The document outlines the importance of big data and the Internet of Things (IoT) for business management, delivered by data scientist Peadar Coyle. It emphasizes the need for skilled analysts to harness data for competitive advantage, showcases various industry case studies, and highlights the multifaceted applications of data science in decision-making. Additionally, it discusses the evolving role of data scientists and the significance of data products in modern business strategies.

1. Big Data and Internet of Things for
Managers
PeadarCoyle
@springcoil

2. Who am I?Who am I?
Keynote,SpeakerandTeacheratconferencesthroughout
Europe
Industryworkand'bigdata'blogger forseveralyears
Co-organizerofDataScienceMeetupinLuxembourg

3. Who do I work for?Who do I work for?
IworkintheProductteamasaDataScientistforJobTODAY
We'reaVC-backedrecruitmentappbasedinLuxembourg
www.jobtoday.com

5. So how come I care about data?So how come I care about data?
Well I always loved science.Well I always loved science.
I wanted to be a neuroscientistI wanted to be a neuroscientist

6. Then I fell in love with MathematicsThen I fell in love with Mathematics
I studied Quantum Mechanics at Bristol andI studied Quantum Mechanics at Bristol and
Mathematics in LuxembourgMathematics in Luxembourg

7. This gets a bit complicated...This gets a bit complicated...
And my cat was never much use...And my cat was never much use...

8. Along the way I learned someAlong the way I learned some
programming and other skills...programming and other skills...

9. I needed to find a careerI needed to find a career
And I decided Academia wasn't for me.And I decided Academia wasn't for me.
So I became a data scientist!So I became a data scientist!

10. Aimsofthetalk
Explainthesubstancebehindthephrase'bigdata'
Tellyouhowyoucanusedatainyourbusiness.
Helpyouunderstandtheimportanceofdatainyourbusiness
strategy.

11. What is a data scientist?What is a data scientist?
AstatisticianwholivesinSanFrancisco
AdataanalystwholivesinNewYork
DataScienceisstatisticsonaMac.
Adatascientistissomeonebetteratstatisticsthanany
softwareengineerandbetteratsoftwareengineeringthanany
statistician.
http://datascopeanalyticscom/what-we-think/2014/02/05/what-is-a-data-scientist

12. Why am I talking about this?Why am I talking about this?

13. What is the competitive advantage?What is the competitive advantage?
Massivelypersonalisedonlineexperiences
'Datamoats'arehardtocopy

14. AmazonAmazon: Supply chain and: Supply chain and
warehouse modelswarehouse models

15. Selecting 'House of Cards'Selecting 'House of Cards'
Source:Netflix
Idea:NetflixknewthatDavidFincherfanslikedpolitical
dramas,andthatKevinSpaceywasverypopular-from
analysingvideoplayingdata,andcustomerpreferences

16. HR AnalyticsHR Analytics
Predictiveanalyticsofwhowouldleaveyourfirm

17. So, who is talking aboutSo, who is talking about Big DataBig Data??
"Weprojectaneedfor1.5millionadditional
managersandanalystsintheUnitedStateswho
canasktherightquestionsandconsumethe
resultsoftheanalysisofBigDataeffectively."-
,McKinseyreport
Bigdata:Thenextfrontierforinnovation,
competition,andproductivity

18. Who else?Who else?

19. Gartner says 'Data is the new oil'Gartner says 'Data is the new oil'

20. But talk is cheap...But talk is cheap...
Bigdataisliketeenagesex:everyonetalksabout
it,nobodyreallyknowshowtodoit,everyone
thinkseveryoneelseisdoingit,soeveryone
claimstheyaredoingit...-
ProfessorDanAriely-DukeUniversity

22. Example: LinkedinExample: Linkedin

23. But I work in the real world not online!But I work in the real world not online!
UPSusesdatafromtheInternetofThingstotravelmore
efficientlyandsavemillionsonfuelconsumption.

24. So what other areas?So what other areas?
Thesearecasestudiesfromvariousmarketsegments
Theaimistohelpyoubrainstormapplications
Happytoansweranyquestionsafterwards

25. How do you recommend books?How do you recommend books?
Use Machine Learning!Use Machine Learning!

26. Preventative Maintenance forPreventative Maintenance for
WindmillsWindmills
Siemens are leveraging IoT dataSiemens are leveraging IoT data
'Source:EnglishWikipedia,originalupload15July2004by
-CreativeCommonsSharealikelicenseLeonardG.

27. Web Crawling and ScrapingWeb Crawling and Scraping
ZalandotheGermanfashione-commercecompany arescraping
millionsofwebsitestofindtrends.

28. Audio and visual dataAudio and visual data
Spotifyusessounddataintheirrecommendations!

29. Social media dataSocial media data

30. Fashion - Image AnalysisFashion - Image Analysis
Lyst.comleveragenovelhuman-in-the-looprecommendation
engines,recommendonthebasisofcoloursofclothes,anddo
cutting-edgeimageanalysiswithdeeplearning
alltoprovidevalueinFashion-Tech.

31. Recruitment dataRecruitment data
Howdoyoudisruptrecruitmentforblue-collarwork?
Onewayisbyleveraging'bigdata'todeliverbetterpersonalised
experiences,optimisethespendofmarketingbudgetand
reducecustomerchurn.

32. What about Metadata?What about Metadata?

33. Genomicsandhealthdataaretoo.
Healthcare dataHealthcare data

34. Even in Food...Even in Food...
MonsantoCEOrecentlysaid'datascienceispartofourgrowth
strategy'
MonsantoleveragesClimateCorpsalgorithmstoup-sell
fertiliserandotherservices

35. I hope you can see that there is...I hope you can see that there is...

36. Sowhygooddataanalysisishard?
Gettingdataishard
Buildingmodelsishard
Askingtherightbusinessquestionsisevenharder
Ioftenhavetoborrowlotsofpeoplesbrainstogetto
therightbusinessquestions...

37. Pick the right methodology for the jobPick the right methodology for the job
Text->topicmodelling,sentimentanalysis,information
extraction
E-commercedata->prospensityanalysis,collaborative
filtering
Multimedia->speech-to-text,audiofingerprinting,face
recognition
Clickstreamlogs->frequentpatternmining,sequenceanalysis
Yieldoptimisation->Optimisationmodels,weather
forecasting
Proton-protoncollisionfromLHC->Ihavenoideadespite
havingaPhysicsdegree

38. Andthenwhat?Wellyoucantellstorieswithvisualizations...

39. ButDataScientistsdon'tjustproducereports
Theyproducedataproductstoo.
Sowhatisadataproduct?
WellI'mgladyouasked...

40. What is a data product?What is a data product?
Adataproductprovidesactionableinformationwithoutexposing
decisionmakerstotheunderlyingdataoranalytics.
Examplesinclude:MovieRecommendations,Weather
Forecasts,StockMarketPredictions,ProductionProcess
Improvements,HealthDiagnosis,FluTrendPredictions,Targeted
Advertising.
–MarkHerman,etal.,FieldGuidetoDataScience

41. Here is an Example from Mailchimp:Here is an Example from Mailchimp:
When should I send that email?When should I send that email?

42. And produce a magic button :)And produce a magic button :)

43. Case Study - Marketing Analytics: InCase Study - Marketing Analytics: In
the Game Industrythe Game Industry
1)Usesgamersplaydatatooptimizemarketing
communicationsacrosschannels.-Customersegmentation
modelling
2)BuildingPersonalizationEngineRulesfor1:1
communicationswithindividualgamers.Tohelpreducecustomer
churn.
3)Predictsgamerslikelihoodtochurnortorespondto
up-selloffers.

44. ExampleExample
Hereisagraphofactiveusersonanonlinegame.Marketing
teamsusetoolslikethistomonitortheircustomersinreal-time

45. Example:Supply Chain ManagementExample:Supply Chain Management
TheseareexamplesfromTableauanexcellentdatascienceproduct-basedonlaptopsizeddata
sets.SimilartomyAmazonwork. Howeverthesecanalsobebuiltwithopensourcetools.

46. Electricity DemElectricity Demand predictionand prediction
Analysing IoT data for demandAnalysing IoT data for demand
predictionprediction

47. Andletdatabeyourguide.
So you can do an experimentSo you can do an experiment

48. User Conversion after a website change.User Conversion after a website change.
..

49. Example: Financial AnalysisExample: Financial Analysis

50. Quantopian IncQuantopian Inc
Leveragingbigdatatobetterassesstheefficiencyoftrading
algorithms.
QuantopianIncisbuildingacrowd-sourcedhedgefundtheygive
theinfrastructure,capitalandresearchtocompetewithWall
Street.

51. Example: Moving average of AAPLExample: Moving average of AAPL

52. Especiallywithchangesinregulation...
Risk is also data science challengeRisk is also data science challenge

53. Data can be used for NGO'sData can be used for NGO's
Thisisawebappofhousepricesandcommutes,doneforanNGO
inLondonwhowantedtoshowtheeffectsof
changesinhousepricesonpeoplescommutes.

54. Politics: Hilary ClintonPolitics: Hilary Clinton
DataScientistsforhercampaignhelpoptimisemediabuys,
analysetheeffectofcommunicationandoptimisethedonor
acquisitionstrategy.

55. So why would I need a data scientist?So why would I need a data scientist?
Youmayalreadyhaveone.Iknownumerousbusiness
intelligence,dataanalysts,businessanalysts,riskanalystswho
AREdatascientists.
Alternativelyyoucanhireadataanalyticsconsultanttohelpyou
getstarted.
ButwhatsignalsshouldIlookfor?
Welltherearemanyanswers...Like...

56. Does this sound like you?Does this sound like you?
Are you losing customers and not understandingAre you losing customers and not understanding
why?why?
Are you making decisions on the basis of data or onAre you making decisions on the basis of data or on
the basis of 'gut feeling'?the basis of 'gut feeling'?
Are you changing your websites or products on theAre you changing your websites or products on the
basis of data driven experimentation?basis of data driven experimentation?

57. If you want Interviews with expertsIf you want Interviews with experts
http://bit.ly/1Uks2Rr orwww.peadarcoyle.com

58. Thank You For ListeningThank You For Listening
Anyquestions?
Reachouttomeifyouhaveanydataquestions.
I'llbedoingatrainingon'bigdata'atNyukosoon.
@springcoil
SearchPeadarCoyleonLinkedin
peadarcoyle@googlemail.com