Big Data in Media

601 views

Published on

This survey of big data and advanced technology as it relates to media was given to an industry association in November of 2012. Rocket Fuel

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
601
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
12
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Big Data in Media

  1. 1. “Big Data” for Media November 20, 2012This presentation was prepared by SoundView Technology Group and is being provided to the Danish Media Association to promote discussion and provide information. Allinformation contained herein is freely shareable by the association as well as anyone participating in the workshop. Attribution is appreciated but not required.
  2. 2. Kris Tuttle 1979-1981Related Work Hardware, Programming 1981-1992 Applied AI, CMU, IBM 1993-2004 Equity Research, Banking, Brokerage, Investing 2004-Present Advisor, Entrepreneur, Researcher, Publisher, Programmer 2
  3. 3. Eddie Obeng:After Midnight 3
  4. 4. Eddie Obeng:After Midnight 4
  5. 5. Eddie Obeng:After Midnight 5
  6. 6. Discussion Points • Flyover of recent significant related events and developments • Unpacking “Big Data” and looking at the pieces • The intersection of big data and media: • The obvious – advertising, targeting, conversions • Data analysis = content? • Content discovery, generation and ranking • Hyper-personalization & attenuation • Wrap up and transition to Q&A© SoundView Technology Group 2012 6
  7. 7. Flyover – Evolution of what’s News Source: Monday Note© SoundView Technology Group 2012 7
  8. 8. Flyover – Artist Control 8
  9. 9. Flyover – “Amateur” Content DevelopmentThe Kickstarter model is disrupting the way things are created,produced and initially adopted. 9
  10. 10. Flyover – Sourcing & Distribution 10
  11. 11. Flyover – Sourcing & Distribution 11
  12. 12. Flyover – Data Analysis as Content 12
  13. 13. Flyover – Mobile 13
  14. 14. How Big Data Looks Size Speed Big Data Applications Smörgåsboard Sloppy© SoundView Technology Group 2012 14
  15. 15. Unpacking Big Data • Often not that big in terms of size often less than 1TB • There is real big data and it’s sometimes enormous ~20 PB/day • Tends to have additional special features: o Multiple sources – transactional, log files, databases, geospatial, o Semi or unstructured – clickstreams, html, sensor data o Shorter duration – seconds to days versus weeks to months o More flexible – sometimes scheme-less, and built for speed • Today the default technology for most projects is Hadoop • Some machine learning is becoming a common feature© SoundView Technology Group 2012 15
  16. 16. Tools are Immature© SoundView Technology Group 2012 16
  17. 17. New DB Technologies© SoundView Technology Group 2012 17
  18. 18. New Language Technology© SoundView Technology Group 2012 18
  19. 19. Data for Targeting & Conversion© SoundView Technology Group 2012 19
  20. 20. Data for Targeting & Conversion • Integrating geospatial data for local advertising • Intersecting social data with news and search for customization • Going beyond “A/B testing” and using real-time data analysis to improve content on the fly • Saved data opens the door to machine learning and better algorithms© SoundView Technology Group 2012 20
  21. 21. Data Analysis as Content • Increased building of proprietary data and surveys – no brainer • In-house data scientists and coding capabilities will help • There are quite a few good text analysis and processing tools out there – NLTK, Python • NoSQL and Network DB tecnology can help© SoundView Technology Group 2012 21
  22. 22. Data-driven Editorial & Contributions© SoundView Technology Group 2012 22
  23. 23. Using Data to Hyper-Personalize • The future of reader relationships is about more than content quality – readers will grow to expect highly personalized content • Managing, distributing and “learning” from collected data requires a much more sophisticated view of how content is represented, managed and distributed© SoundView Technology Group 2012 23
  24. 24. Getting Started – Education© SoundView Technology Group 2012 http://bigdatauniversity.com/ 24
  25. 25. Getting Started – Data Sources© SoundView Technology Group 2012 25
  26. 26. Getting Started – Vendors© SoundView Technology Group 2012 26
  27. 27. Getting Hygge with Big Data • We are still in the very early days of implementation – nothing is precluded • Appoint or hire a “data czar” - more than a point person, the one who can translate the technology into implementation opportunities • For each line of business map revenue growth and profit margins to variables that might be improved with more data and better analysis • In-house custom coding capability is a strategic advantage – data integration remains a big challenge • Start building some proprietary data – surveys, histories, aggregations • Are any ideas worth implementing in the local market? (Zite, HuffingPost, NYT/Nate Silver) • Experiment, experiment, experiment© SoundView Technology Group 2012 27
  28. 28. 28
  29. 29. Kris Tuttlekris@soundviewadvisory.com +1-617-934-1877 (US)+33(0)6.7439.8593 (France)

×