How can Data Science benefit your business?
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This document provides an overview of how data science can benefit businesses and examples of how data science has been applied in different industries. It discusses how data scientists can help businesses harness big data by performing tasks like customer segmentation, predictive analytics, forecasting, and developing data products. The document also provides several case studies and examples of how specific companies have used data science for applications such as optimizing marketing strategies, reducing customer churn, and improving supply chain management.
How can Data Science benefit your business?
- 1. How can Data Science benefit your business? PeadarCoyle DataAnalytics Consultant @springcoil
- 3. I did Data in ShanghaiI did Data in Shanghai Helpinganeventwebsitetargetitscustomers
- 4. Data in LondonData in London Datageeksneedtoolslikethese,Ihelpedlaunchthebeta.
- 5. I worked with Data in LuxembourgI worked with Data in Luxembourg Forasmalle-commercewebsite.DoingSupplyChainmodels.
- 6. Now I work withNow I work with Data in Luxembourg @Data in Luxembourg @
- 7. In Air Traffic ManagementIn Air Traffic Management BTWAirtravelproducesALOTofdata!
- 8. 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
- 9. Then I fell in love with PhysicsThen I fell in love with Physics I studied Quantum Mechanics andI studied Quantum Mechanics and Quantum Optics at BristolQuantum Optics at Bristol
- 10. This gets a bit complicated...This gets a bit complicated... And my cat was never much use...And my cat was never much use...
- 11. So I ended up in Math & Stats...So I ended up in Math & Stats...
- 12. Along the way I learned someAlong the way I learned some programming and other skills...programming and other skills...
- 13. 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! Now what skills does a data scientist have?Now what skills does a data scientist have?
- 15. To me data Science is a lot like ScienceTo me data Science is a lot like Science
- 16. But the hardest thing to learn has been..But the hardest thing to learn has been.. “Beingadatascientistisnotonly aboutdatacrunching.It’sabout understandingthebusiness challenge,creatingsomevaluable actionableinsightstothedata, andcommunicatingtheirfindings tothebusiness.” Jean-PaulIsson,Monster Worldwide,Inc.
- 17. I'm still learning the tech stuff tooI'm still learning the tech stuff too What is Machine learning?What is Machine learning? Well this next slide might help...Well this next slide might help...
- 19. What is Data Science?What is Data Science? Data Scientists help you harness theData Scientists help you harness the value of 'big data'value of 'big data'
- 20. So, who is talking about Big Data?So, who is talking about Big Data? "Weprojectaneedfor1.5millionadditional managersandanalystsintheUnitedStateswho canasktherightquestionsandconsumethe resultsoftheanalysisofBigDataeffectively."- ,McKinseyreport Bigdata:Thenextfrontierforinnovation, competition,andproductivity
- 22. Gartner says 'Data is the new oil'Gartner says 'Data is the new oil'
- 24. But talk is cheap...But talk is cheap... Bigdataisliketeenagesex:everyonetalksabout it,nobodyreallyknowshowtodoit,everyone thinkseveryoneelseisdoingit,soeveryone claimstheyaredoingit...- ProfessorDanAriely-DukeUniversity
- 25. So how do you get value out of yourSo how do you get value out of your data?data?
- 26. You could hire a data scientistYou could hire a data scientist This talk is aimed at helping you understand if youThis talk is aimed at helping you understand if you need to hire a 'data scientist'.need to hire a 'data scientist'.
- 28. Or this talk could have been titled...Or this talk could have been titled... But Peadar where are the businessBut Peadar where are the business examples?examples?
- 31. But I work in the real world not online!But I work in the real world not online! UPSusesdatatotravelmoreefficientlyand savemillionsonfuelconsumption.
- 32. What is "Big Data" anyway?What is "Big Data" anyway? Customerpeferencedatais...
- 33. What is "Big Data" anyway?What is "Big Data" anyway? Wind sensor data is tooWind sensor data is too 'Source:EnglishWikipedia,originalupload15July2004by -CreativeCommonsSharealikelicenseLeonardG.
- 34. What is "Big Data" anyway?What is "Big Data" anyway? Webcrawlingdataistoo
- 35. What is "Big Data" anyway?What is "Big Data" anyway? Audioandvisualdataistoo
- 36. What is "Big Data" anyway?What is "Big Data" anyway? SocialMediadatamustbetoo
- 37. What is "Big Data" anyway?What is "Big Data" anyway? Nottomentionsocialmediametadata
- 38. Genomicsandhealthdataaretoo. What is "Big Data" anyway?What is "Big Data" anyway?
- 39. AndwhataboutParticlePhysicsdata? What is "Big Data" anyway?What is "Big Data" anyway?
- 40. I hope you can see that there is...I hope you can see that there is...
- 41. Remember this slide?Remember this slide?
- 43. 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 Proton-protoncollisionfromLHC->Ihavenoideadespite havingaPhysicsdegree
- 46. 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
- 47. But you said...But you said...
- 48. Here is an Example from Mailchimp:Here is an Example from Mailchimp: When should I send that email?When should I send that email?
- 49. Step 1 to 100: Data Scientists - do lots ofStep 1 to 100: Data Scientists - do lots of analysis...analysis...
- 50. And produce a magic button :)And produce a magic button :)
- 51. Define Data ScienceDefine Data Science Itistheapplicationofscienceandmodelstoreallycomplex humanproblems Suchas:Whoisbuyingourproduct,whyaretheyleavingour service. Datascientistsleveragemathematicsandcomputerscienceto deliverbusinessvaluesuchassmootheroperations,enhancing yourmarketingstrategyor forecastingsupplyanddemand. Inshortdatascientistshelpyouprepareforthefuture.
- 54. 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.
- 56. What about forecasting? Do you mean the weather?What about forecasting? Do you mean the weather? (In Ireland and the UK it is quite easy - just guess rain(In Ireland and the UK it is quite easy - just guess rain all the time!)all the time!) But there are other kinds of forecasts such as supplyBut there are other kinds of forecasts such as supply chain forecasts or demand forecasts....chain forecasts or demand forecasts....
- 57. Example:Supply Chain ManagementExample:Supply Chain Management TheseareexamplesfromTableauanexcellentdatascienceproduct-basedonlaptopsizeddata sets.SimilartomyAmazonwork. Howeverthesecanalsobebuiltwithopensourcetools.
- 58. But predicting the future is hardBut predicting the future is hard "It’s Difficult to"It’s Difficult to Make Predictions,Make Predictions, Especially AboutEspecially About the Future" -the Future" - Niels BohrNiels Bohr
- 59. Andletdatabeyourguide. So you can do an experimentSo you can do an experiment
- 60. User Conversion after a website change.User Conversion after a website change. Luckily they measured it. They learned the websiteLuckily they measured it. They learned the website change was a bad decision.change was a bad decision.
- 61. Sometimes in life you just need picturesSometimes in life you just need pictures or data visualizations, like this...or data visualizations, like this...
- 62. Or this: Number of wind turbines by state in the US?Or this: Number of wind turbines by state in the US?
- 63. But this is Luxembourg...But this is Luxembourg... So we need finance examples...So we need finance examples...
- 64. Example: Financial AnalysisExample: Financial Analysis
- 65. Example: Moving average of AAPLExample: Moving average of AAPL
- 66. Especiallywithchangesinregulation... Risk is also data science challengeRisk is also data science challenge
- 67. But I don't work for a corporationBut I don't work for a corporation DatacanbeusedforNGOstoo...
- 68. Data can be used for NGO'sData can be used for NGO's Thisisawebappofhousepricesandcommutes,doneforanNGO inLondonwhowantedtoshowtheeffectsof changesinhousepricesonpeoplescommutes.
- 69. Reducing Maternal Mortality Rates in MexicoReducing Maternal Mortality Rates in Mexico --Mexico - Presidencia de la RepublicaMexico - Presidencia de la Republica ThematernaldeathsinMexicofrompregnancy,childbirthor postpartumcomplicationshavedecreasedfrom89deathsper 100,000livebirthsin1990to43in2011.Despitethis improvement,therateofdeclinehassignificantlyslowedand MexicoisnotontracktoachieveitsMillenniumDevelopment Goalofreducingmaternalmortality75%by2015.
- 70. But what if you're in Politics?But what if you're in Politics?
- 71. Earlier I showed how data canEarlier I showed how data can even predict 49 out of 50 stateseven predict 49 out of 50 states in the last American election.in the last American election. AndthatObamawouldbethepresident!
- 72. 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...
- 73. Does this sound like you?Does this sound like you? Are you not taking full advantage of your reporting?Are you not taking full advantage of your reporting? Do you need a high level visual overview of yourDo you need a high level visual overview of your operations?operations? Are you targeting your marketing efforts effectively byAre you targeting your marketing efforts effectively by using the right customer segmentation - by age orusing the right customer segmentation - by age or gender for example?gender for example?
- 74. Or this?Or this? 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?
- 75. Example: What-if analysis...Example: What-if analysis...
- 76. What about communication?What about communication? Mathematicallysoundcommunicationtoclients:youmayhave situationswhereyouneedthedatascientiststotalkdirectlyto clientsortotheirdatascientists. Thisisyetanotherreasontomakesureyouhiresomeonewith excellentcommunicationskills,becausetheywillberepresenting yourbusinesstoreallysmartpeople.
- 77. Data Scientists are like 'translators'Data Scientists are like 'translators' Alotofmyworkatthemomentismathematicalcommunication withexternalstakeholdersandProfessors. AtAmazonalotofmyworkwaswithResearchScientistsin Optimization.Translatingtheirideasforbusinessstakeholders. Ioftenhavetotranslatefromthe'business'tothe'software' team. DoyouhavesomeonelikethatonYOURteam?
- 78. If this sounds familiarIf this sounds familiar then you might needthen you might need to hire a data scientist!to hire a data scientist!
- 79. I hope the examples helpedI hope the examples helped Ihopeitisalsoclearhowdatacanbeusedinwhateverfieldyou workin. Ihopeitisalsoclearthat'bigdata'isnotsomethingtobescared ofbutshouldbepartofyourorganizationsstrategy. Iknowthatdevelopingadata-drivencultureisextremelydifficult.
- 80. Thank You For ListeningThank You For Listening Anyquestions? Reachouttomeifyouhaveanydataquestions. @springcoil SearchPeadarCoyleonLinkedin peadarcoyle@googlemail.com