Decision Making and Business Intelligence.docx

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Department
Computer Science
Course
Computer Science 1032A/B
Professor
Diane Goldstein
Semester
Winter

Description
Decision Making and Business Intelligence Challenges of Making Decisions  Decision making is a daily occurrence for business managers  Factors making business decisions challenging o Uncertainty and complexity o Information overload o Data quality Information Overload  Storage capacity increases  Cost decreases  Basically unlimited today  Exponential growth o Both inside and outside of organizations o Used to improve decision making  Ability to store any size customer data  Allows for a better understanding of the customers  Data can be used for forecasting  Competitive strength when making decisions  Business manager’s challenge o Find appropriate data o Incorporate this data in decision making  Information systems o Help and hinder Data Quality  Processed data from operational systems can be used for o Basic reports o E.g. – current sales, sales projections  Raw data unsuitable for sophisticated reporting or data mining o Dirty data o Missing values o Inconsistent data o Data not integrated o Wrong granularity – too fine/not fine enough o Too much data – too many attributes/too many data points OLTP – Support for Decision Making  Online Transaction Processing (OLTP) systems o Collects data electronically o Processes the transactions online  Backbone of all functional, cross-functional and Interorganizational systems in an organization  OLTP systems support decision making o Provides raw information about transactions o Provides information about status for an organization Transaction Processing  Real-time processing o Transactions are entered and processed immediately upon entry  E.g. – airline reservation systems, banking systems  Batch processing o Systems waits until it has a batch of transactions before the data are processed and the information is updated  E.g. – transfer of all daily branch transactions to the central office for processing Data Resource Challenge  While data may be collected in OLTP, the data may not be used to improve decision making  Data as an asset? o Asset: resource from which future economic benefits may be obtained o How is data valued at an organization? o Who manages it? o Where is the data? o Need to treat data as an important resource OLAP – Online Analytic Processing  Focus on making OLTP-collected data useful for decision making  Provides the ability to sum, count, average and perform other simple arithmetic operations of groups of data  Report has measures or facts and dimensions Business Information (BI) Systems  Provide information for improving decision making  Primary systems o Reporting system  Integrate data from multiple sources  Process data  Sorting  Grouping  Summing  Averaging  Comparing  Results formatted into reports  Improve decision making by providing the right information to the right user that the right time o Data-mining systems  Process data using statistical techniques  Regression analysis  Decision tree analysis  Look for patterns and relationships to anticipate events or predict outcomes  Market-basket analysis  Predict donations  Application of statistical techniques to find pattern and relationships among data  Represents convergence of disciplines  Takes advantage of developments in data management to process
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