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Description
Flashcards by Adriana Vincelli-Joma, updated more than 1 year ago
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Created by Adriana Vincelli-Joma
almost 5 years ago
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| Question | Answer |
| Decision making challenges | 1. concept of rationality is hard to define 2. good outcomes result from irrational processes; bad outcomes result from good processes 3. limit in cognitive capabilities 4. uncertainty and complexity 5. info. overload 6. data quality |
| OLTP vs OLAP | Online Transaction Processing (OLTP): -collects data electronically and process transaction online -backbone of all functional, cross-functional and inter-organizational systems in organization -provides raw info about transactions and status to support decision-making Online Analytic Processing (OLAP): -focus on making OLTP collected data useful for decision making -provides ability to sum, count, average, and perform other simple arithmetic operations on groups of data -report has measures, or facts and dimensions |
| What is a data resource challenge? | -data are collected in OLTP but are not used to improve decision making |
| What is a business intelligence system? How do they provide competitive advantage? | business intelligence (BI) system: provides info for improving decision making -group decision support systems: reduce biases inherent in group discussion and option evaluation -reporting systems: provide relevant, accurate, and timely info to right person -data-mining systems: discover patterns and relationships in data to predict future outcomes -knowledge management systems: publish employee and others' knowledge; create value from existing intellectual capital; foster innovation, improve customer service, increase organizational responsiveness, and reduce costs -expert systems: encode saving, and processing expert knowledge |
| What are the purpose and components of a data warehouse? | Purpose: extract and clean data from operational systems and other sources Components: -operational databases -other internal data -external data -data extraction/cleaning/preparation programs -data warehouse metadata -data warehouse database -data-warehouse DBMS -business intelligence tools |
| What is a data mart and how is it different than a data warehouse? | -database that prepares, stores, and manages data for reporting and data mining for specific business functions -created to address particular needs -smaller than data warehouse -address particular component of function area of business -users may not have data management expertise |
| Types of data-mining applications | -unsupervised data mining: analysts do not create model or hypothesis before running analysis *cluster analysis: identify groups of entities that have similar characteristics -supervised data mining: model developed before analysis; statistical techniques applied to data *regression analysis: measures impact set of variables on another variable * neural networks: predict values and make classifications such as "good/poor prospect" customers |
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