Big Data Analytics: Facts and Feelings
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Big Data Analytics: Facts and Feelings

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Presentation by Seth Grimes to the Washington DC chapter of the Data Warehousing Institute, June 21, 2013.

Presentation by Seth Grimes to the Washington DC chapter of the Data Warehousing Institute, June 21, 2013.

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  • there are lots of Analytics fatcs can be found at this blog

    http://blogs.bridgei2i.com/2014/03/04/social-customer-intelligence-bridgei2i-infographic/



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Big Data Analytics: Facts and Feelings Presentation Transcript

  • 1. Big Data Analytics:Facts and FeelingsSeth GrimesAlta Plana Corporation@sethgrimesTDWI – Washington DCJune 21, 2013
  • 2. Big Data Analytics: Facts and FeelingsTheses• We gain knowledge when we makeconnections.• Data analysis is a process of connectiondiscovery.• The more data, the greater the possibilities.• The more data, the greater the need to filter,reduce, and contextualize.• Timeliness counts.
  • 3. Big Data Analytics: Facts and FeelingsThe World of Big DataMachine data (e.g., logs, sensor outputs,clickstreams).Actions, interactions, and transactions:geolocation and time.Profiles: individual, demographic & behavioral.Text, audio, images, and video.Facts and feelings.
  • 4. Big Data Analytics: Facts and FeelingsA 3-slide reprise...
  • 5. Big Data Analytics: Facts and FeelingsImperatives for the 2010s:Do more with more.“It’s Not Information Overload. It’s FilterFailure”: Clay Shirky, 2008.• More sources & types of data.• Greater data volumes.• New hardware and methods.Automate more, more intelligently.• Analytics.• Semantics.Engage. Socialize.
  • 6. Big Data Analytics: Facts and FeelingsI see three categories of data:1. Quantities, whether measured, observed, orcomputed.2. Content, which I’ll characterize as non-quantitative information.3. Metadata (semantic & structural) describingquantities and content.• Our concern is content, analytics & fusion.• Structured/unstructured is a falsedichotomy.• Where do relationships fit?
  • 7. Big Data Analytics: Facts and Feelingshttp://www.businessweek.com/magazine/content/04_19/b3882029_mz072.htmEn route.
  • 8. Big Data Analytics: Facts and FeelingsEnd of reprise. So, is this Big Data?
  • 9. Big Data Analytics: Facts and FeelingsOf course not. It’s a number, not data.Size (Volume) is only one Big Data factor.Other factors (standard definition) areVelocity and Variety.I reject reVisionist 3Vs extensions such as:Variation/Variability.Veracity.Value.These factors are the province of analytics.
  • 10. Big Data Analytics: Facts and FeelingsGary King, Harvard Univ. –“Big Data isn’t about the data. It’s aboutanalytics.”Me –Analytics is a collection of tools andtechniques that extract insights from data.I’d argue –The Value in Big Data is in content, patterns,and connections, derived via analytics.
  • 11. Big Data Analytics: Facts and FeelingsVariability is an interpretive property. I say –The sense of Big Data is in context andintent…of both the data producer and thedata consumer, captured in metadata and(also) derived via analytics.
  • 12. Big Data Analytics: Facts and FeelingsAs for Veracity, data is data. Consider:“The Iraqi regime… possesses and produceschemical and biological weapons.” –George W. Bush, October 7, 2002.
  • 13. Big Data Analytics: Facts and FeelingsData… and more. Is this Big Data?No, it’s a screen of aggregated query results.
  • 14. Big Data Analytics: Facts and FeelingsThe Big Data is behind it.http://www.newyorker.com/online/blogs/culture/2012/05/google-knowledge-graph.html
  • 15. Big Data Analytics: Facts and FeelingsAnd behind comparably-scaled/structuredsystems.
  • 16. Big Data Analytics: Facts and FeelingsComparably-scaled/structuredsystems?http://www.cambridgesemantics.com/semantic-university/semantic-search-and-the-semantic-web
  • 17. Big Data Analytics: Facts and FeelingsGraphs model language models relationships.
  • 18. Big Data Analytics: Facts and FeelingsAnother view, using an old GATE image.http://gate.ac.uk/hamish/talks/ibot-slidy.html
  • 19. Big Data Analytics: Facts and Feelings… for instance, social language.
  • 20. Big Data Analytics: Facts and FeelingsText analytics applies natural-languageprocessing (NLP) techniques to discern –EntitiesRelationshipsContextIdentity– and get at the sense of “unstructured”online, social, and enterprise information.Semantic identity unites data of all types.
  • 21. Big Data Analytics: Facts and Feelingshttp://searchuserinterfaces.com/Sensemaking:“It is convenient to divide the entireinformation access process into twomain components: informationretrieval through searching andbrowsing, and analysis andsynthesis of results. This broaderprocess is often referred to in theliterature as sensemaking.Sensemaking refers to an iterativeprocess of formulating aconceptual representation from ofa large volume of information.”– Marti Hearst, 2009
  • 22. Big Data Analytics: Facts and FeelingsIntelligent computing – sensemaking –involves:Big (and little) Data.• Quantities.• Content.• Metadata.Analytics.Semantics.Integration.Facts and feelings.
  • 23. Big Data Analytics: Facts and FeelingsFeelings: Sentiment detection, classification.
  • 24. Big Data Analytics: Facts and Feelingshttp://techpresident.com/news/21618/politico-facebook-sentiment-analysis-bogus
  • 25. Big Data Analytics: Facts and Feelings“Sentiment analysis is the task of identifying positiveand negative opinions, emotions, and evaluations.”-- Wilson, Wiebe & Hoffman, 2005, “RecognizingContextual Polarity in Phrase-Level SentimentAnalysis”“Sentiment analysis or opinion mining is thecomputational study of opinions, sentiments andemotions expressed in text… An opinion on a featuref is a positive or negative view, attitude, emotion orappraisal on f from an opinion holder.”-- Bing Liu, 2010, “Sentiment Analysis and Subjectivity,” inHandbook of Natural Language Processing
  • 26. Big Data Analytics: Facts and FeelingsSentiment may be of interest at multiplelevels.Corpus / data space, i.e., across multiple sources.Document.Statement / sentence.Entity / topic / concept.Human language is noisy and chaotic!Jargon, slang, irony, ambiguity, anaphora,polysemy, synonymy, etc.Context is key. Discourse analysis comes intoplay.
  • 27. Big Data Analytics: Facts and FeelingsEmotion and effect.
  • 28. Big Data Analytics: Facts and FeelingsEmotion and understanding.
  • 29. Big Data Analytics: Facts and FeelingsPrediction/Feeling/Wish... and Intent.http://www.aiaioo.com/whitepapers/intention_analysis_use_cases.pdfhttp://sentibet.com/
  • 30. Big Data Analytics: Facts and FeelingsMany options (text).
  • 31. Big Data Analytics: Facts and Feelings(Accessible) Data Everywhere
  • 32. Big Data Analytics: Facts and FeelingsBeyond Text:• Audio including speech.• Images.• Video.http://www.geekosystem.com/facebook-face-recognition/http://www.sciencedirect.com/science/article/pii/S0167639312000118http://flylib.com/books/en/2.495.1.54/1/
  • 33. Big Data Analytics: Facts and FeelingsOr just ask: Swipp mobile polling (example).
  • 34. Big Data Analytics: Facts and FeelingsSurfaced.
  • 35. Big Data Analytics: Facts and FeelingsA Big Data analytics architecture (example).http://www.geeklawblog.com/2011/12/lexis-advance-platform-launch-two.html
  • 36. Big Data Analytics: Facts and FeelingsComplementary.
  • 37. Big Data Analytics:Facts and FeelingsSeth GrimesAlta Plana Corporation@sethgrimesTDWI – Washington DCJune 21, 2013