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ARM 401 – 4 Exam Questions with Correct Answers.
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ARM 401 – 4 Exam Questions with Correct Answersv v v v v v v v
Big vData v- vAnswer v- v v vSets vof vdata vthat vare vtoo vlarge vto vbe vgathered vand vanalyzed vby
vtraditional vmethods.
Data vGovernance v- vAnswer v- v v vIs va vframework vof vrules, vstandards vand vdecisions vfor vmanaging
vdata. vThe vprogram vset vstandards vand voversee vthe vmanagement vof va vfirm's vdata vassets vin vorder
vto vmeet vquality vstandards vand vto vprevent vabuse.
Five vCharacteristics vof vBig vData v- vAnswer v- v v v1. vVolume
2. vVariety
3. vVelocity
4. vVeracity
5. vValue
Sources vof vBig vData v- vAnswer v- v v vInternal vdata v- vOwned, vcaptured vand vstored vby van
vorganization.
External vdata v- vBelongs vto van ventity vother vthan vthe ventity vthat vwishes vto vuse vit.
Internal vData v- vAnswer v- v v vData vowned vby vthe ventity vthat vuses vit.
External vData v- vAnswer v- v v vBelongs vto van ventity vother vthan vthe ventity vthat vwishes vto vuse vit.
Structured vData v- vAnswer v- v v vIs vdata vorganized vinto vdatabases
with vdefined vfields vand vlinks vbetween vand vamong
databases.
Unstructured vData v- vAnswer v- v v vIs vdata vthat vis vnot vorganized vand
that voften vconsists vof vtext, vimages, vand vnontraditional vmedia.
Third-party vdata vincludes v- vAnswer v- v v vGeo-demographic vdata v(classification vof vpopulation),
veconomic vdata v(interest vrates, vassets vprices, vexchange vrates vand vconsumer vpricing vindex) vand
vcredit vrating
, Economic vdata. v- vAnswer v- v v vIncludes vinterest vrates, vasset vprices, vexchange vrates, vand vthe
vconsumer vprice vindex
Geodemographic vdata v- vAnswer v- v v vRegards vclassifications vof vpopulation vgroups.
Big vData vCategories v- vAnswer v- v v v1. vExternal vand vstructured v- vtelematics, vfinancial vdata, vlabor
vstatistics.
2. vExternal vand vunstructured v- vSocial vmedia, vnew vreports vand vinternet vvideos.
3. vInternal vand vStructured v- vPolicy vinformation, vclaims vhistory vand vcustomer vdata.
4. vInternal vand vunstructured v- vAdjusters vnotes, vcustomer vvoice vrecordings vand vsurveillance
vvideos.
Predictive vModeling v- vAnswer v- v v vUses va vdefined vtarget vvariable vto vpredict vor vestimate van
vunknown voutcome. vUsed vto vpredict vfuture vvalues vand vestimate vunknown vpast vor vpresent
vvalues.
Target vVariable v- vAnswer v- v v vIs vthe vattribute vwhose vvalue vis vbeing vpredicted vin va vdata
vanalytical vmodel.
Seven vSteps vin vBuilding va vPredictive vModel v- vAnswer v- v v v1. vGather vhistoric vdata.
2. vDivide vdate vinto vtraining vdata vand vholdout vdata.
3. vBuild vthe vmodel vusing vthe vtraining vdata.
4. vApply vthe vmodel vusing vthe vtraining vdata.
5. vUse vperformance vmetrics vto vevaluate vthe vmodel.
6. vUse vfeedback vto vadjust vthe vmodel, vrepeating vSteps v3, v4 vand v5 vas vneeded.
7. vPut vthe vmodel vinto vproduction vand vreevaluate vas vneeded.
Training va vPredictive vModel v- vAnswer v- v v vUsing vexisting vdata vto vcreate vpredictive vmodels vthat
vhelp vthem vanticipate vbehaviors.
Training vData v- vAnswer v- v v vData vthat vis vused vto vtrain va vpredictive vmodel vand vthat vtherefore
vmust vhave vknown vvalues vfor vthe vtarget vvariable vof vthe vmodel.
Overfitting v- vAnswer v- v v vOccurs vwhen vthe vmodel vis vso vclosely vtailored vto vthe vtraining vdata vthat
vit vis vnot veffective von vother, vnew vdata.
Holdout vData v- vAnswer v- v v vExisting vdata vwith va vknown vtarget vvariable vthat vis vheld vback vand
vnot vused vas vpart vof vthe vtraining vdata. vThe vdata vis vused vto vtest vthe vmodel vto vmake vsure vthat
vit vperforms vwell von vknown vdata.
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