Big Data


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Big Data

  1. 1. Big Data Andrew Jeavons PresidentSurvey Analytics LLC
  2. 2. Overview• Coming out of the data desert.• What do we mean by Big Data ?• Behavior, Big Data and Market Research.• Get a model to get ahead.....
  3. 3. Data Desert• Data was scarce.. • The hunt for completes. • Sampling ? • Limited data. • Limited potential...
  4. 4. The Deluge • The Data Tsunami. • What we get.. • What we don’t get...
  5. 5. Forms of Data• Metadata, Paradata, Data• Big Data and Prediction of behavior.• The central dogma: • Big Data is Marxist. • Black Swans - Taleb’s cautionary tale...
  6. 6. Machine Learning• What is meant by this ?• Learning and pattern recognition.
  7. 7. Nerves and Genes • Neural Networks • Genetic Algorithms • “Agnostic” algorithms...
  8. 8. Neural NetworksOriginally sought to reproduce the waythe nervous system works.Had the ability to learn complexrelationships with any assumptions.Can learn complex non linearrelationships.
  9. 9. Back Propagation
  10. 10. Genetic Algorithms
  11. 11. Biological metaphor: encode problems as chromosomes.Fitness function.Evolve different mapping functions via principles of evolution.Cross over and mutation (note: mutation rates not as powerful asyou may think...)MR example: used GA’s to evolve panel sample balancing - rim balancing.
  12. 12. Social Media Data• We have a lot of text...that we didn’t have before...• Text has its own set of problems..unlike Gore Vidal we don’t speak in sentences.• “#itsucks phat”• Txt messages, social media messages.• Parsing and tokenizing
  13. 13. Sentiment Analysis• One of the frontiers for MR and Big Data• Can we tell the sentiment behind the comment ?• Text is messy because language is messy. • Grammatical vs Stochastic
  14. 14. Surveys, Market Research and Big Data• Fusion of data• Survey and behavioral• “Whole respondent” view• Surveys can be “big data”
  15. 15. Prediction and Market Research • Statisticians are the new “rock stars” (Eric Schmidt) • MR has to embrace prediction and realize the limits of explanation. It’s great to know why, better to know what’s next ? • Theories of respondents and consumers...