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Chapter 8

MIS Chapter 8 Decision Making and Business Intelligence.docx

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Simon Fraser University
Business Administration
BUS 237
Zorana Svedic

Bus 237 Management Information Systems Chapter 8 Chapter 8: Decision Making and Business Intelligence Information overload An overabundance of irrelevant data Petabytes 10 bytes Exabytes 10 bytes Dirty data Problematic data. Examples are a value of B for customer gender and a value of 213 for customer age. Other examples are a value of 999-999- 9999 for a North American phone number, a part colour of green, and an email address [email protected] All these values are problematic when data mining Granularity The level of detail in data. Customer name and account balance is large granularity data. Customer name, balance and the order details and payment history of every customer order is smaller granularity Clickstream data E-commerce data that describe a customer’s clicking behaviour. Such data include everything the customer does at the website Online transaction processing (OLTP) Collecting data electronically and processing transactions online Data resource challenge Occurs when data are collected in OLTP but are not used to improve decision making Decision support systems (DSSs) Systems that focus on making data collected in OLTP useful for decision making Online analytic processing (OLAP) A dynamic type of reporting system that provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data. Such reports are dynamic because users can change the format of the reports while viewing them Drill down With an OLAP report, to further divide the data into more detail Business intelligence (BI) system A system that provides the right info to the right user at the right time. A tool produces the info but the system ensures that the right info is delivered to the right user at the right time Group decision support systems An application that enables more than one individual to (GDSSs) undertake a decision. Often includes voting and brain-storming functions Reporting systems Systems that create info from disparate data sources and deliver that info to the proper users on a timely basis Data-mining systems IS that processes data using sophisticated statistical techniques, such as regression analysis and decision-tree analysis to find patterns and relationships that cannot be found by simpler operations, such as sorting, gro
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