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Old March 29th, 2016, 12:27 PM
Default Management Information System Notes for MBA

Can you provide me the Notes or Study Material for Database Management System of Management Information System for preparation of MBA (Master in Business Administration) course?
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Old March 29th, 2016, 12:43 PM
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Join Date: Nov 2011
Default Re: Management Information System Notes for MBA

The Notes or Study Material for Database Management System of Management Information System for preparation of MBA (Master in Business Administration) course are as follows:

Data Warehousing

Advantages of Data Warehouse

A data warehouse provides a common data model for all data of interest regardless of the data’s source. This makes it easier to report and analyze information than it would be it multiple data models where used to retrieve information such as sales invoices order receipts, general ledger charger, etc.

Prior to loading data into the data warehouse, inconsistence are identified and resolved. This greatly simplifies reporting and analysis.

Information in the data warehousing is under the control of data warehouse users so that even if the source system data is purged over time, the information in the warehouse can be stored safely for extended period of time. Data warehousing can work operational system, data warehousing provide retrieval of data without slowing down operational system.

Data warehouse facilitate decision support system applications such as trends report ( e.g the items with the most sales in a particular area within the last two years),exception reports that show actual performance versus goals, consolidated /standardized comprehensive, rapidly available information.

Features of Data Mining

i) Provides insight into hidden patterns and relationships in your data.
A classic example of data mining is a retailer who uncovers a relationship between sales of diapers and beer on Sunday afternoons- two items you wouldn’t normally consider as linked. The explanation is that husbands who are sent out to pick up a fresh supply of diapers are also likely to pick up some beer while they happen to be in the store – something that hadn’t been recognized as a significant sales driver before data mining uncovered it.

ii) Enables you to exploit these correlations to improve organizational performance.
Continuing the example above, very often retailers act on the relationships they discover by using tactics such as placing linked items together on end-of-isle displays as a way to spur additional purchases. All organizations can benefit from acting in a similar way – using newly discovered patterns and correlations as the basis for taking action to improve their efficiency and effectiveness.

iii) Provides indicators of future performance.
“Those who do not learn from history are doomed to repeat it” is a famous quote from philosopher George Santayana. In the case of data mining, being able to predict outcomes based on historic data can dramatically improve the quality and outcomes of decision making in the present. As a simple example, if the best indicator of whether a customer will pay on time turns out to be a combination of their market segment and whether or not they have paid previous bills on time, then this information you can usefully benefit from in making current credit decisions.

Advantages of Data Mining

Marketing / retailing
Data mining can aid direct marketers by providing them with useful and accurate trends about their customer’s purchasing behavior. Based on these trends, marketers can direct their marketing attentions to their customers with more precision. For example, marketers of a software company may advertise about their new software to consumers who have a lot of software purchasing history. In addition, data mining may also help marketers in predicting which products their customers may be interested in buying. Through this prediction, marketers can surprise their customers and make the customer's shopping experience a pleasant one.

Retail stores can also benefit from data mining in similar ways. For example, through the trends provided by data mining, the store managers can arrange shelves, stock certain items, or provide a certain discount that will attract their customers.

Banking / crediting
Data mining can assist financial institution in areas such as credit reporting and loan information for example, by examining previous customers with similar attributes, a bank can estimate the level of risk associated with each given loan. In addition,data mining can also assist credit cards issuers in detecting potentially fraudulent credit card transaction. Although the data mining technique is not 100% accurate in its prediction about fraudulent charges, it does help the credit card issuers reduce their losses.

Law enforcement
Data mining can aid law enforcers in identifying criminal suspects as well as apprehending these criminal by examining trends in location, crime type, habit, and other patterns of behaviors.

Data mining can assist researchers by speeding up their data analyzing process thus, allowing them more time to work on other projects.
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