El impacto del big data en la estrategia de los medios de comunicacion by Oscar Mendes de Stratio Primer Encuentro Big Media by Actuonda Madrid 2014
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El impacto del big data en la estrategia de los medios de comunicacion by Oscar Mendes de Stratio Primer Encuentro Big Media by Actuonda Madrid 2014

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El impacto del Big Data en la estrategia de negocio de los medios de comunicación ...

El impacto del Big Data en la estrategia de negocio de los medios de comunicación
Oscar Mendez (CEO, Stratio)
@omendezsoto @stratioDB

Primer encuentro BIG MEDIA
Conectando Media, Audiencia y Publicidad con Datos
24 de junio 2014, Madrid
• Sponsor Platinum : Perfect Memory
• Sponsor Gold : Stratio, Paradigma
• Con el apoyo de : Big Data Spain, Medios On
• Socio tecnológico : Agora News
• Organizadores : Actuonda y Cátedra Big Data UAM-BM
• Contacto : Nicolas Moulard (Actuonda) moulard@actuonda.com @Radio_20
www.bigmediaconnect.es

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El impacto del big data en la estrategia de los medios de comunicacion by Oscar Mendes de Stratio Primer Encuentro Big Media by Actuonda Madrid 2014 Presentation Transcript

  • 1. El impacto del Big Data en la estrategia de negocio de los medios de comunicación
  • 2. Too many Vs for Big Data Batch of new technologies that allow us to extract value out of a dataset which, due to it’s volume, variety or velocity, was not previously exploited
  • 3. “Set of new technologies, able to extract additional value of all the available data of a company”
  • 4. Petabytes: Google 300 PB, facebook: 45 PB, Yahoo! 180 PB Exabytes: U.S. healthcare Zetabytes: 2011, 1.8 ZB created. World Information 9.57 ZB YottaByte, Brontobyte, GeopByte to be reached I don’t have so much data… A big European company = Terabytes
  • 5. Why does it apply to my case?
  • 6. Ever increasing amount of data, and more heterogeneous: Ubiquity, mobility, geolocation, social networks, internet, sensors, M2M
  • 7. Unstructured or semi structured data, equal to 85% of available data, is not used by companies This represent the new Fuel for companies Specially for media
  • 8. You can’t stay stuck in old paradigms
  • 9. MARKET TRENDS
  • 10. Value and real ROI are the best KPIs •Increase of client acquisitions • Resource optimization • Increase in sales • Customer loyalty
  • 11. It is not just another trend
  • 12. Opportunities/possibilities Threats/risk for mediaThreats/risk for media
  • 13. The Bubble filter
  • 14. You must enter in the user bubble
  • 15. 83% of the surveyed companies were able to do things with Big Data that seemed impossible to achieve before “The art of possible” “Impossible is not a fact, it’s an opinion”
  • 16. DATA JOURNALISM && DATA DRIVEN JOURNALISM
  • 17. “Datajournalism can be based on any data that has to be processed first with tools before a relevant story is possible. It doesn't include visualisation per se"
  • 18. Data journalism with Social networks tracking (Tag Clouds)
  • 19. Data journalism with Social networks tracking and flow of data
  • 20. Data journalism with Social networks tracking and geolocation
  • 21. Data journalism with Sentiment analysis and semantic engines
  • 22. Description: Search the social network comments and mentions of interest of a particular issue or event for further evaluation, influencers detection and graphical display of the conversation to facilitate analysis. Advantages: Show real-time event (symposium, forum, seminar, etc..) with visual information. Data journalism with Social networks tracking Application Get opinions and feelings about a topic in social networks in real time Identify the influencers of a hot topic Risk detection and prevention Emotional mining: Know the term that is most popular for some people, brand, event, etc.and this way you can know about the generated feelings by the most important terms.
  • 23. Description: Search the network content and publications on specific subjects of our interest, to detect, filter, collect and process relevant information in semi- real time or batch. Associated with the semantic analysis this allows the detection and classification of the contents effectively. Advantages: Data journalism with Web Content Crawling and Scraping Advantages: Allows the generating of sites in a dynamic way without any intervention or exhaustive searches, with the contents collected and categorized. Unifies in a single web all the tasks that users have to do manually, so it saves them money and generates loyalty.
  • 24. EXAMPLES MEDIA COMPANIES
  • 25. Description: Customizing homepages based on user navigation Analysis and customization of the homepage and site in real time for each user based on their browsing Modification of contents, highlights, ads, in real time based on user history Advantages: Over 300% increase in clickthrough Creating millions of web pages in real time Customizing Web Sites: Behavioral Customization +160% clicks vs. one size fits all +79% clicks vs. randomly selected +43% clicks vs. editor selected Recommended links News Interests Top Searches Creating millions of web pages in real time Increasing Conversions Increase in sales Cost ten times lower than other solutions
  • 26. Description: Monitoring the download and streamming of videos. Analysis of streaming Quality of streaming Tele5: Monitoring of Streaming Videos Peaks of service and bottle neck Advantages: Problems detection and alerts Optimization of service Tracking of campains
  • 27. Description: Allows you to label and categorize automatically and massively, any type of content or information. Advantages: Allows searching, categorization, clustering, and be able to extract value out of information otherwise hardly findable and usable. Utilizes state of the art tools to identify entities, NED systems, NERD. These tools combined with the use of disambiguation of entities using a Big Data system containing the Wikipedia and other sources of information. Massive information tagging Speed processing capabiliƟes and data volume superior to that of other systems.
  • 28. Description: Newsletter development, email-marketing or any other sent material segmented by individual preferences Analyzes and takes into account: • Financial information and user data • Navigation and usage information from previous marketing shipments • Mobile app data (GPS, payments, browsing of offers…) • Users’ information from the social networks Personalized Marketing with Big Data • Users’ information from the social networks Advantages: Increased clickthrough Increase in conversions and sales Natural language processing – semantics and sentiments Combines private and public data
  • 29. Description: Big Data Search Assist: Search engines optimized for Big Data with self-learning improvements based on use Search engines for websites, intranets, apps With instant real-time search, single box with natural language processing, suggestions, highlighting, automatic corrections, “you wanted to say” tips, etc ... Advantages: Search Engines Advantages: Easy management for business users: Order of results, filters, etc ... Advanced features of the search engines with a cost ten times lower than other solutions Improved performance and scalability compared to other solutions Easy to integrate and use
  • 30. SUMMARY
  • 31. Is not about Big Data, is about getting value from data: To have applications managing data that help people to make better his work To get all the data from your users to make the best use of the contents you have: • Customization• Customization • Recommendation To generate contents from data in news ways of visualization: Data Jounalism
  • 32. The Opportunity to … Ride The “Big Data” wave
  • 33. Q&A
  • 34. THANKS “the best way to predict the future is to create it” THANKS
  • 35. Organizadores Sponsor platinum Sponsor Gold Con el apoyo de Socio tecnológico Nicolas Moulard, Director de Actuonda moulard@actuonda.com Tel : +34 699 248 200 @Radio_20