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Big Data for Startups

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Big Data for Startups - Practical tips for applying Big Data for your own startups

Published in: Software, Technology

Big Data for Startups

  1. 1. Big Data for Startups Ngon Pham - Lead Engineer & CTO at Lana
  2. 2. Content ● Introduction ● 10 practical problems & solutions ● Q & A
  3. 3. Introduction ● How to make use of social platforms to empower your startups ○ Facebook ○ Youtube ○ Foursquare
  4. 4. Problem 1 ● How to integrate Facebook user information into your product ● Solution ○ Allow Facebook sign-in, ask for related permissions ○ Use the token to build user reflection for your product: Bio, Statuses, Events, Groups, Likes… ○ Demo
  5. 5. Problem 2 ● How to integrate Facebook into your vertical eCommerce site for social marketing ● Solution ○ Integrate Facebook sign in, ask for token to analyze user bio, their likes and compute user interest score ~ how they are interested in your category ○ Encourage them to like your page, share your product basing on their interest score
  6. 6. Problem 3 ● How to analyze Facebook users, and do the target marketing even if you don’t know how to code ● Solution ○ Use http://www.ocommunity.net/ ○ Facebook ad targeting by user ID ○ Demo
  7. 7. Problem 4 ● How to crawl all Foursquare places for a specific country ● Solution ○ Use a simple spreading algorithm ○ Demo: Vietnam, Singapore, Indonesia, Cambodia
  8. 8. Problem 5 ● How to use Foursquare as a social layer to empower your reviewing site: Travel, Food... ● Solution ○ Do a matching (manually / semi-auto) between Foursquare places and your database ○ Constantly get updates from Foursquare for: Number of checkins, Photos, Tips...
  9. 9. Problem 6 ● How to crawl all videos for a specific language on Youtube ● Solution ○ Use a language detection library https://code.google. com/p/language-detection/ ○ Crawl using Related Video API provided by Youtube ○ Demo
  10. 10. ● How to build a classified video app on top of Youtube ● Solution ○ Crawl all videos & develop some filtering algorithms ○ Some useful tools for cleaning / sampling data: Google Refine, R… ○ Demo Problem 7
  11. 11. ● How to scale processes across machines? ● Solution ○ Use a Queue server for dividing the workload https: //www.rabbitmq.com/ Problem 8
  12. 12. ● How to export processed data for end-users as a website ● Solution ○ Use Wordpress ■ Data model is very simple ~12 tables ■ Tons of plugins and themes ○ Demo Problem 9
  13. 13. ● How to export processed data for Business Intelligence / Visualization ● Solution ○ Export processed data to MySQL ○ Use Pentaho / JasperReport to hook in ○ Demo Problem 10
  14. 14. Q & A Q & A

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