Music Videos and Gastronomification for Big Data Analysis Thomas Levine & Brian Abelson csv soundsytem
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1 MusicVideosand Gastronomificationfor BigDataAnalysis ThomasLevine&BrianAbelson csvsoundsytem big data talk
2 csvsoundsystem Bigdataconsultingfirmbasedin NewYork Specialties Keepthingssimple Makingthingsthatpeopleunderstand csv standsfor comma separated values
3 Big data
4 Voluminous data
5 Complex data
6 Voluminous data Complex data
7 Voluminous data Big data Complex data
8 rowid price updated Voluminous spreadsheet
9 id price updated long lat zip Complex spreadsheet
10 Big spreadsheet
11 Aggregation High volume spreadsheet Low volume spreadsheet
12 Dimensionalityreduction Complex spreadsheet Simple spreadsheet
13 Visualizing big data
14 GraphsonHadoop
15 Talktothesepeople
16 What about complex data?
17 Data Visualization
18 Data Visualization
19 Data Dimensionality reduction Data Visualization
20 Data Visualization
21 Data Musicvideos
22 Data Gastronomification
23 Tradeoffs: Scalesofmeasurement Ratiodata Intervaldata Ordinaldata Nominaldata Visuals,music, andfoodcanall doeachlevel Ratioand intervalare moredifficult withfood
24 Other benefits of music videos and gastronomification
25 Application:Complexdata fornon technicalaudiences Situation: Peopleunderstandbargraphs,butthey areunivariate. Graphscaneasilyrepresentsix variables,butpeopledon'talways understand. Problem:Graphsaretooabstract Solution:Musicandfood
26 Engagingyoungaudiences
27 Data drivenculture
28 Dataguacamole NewYorkCitymathtestscores 32districts 6grades(3rdthrough8th) 7years(2006to2012) Abowlforeachyear Levelsofingredientsbasedon relativetestscoresfordifferent schoolsindifferentgrades
29 Dataguacamole
30 Censusspices spices on itp
31 Modelingmobileadclicks Decisivemobileadvertisement targeting( Collectingdataon10%ofall mobileadtraffic Biddingalgorithmusespredictive modelingwithmachinelearning Representingdataastacostuning theirbiddingalgorithms
32 Decisive jalapeno=wifi (versus3g/4g) cheese=clickedad taco=adimpression meat typeofphone onions=shownad
33 Classifyinghealthcare eligibility BoozAllenHamilton Systemtodeterminehealthcare eligibilityofpeople Dataset: Eachrecordisaperson. Mostfeaturesaredates. Usingsheetmusic(ourspreadsheet basedsmalldatasolution)todetect incorrectclassifications
34 ThesearenotBoozAllen'sdata;wecan't showyouthose.
35 Whatabout realtimebigdata gastronomification?
36 ThreeV'sof BigData
37 Voluminous Big Complex data data data
38 Variety Volume
39 Variety Volume Velocity
40 HotKarot ( OpenSaucetechnology Connectstovariousdatasources Realtime
41
42 Ourrealtimesolution Demo
43 our open source libraries
44 ddr,ddpy,& sheetmusic
45 Music software Data software
46 Music software Data software
47 Mergingdatasoftware andmusicsoftware ddr:musicsequencerbackedbyr vectorsanddata.frames ddpy:midigeneratorbackedby pandasdataframes. sheetmusic:web basedmusic compositionbackedbygoogle Spreadsheets
48 geom_taco
49 Whywewrotegeom_taco Dependenceonhumanexpertslimits gastronomification OpenSauce( CensusSpices geom_tacousescommodity infrastructure Robust,scalable,inexpensive
50 geom_taco Ageomforggplot Non visualaesthetics Fill Salsa Guacamole...
51 End
52 Jobs Salespersons JavaEngineers TestEngineers
53 ThomasLevine BrianAbelson
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