full transcript

From the Ted Talk by Susan Etlinger: What do we do with all this big data?

Unscramble the Blue Letters


But it doesn't have to be this way. We are not passive cernosmus of data and tnoogchely. We shape the role it plays in our lives and the way we make meaning from it, but to do that, we have to pay as much atttionen to how we think as how we code. We have to ask questions, and hard questions, to move past counting things to understanding them. We're constantly bombarded with stories about how much data there is in the wrlod, but when it comes to big data and the challenges of interpreting it, size isn't everything. There's also the speed at which it moves, and the many varieties of data types, and here are just a few examples: images, text, video, adiuo. And what unites this disparate types of data is that they're cetraed by people and they rrieque context.

Open Cloze


But it doesn't have to be this way. We are not passive _________ of data and __________. We shape the role it plays in our lives and the way we make meaning from it, but to do that, we have to pay as much _________ to how we think as how we code. We have to ask questions, and hard questions, to move past counting things to understanding them. We're constantly bombarded with stories about how much data there is in the _____, but when it comes to big data and the challenges of interpreting it, size isn't everything. There's also the speed at which it moves, and the many varieties of data types, and here are just a few examples: images, text, video, _____. And what unites this disparate types of data is that they're _______ by people and they _______ context.

Solution


  1. audio
  2. consumers
  3. world
  4. attention
  5. created
  6. technology
  7. require

Original Text


But it doesn't have to be this way. We are not passive consumers of data and technology. We shape the role it plays in our lives and the way we make meaning from it, but to do that, we have to pay as much attention to how we think as how we code. We have to ask questions, and hard questions, to move past counting things to understanding them. We're constantly bombarded with stories about how much data there is in the world, but when it comes to big data and the challenges of interpreting it, size isn't everything. There's also the speed at which it moves, and the many varieties of data types, and here are just a few examples: images, text, video, audio. And what unites this disparate types of data is that they're created by people and they require context.

Frequently Occurring Word Combinations


ngrams of length 2

collocation frequency
health media 4
people talk 3
orwell feared 2
huxley feared 2
big brother 2
big data 2
critical thinking 2


Important Words


  1. attention
  2. audio
  3. big
  4. bombarded
  5. challenges
  6. code
  7. constantly
  8. consumers
  9. context
  10. counting
  11. created
  12. data
  13. disparate
  14. hard
  15. images
  16. interpreting
  17. lives
  18. meaning
  19. move
  20. moves
  21. passive
  22. pay
  23. people
  24. plays
  25. questions
  26. require
  27. role
  28. shape
  29. size
  30. speed
  31. stories
  32. technology
  33. text
  34. types
  35. understanding
  36. unites
  37. varieties
  38. video
  39. world