MIS 301 Final Exam Study Guide.docx

MIS 301 Final Exam Study Guide.docx - Final Exam Study...

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Final Exam Study Guide Business Intelligence (Course slides and Air France Case) Why has Business Intelligence become so popular? Walmart’s Info Systems Within 15 seconds of a purchase, customer purchase data is sent to the Wal-Mart data center Wal-Mart uses this data to track sales, replenish inventory, and communicate with over 100,000 vendors What do people stock up on when a hurricane is imminent? Water, beer, and pop tarts Data Sources Tracked transac±ons à increased insights à increased sales External sources o Partners: Manufacturer à Retailer à Customer o Data aggregators (Frms that collect and resell data) 3 V’s o Volume – The amount of data that we are crea±ng as companies and individuals has increased greatly o Variety – ²ormat and types of data di³er greatly (e.g. Business, Social, Pics, IOT) o Velocity – New data is being created every millisecond in our world (e.g. Stock Market, Your phone’s sta±s±cs alone!) Data Warehouses Lots of data exist in old legacy systems ²or companies to take advantage of data, informa±on must be accessible Data WH is a large-database repository that consolidates silo’ed data. Business Intelligence (BI) Systems Provide informa±on for improving decision making Primary systems: Repor±ng systems Data-mining systems Knowledge management systems Expert systems Business intelligence systems use data created by other systems to provide repor±ng and analysis for organiza±onal decision making The ability to pull data from across an organiza±on and make decisions is key to business success. Value of BI tool Analyze data Look for pa´erns Use pa´erns to make business decisions Declining cost of compu±ng Declining cost of storage Increasing interconnec±vity of devices and systems More data and informa±on available to businesses Results of data analyses could be used to generate and sustain compe±±ve advantage
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Share informaton wiTh business parTners EX: Manage invenTory Make seasonal or regional buying decisions Drop iTems from invenTory EX: Design marketng and advertsing sTraTegies around Trends (Back To School) Reportng SysTems InTegraTe daTa from multple sources Process daTa by sortng, grouping, summing, averaging, and comparing ResulTs forma±ed inTo reporTs Improve decision making by providing righT informaton To righT user aT righT tme DaTa Mining: Non-Trivial discovery of novel, valid, comprehensible and poTentally useful pa±erns from daTa DaTa Mining SysTems Process daTa using sTatstcal Techniques Decision Tree analysis ClusTering Associaton Rules Descriptve & Predictve Look for pa±erns and relatonships To antcipaTe evenTs or predicT ouTcomes MarkeT-baskeT analysis PredicT donatons DaTa Mining ²echniques Data mining: ²he auTomaTed search in large daTabases for non-obvious paTerns and relatonships To an±cipate evenTs or predict ouTcomes Four classes of Techniques:
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MIS 301 Final Exam Study Guide.docx - Final Exam Study...

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