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BUS 237 Chapter 8 notes

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Department
Business Administration
Course
BUS 237
Professor
Kamal Masri
Semester
Fall

Description
1.) Ackoff’s assumptions a. Managers have no problem with making decisions if they get the data they need (too many possibilities exist) b. Poor decisions are made because managers lack relevant info (contrary: overloaded with info) c. Managers know the data they need (in reality they aren’t sure) 2.) Information overload – overabundance of data; a. managers suffer from this compared to lack of data i. petabytes: 200 petabytes is roughly the amt of all the printed material ever written (growing by 30% a year) ii. 3300 petabytes or 3.3 exabytes by 2010 3.) Data Quality a. Dirty data – problematic (B for gender, 213 for age) b. Missing Values – lacking info c. Inconsistent data – when data is gathered over time and changes will not match d. Granularity – degree summarization or detail i. Coarse data – highly summarized ii. Fine data – details that are too precise (better than too course, can be made courser anyway) 1. Clickstream data – capture customer’s clickage 4.) OLTP – Online Transaction Processing a. collecting data electronically and processing transactions online i. Real Time – if transactions are entered and processed immediately on entry 1. More up to date ii. Batch – waiting for transactions to pile up before you process them 5.) OLAP – Online Analytic Processing a. Data resource challenge – data collected to improve decision making b. DSS – decision support systems or OLAP i. Provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data ii. OLAP cube/ report – some products show data using three axes 1. Generated by OLAP servers...can’t be done by DBMS 2. Used in BI or business intelligence 6.) BI – Business Intelligence (Systems) a. Provides info for improving decision making i. Vary in characteristics and capabilities and foster competitive advantage b. Types i. GDSS s – Group Decision Support Systems – allow multiple parties to participate in decision making and improve outcomes by reducing biases. ii. Reporting Systems – integrate and process data (grouping , summing, formatting, produce, admin, and deliver reports); 1. improve decisions by providing relevant info to the right person iii. Data- Mining systems – Use sophisticated stats techniques to find patterns and relationships; 1. improve decisions by discovering patterns and relationships in data to predict future outcomes a. Market basket analysis – computes correlation of items on past orders to determine items that are frequently purchased together iv. Knowledge Management Systems – Share knowledge of products, product uses, best practices, etc.. 1. Improve decisions by publishing employee and others’ knowledge; 2. create value from existing intellectual capital; 3.
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