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IT211101 Handout 1*Property of STI[email protected]Page 1 of 4OVERVIEW OF BIG DATA AND BUSINESS ANALYTICSIn the era of knowledge economy, getting the right information todecision makers at the right time is critical to their business success,and one such attempt includes the growing use of business analytics(Min, 2017). Business analytics is one of the most talked-about topicsin the field of business and information technology. And as expected,business analytics is becoming one of the most sought-after coursesin the academe.Business Analytics (BA)Below are some of the definitions of business analytics:Business analytics is comprised of solutions used to build analysismodels and simulations to create scenarios, understand realitiesand predict future states including data mining, predictiveanalytics,appliedanalytics,andstatistics).Business Analytics is the study of data through statistical andoperationsanalysis,theformationofpredictivemodels,application of optimization techniques, and the communication ofthese results to customers, business partners, and collegeexecutives (Galleto, 2018).Business analytics refers to a broad use of various quantitativetechniques such as statistics, data mining, optimization tools, andsimulation supported by the query and reporting mechanism toassist decision makers in making more informed decisions withinaclosed-loopframeworkseekingcontinuousprocessimprovement through monitoring and learning (Min, 2017).Here are the definitions of Business Intelligence (BI):Business Intelligence is the process of collecting informationfrom all sources to make data-driven decisions in an organization(Galleto, 2018).Business Intelligence is the process of combining aspects ofreporting, monitoring, and alerting, dashboards,scorecards,andad hoc query data exploration (Galleto, 2018).Challenges with Business AnalyticsPenn State University’s John Jordan described thechallenges withBusiness Analytics: there is “a greater potential for privacy invasion,greater financial exposure in fast-moving markets, greater potential formistaking noise for true insight, and a greater risk of spending lots ofmoneyandtimechasingpoorlydefinedproblemsoropportunities.”Other challenges with developing and implementingBusiness Analytics include:Executive OwnershipBusiness Analytics requires buy-infrom senior leadership and a clear corporate strategy forintegrating predictive modelsIT InvolvementTechnology infrastructure and tools must beable to handle the data and Business Analytics processesAvailable Production Data vs. Cleansed Modeling DataWatch for technology infrastructure that restricts availabledata for historical modeling, and know the difference betweenhistorical data for model development and real-time data inproductionProject Management Office (PMO)The correct projectmanagement structure must be in place in order to implement

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