yves studer: big data in practice

Towards(a(procedure(model(for(Big(Data(

Costa(&(Oliveira((2012)(

((((((((((((((((((((((Big(Data(in(Prac@ce(

04th(of(February(2014(|(Yves(Studer(

#1 You are able to identify common hurdles when doing Big Data.

#2 You know some strategies and a procedure model to

overcome these.

Big(Data:(Agenda(

1.  Why?(Mo@va@on(&(perspec@ves(on(Data(in(an(enterprise(

2.  What?(Short(overview(of(challenges(

3.  How?(An(example(of(a(procedure(model(

7’#

5’#

2’#

?!(

Why? Your Motivation

?(?(

New Paradigm: Big data streaming into an enterprise means(not(just(to(capture(and(store(data(but(to(put(it(into(the(hands(of(end users.

Aberdeen(Group((2012)(

Extend(the(territory(

Dig(deeper(into(the(current(pool(

Analyse(dead(storage(

Explore(the(black(hole(

Internal(

which(can(already(be(used(Data(

exists(but(yet(unused(

not(yet(collected(

External(Linking(internal(and(external(informa@on(

Based(on(Arthur(D.(LiXle((2013)(

External((Data(

Insurance(Sector(Example(

What(type(of(Big(Data(to(exploit?(

Edward&Vandenberg,&Farmers&Insurance’s&Director&of&Advanced&Analy=cs&in&Whi=ng&(2013)&

Why(external(data?(

Insurance(is(a(predic@on(business:((

“If(a(predic@on(model(is(only(4(to(5(percent(beXer(than(a(naïve(predic@on,(but(new,(external(data(can(help(improve(that(by(a(couple(of(points(across(millions(of(transac@ons,(that’s(huge.”(


It(is(said(to(be(worth(the(trouble(

! (2.5(@mes(stock(apprecia@on.((! (2(@mes(larger(EBITDA(growth.((! (1.6(@mes(higher(revenue(growth.(

IBM&&&The&Economist&(2012)&&

Whi=ng&(2013)&

Analy@cal(advantages((of(external(Data(

•  BeXer(understanding(of(customer(habits(/(risks(•  Effec@ve(marke-ng:(judge(customer(reac@ons(•  Improved(tracking(of(insurance(markets(and(the(overall1business1health1

•  Development(of(new1products1and(programs(to(capitalize(on(market(changes.(

•  BeXer(fraud(detec-on1


YOUR1CHALLENGES1

What? Your Challenges

Whi@ng((2013)(

Challenges(

•  New(data(choices(•  Privacy(concerns(•  Time(delays(•  Increasing(data(volume:(Volumeecapable(Infrastructure(

•  Innova@on:(Cultural(Shif(•  Gegng(the(external(data(before(the(project(•  Human(Bias(


Selected(Challenges(

Challenge 1: Value Issues

Challenge 2:

Legal Issues

Challenge 1: Value Issues

D.(LiXle((2012)(

Where(Big(Data(creates(Value(

Based(on(survey(by(Aberdeen(Group((2012)(

Data(analysis(not(detailed(enough(#1(

Data(inaccessible(/(underused(#2(

End(users(gegng(data(not(fast(enough(#3(

Data$too$fragmented$/$‘siloed’$not$ac4onable

#4(

Transla@ng(Big(Data(into(Value(

Schmarzo((2013)(

#1(#2(#3(#4(

What(to(do?((I)(

!  Iden@fy(key(business(ini@a@ves(

!  Business(&(IT(stakeholder(collabora@on(

!  Formalise(the(“envisioning(process”(

!  Use(Prototpyes(

Schmarzo((2013)(

What(to(do?((II)(

!  Understand(technology(&(architectural(op@ons(

(!  Uncover(new(mone@sa@on(possibilites((!  Understand(the(organisa@onal(

implica@ons(

Schmarzo((2013)(

Challenge 2: Legal Issues

legal rules collide with technological and business realities

Tene(&(Polonetsky((2012)(

Selected(Legal(Issues(

• Obsolete(Concept(“Personally(Iden@fiable(Informa@on”((PII)?(•  Data(Minimisa@on(and(Big(Data?(

Old(Roots(of(Privacy(Guidelines(

Organisa@on(for(Economic(Coeopera@on(and(Development((2013)(

Closed(Networks(

1(Actor(((“Data(Controller”)(

Limited(numbers(of(Sources(

Limited(numbers(of(Sources(

What(is(PII?(

•  Defini-on:1“any(informa@on(rela@ng(to(an(iden@fied(or(iden@fiable(individual”.(

Any(data(that(are(not1related1to(an(iden@fied(or(iden@fiable(individual(are(therefore(nonepersonal(and(are(outside1the1scope1of1the1Guidelines.(


“Nice,(if(we(anonymise(it(is(no(PII!”(“Tradi@onally,(deGiden-fica-on1was(viewed(as(a(silver(bullet(allowing(organisa@ons(to(reap(the(benefits(of(analy@cs(while(preserving(individuals’(privacy.((


Well,(boss…(

([…](computer(scien@sts(have(repeatedly(shown(that(even(anonymised(data(can(typically(

be(reeiden@fied(and(associated(with(specific(individuals.”((( Tene(&(Polonetsky((2012)(

Solu@on?(

(“Treat(all(data(as(PII(or(you(play(whackeaemole”(

Paul(Ohm((2012)(from(University(of(Colorado(Law(School(

Data(Minimisa@on(

•  Organisa@ons(are(required(to(–  limit1the1collec-on1of1personal1data1to(the(minimum(extent(necessary(to(obtain(their(legi@mate(goals.((

– delete1old1data1that(is(no(longer(required(


Solu@on?(

•  In(a(big(data(world,(the(principle(of(data(minimiza@on(should(be(interpreted1differently1–  requiring(organiza@ons(to(deeiden@fy(data,(–  implement(reasonable(security(measures,(–  limit(uses(of(data(for(acceptable(purposes((individual(&(societal(view).(


What’s(next?(

•  The(EU(Data(Protec@on(Direc@ve(is(being(finalised(by(this(year*((

•  The(OECD(currently(assesses((– employment(impact(of(dataedriven(automa-on,(–  issues(related(to(compe@@on(– and(intellectual1property(rights.(

(*(Some(vivid(discussions(are(currently(going(on,((follow(#EUDataP(on(TwiXer(

How? A Procedure Model

1(

2(

3(

The(Big(Data(Procedure(Model(

BITKOM((2012)(

1(

2(

3(

4(

5(

6(

7(

8(

Maturity(Assessment(

Prepara@on(of(IT(

Implementa@on(

Consolida@on(&(Migra@on(

Exploita@on(of(new(Data(Repor@ng(&(Predic@ve(Analy@cs(

True(endetoeend(integra@on(

Con@nuous(Improvement(

Phase(1:(Maturity(Assessment(

BITKOM((2012)(

1(Maturity(Assessment(

51

41

31

21

11

01

BusinesseOp@misa@on(

Some(Processes(op@mised(

Some(Project(in(endephase(

Some(Projects(started(

Some(Concepts(&(PoC(

Inexistent(

Op@misa@on(

Applica@on(

Strategy(

Centre(of(Excellence(

Big(Data(Ini@a@ves(

Legacy(Applica@ons(

Phase(2:(Prepare(IT(for(Big(Data(

BITKOM((2012)(

1(

2(


Prepara@on(of(IT(

(ITegoals(

GapeAnalysis((

Phase(3:(Implementa@on(

BITKOM((2012)(

1(

2(

3(


Prepara@on(of(IT(

Implementa@on(

(Integra@on(into(exis@ng(ITelandscape(

Consider(CloudeSolu@ons((

Cultural(Issue:(ParadigmeShif(

based(on(Hoge((2012)(

?Tradi-onal1 Big1Data1

?

IT(enables((cloud)(plauorm(for(discovery(

Business(Units(discover(informa@on(in(data(

Business(Unit(defines(ques@ons(

IT(structures(data(to(answer(the(ques@ons(

Phase(4:(Consolida@on(&(Migra@on(

BITKOM((2012)(

1(

2(

3(

4(


Prepara@on(of(IT(

Implementa@on(


(Op@misa@on(of(exis@ng(infrastructure?(

New(data(sources?((

Ownership(of(Data!((

Phase(5:(Exploita@on(of(new(Data(

BITKOM((2012)(

1(

2(

3(

4(

5(


Prepara@on(of(IT(

Implementa@on(


Exploita@on(of(new(Data(

Phase(6:(Repor@ng(&(Predic@ve(Analy@cs(

BITKOM((2012)(

1(

2(

3(

4(

5(

6(


Prepara@on(of(IT(

Implementa@on(



Phase(7:(Endetoeend(Integra@on(

BITKOM((2012)(

1(

2(

3(

4(

5(

6(

7(


Prepara@on(of(IT(

Implementa@on(




Phase(8:(Con@nuous(Improvement((

BITKOM((2012)(

1(

2(

3(

4(

5(

6(

7(

8(


Prepara@on(of(IT(

Implementa@on(




Con@nuous(Improvement(

Key(Takeaways(

•  (External)(Big(Data(can(create(a(compe@@ve(advantage(

•  To(achieve(it,(many(issues(have(to(be(considered.(Our(focus(today(was(on:(– Finding(the(business(value(– An@cipa@ng(legal(changes(

•  Procedure(models(allow(to(tackle(the(Big(Data(challenges(step(by(step.(

We(can(do(it.(

Bibliographic,References,,,AberdeenGroup,,2012.,In#memory)Compu-ng :)Li2ing)the)Burden)of)Big)Data)Two)Birds)with)One)

Stone.)Available,at:,h?p://spoAire.Bbco.com/~/media/contentEcenter/arBcles/aberdeenEinEmemoryEanalyBcsEforEbigEdata.pdf,[Accessed,January,4th,,2014].,

BITKOM,,2012.,Management,von,BigEData,Projekten.,Available,at:,h?p://www.bitkom.org/files/documents/LF_big_data2013_web.pdf,[Accessed,January,4th,,2014].,

BoozAllenHamilton,,2012.,Harnessing,Big,Data,to,Solve,Complex,Problems:,The,Cloud,AnalyBcs,Reference,Architecture.,Available,at:,h?p://www.boozallen.com/media/file/theEcloudEanalyBcsEreferenceEarchitectureEvp.pdf,[Accessed,January,4th,,2014].,

Davenport,,T.H.,&,Harris,,J.G.,,2007.,Compe-ng)on)Analy-cs:)The)new)Science)of)Winning,(eBook).,,Boston,,Massachuse?s:,Harvard,Business,School,Publishing.,Available,at:,h?p://www.amazon.com,[Accessed,November,28,,2013].,

Davenport,,T.H.,,2012.,Enterprise)Analy-cs:)Op-mize)Performance,)Process,)and)Decisions)Through)Big)Data,(eBook).,,New,Jersey:,FT,Press.,Available,at:,h?p://www.amazon.com,[Accessed,November,28,,2013].,

,

Bibliographic,References,Hoge,,W.,,Big,Value,from,Big,Data.,,,pp.1–19.,Available,at:,h?p://www.slideshare.net/

WilfriedHoge/ibmEbigEvalueEfromEbigEdata,[Accessed,January,5,,2014].,IBM,Center,for,Applied,Insights,,2012.,Outperforming,in,a,dataErich,,hyperEconnected,world.,

Available,at:,h?p://wwwE01.ibm.com/common/ssi/cgiEbin/ssialias?htmlfid=YTE03002USEN&appname=wwwsearch,[Accessed,January,16,,2014],

Lee,,E.,,2013.,Insurers,Tame,the,Challenge,of,Data,Through,Context.,PropertyCasualty360.,Available,at:,h?p://www.propertycasualty360.com/2013/01/31/insurersEtameEtheEchallengeEofEdataEthroughEcontex?t=analyBcsEdata,[Accessed,January,28,,2014].,

Paul,M.,Schwartz,&,Daniel,J.,Solove,,The,PII,Problem:,Privacy,and,a,New,Concept,of,Personally,IdenBfiable,InformaBon,,86,NYU,L.,REV.,1814,(2011),

Tene,,O.,&,Polonetsky,,J.,,2012.,Big,Data,for,All:,Privacy,and,User,Control,in,the,Age,of,AnalyBcs.,Northwestern)Journal)of)Technology)and)Intellectual)Property,,11(5).,Available,at:,h?p://papers.ssrn.com/sol3/papers.cfm?abstract_id=2149364,[Accessed,January,30,,2014].,

Tene,,O.,,2012.,The,ComplexiBes,of,Defining,PersonalData:,AnonymizaBon,,8,DATA,PROT.,L.,&,POLICY,8,,6.,

Image,Sources,Penguins,E,h?ps://www.kernel.org/pub/linux/kernel/people/paulmck/Confessions/

Elephant_Team_03.jpg,Elephant,in,rage,E,h?p://www.snidelyworld.com/Humor/Photos/ElephantRage.jpg,Money,elephant,E,h?p://goclom.net/origamiEpapier/origamiEelephantEfacile.aspx,Elephant,parade,E,h?p://www.viralread.com/wpEcontent/uploads/2013/04/circusEelephants.jpg,

Water,&,hands,E,h?p://flickr.com/dinabenne?,Stones,E,h?p://flickr.com/arztsamui,Wall,E,h?p://flickr.com/rudolfvlcek,Dashboard,E,h?p://flickr.com/sashaLah,Silos,E,h?p://flickr.com/davidvernon,

,All,accessed,at,20th,of,January,2014,,

yves studer: big data in practice

Technology

ons schmarzo2013challenge

ngtoan iden

edor iden

legal issueschallenge

legal rules

value issueschallenge

big data streaming

motivationnew paradigm