understanding Big DataTransforming Data into Stories
    27. 27. Real Estate Pharma Sales Politics Finance SportsTransforming Data into Stories
    28. 28. Wherever there is data, we can tell the storyTransforming Data into Stories
    29. 29. What about the unstructured world?Transforming Data into Stories
    30. 30. We track it and tag itTransforming Data into Stories
    31. 31. We structure itTransforming Data into Stories
    32. 32. And use it to write storiesTransforming Data into Stories
    33. 33. We Transform Data into Stories are the bridge between numbers and knowing. Stories and InsightTransforming Data into Stories
    34. 34. Kristian J. HammondNarrative Science@whisperspace 34

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