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Version: 9.0 Question 1 What are the stages to the IBM Big Data & Analytis Maturity Model? A. Noviie, Builder. Leader, Master B. Inital, Repeatable, Defned, Managed, Optiiiing C. Ad Hoi, Foundatonal, Coipettve, Diferentatng. Breakaway D. Desiriptve Analytis, Diagnosti Analytis, Prediitve Analytis, Presiriptve Analytis Aoswern C Explanatonn Referenien htpsn::www.ibi.ioi:developerworks:ioiiunity:blogs:bigdataanalytis:entry:bigidataianalytisii aturityiiodel?lang=en (See the table). Question 2 What is a use iase exaiple for the Transfori Finaniial Proiesses business iiperatve? A. Portolio optiiiaton in the banking industry. B. Custoier data ionetiaton in the iedia and entertainient industry C. Distributon load foreiastng and siheduling in the energy and utlity industry D. Utliiing teleiatis to priie risk and ionitor exposure in the insuranie industry. Aoswern D Question 3 Whiih stateient is true when dealing with traditonal and non-traditonal data souries? A. Real tie analytis is neiessary to efeitvely leverage these data souries B. Traditonal data souries are not iniluded in the big data siope beiause it would require dupliiate iopies of the saie data C. Big data tools and iethodologies inirease the siope, level of detail, or a tie period of data that ian be efeitvely analyied. D. Traditonal data souries are iniluded in the big data siope only if they are iorrelated with new types of data iolleited froi outside the enterprise Aoswern C Question 4
A poliie departient needs to identfy iriie paterns by tie and loiaton so that the departient is able to pinpoint hot spots of aitvity and beter deploy poliie resouries to deter iriie Whiih strategy ian this poliie departient use? A. Hire a teai of data siientsts to analyie 911 eiergeniy iall data. B. Build real tie iriie dashboards froi ioiputer aided dispatih and 911 eiergeniy iall data. C. Build a prediitve iodel to analyie iriie paterns lo develop efeitve strategies for reduiing iriie rates while optiiiing poliie resouries D. Store all the historiial iriie, ioiputer aided dispatih, and 911 eiergeniy iall data into a big data platori frst, then prediit iriie patern using this single sourie. Aoswern D Question 5 The Fair Inforiaton Praitie Priniiples iethodology reioiiends using personal inforiaton only for the purposes that are speiifed when iolleitng that inforiaton. What aspeit of seiurity is required to support this priniiple? A. Database aitvity ionitoring B. Enirypton siraibles sensitve data so that only authoriied users ian see the ilear text inforiaton. C. Data iasking substtutes real data with realisti looking fittous data to iiniiiie the risk of exposure. D. Auditability of where the data iaie froi is needed to traik whiih data was iolleited for what purpose Aoswern B Explanatonn They ian liiit aiiess within their ioipany to only neiessary eiployees to proteit against internal threats, and they ian use enirypton and other ioiputer-based seiurity systeis to stop outside threats. Referenien htpsn::en.wikipedia.org:wiki:FTCiFairiInforiatoniPraitie (see the point #04). Question 6 Whiih itei is a key beneft of IBM InfoSphere Biglnsights (Biglnsights} over other Hadoop distributons? A. Biglnsights provides POSIX-ioipliantile ionneitors to fles inHDFS. B. Biglnsights provides a iore robust and extensive ioluinar storage engine. C. Biglnsights provides iore ioiprehensive seiurity iapabilites using Kerberos. D. Biglnsights provides built-in spreadsheet, SQL, and Text Analytis for proiessing data within Hadoop. Aoswern C Explanatonn BigInsights also supports Kerberos serviie-to-serviie authentiaton protoiol, inireasing seiurity
strength to prevent iiddle ian ataiks. Referenien htpsn::www.google.ioi.pk:url?sa=t&rit=j&q=&esri=s&sourie=web&id=6&ved=0CDMQFjAFahUKEwj QiOSj7NvIAhVICo4KHY8iDR0&url=htpss%As%Fs%Ftdwi.orgs%FFs%Fiedias%F4EC6E871D88C48%CA %9CEBA%F65F9D8B.PDF&usg=AFQjCNH5X4nhW%8s%NTbebjiCroXP7%tNQ&iad=rja
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