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Implementation of data mining in after sales - parts in an automotive manufacturer and distributor company

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DaimlerChrysler is one of major automotive company in Indonesia. To improve their Inventory Information System, they have to increase their efficiency and effectiveness in maintaining the cycle of parts in their inventory, especially in their Planning Decision System and Forecasting future needs. There are several ways to acquire this goal; one of it is with data mining which is able to make a prediction using existing data in their database in order to forecast future demand to enhanced order for parts procurement. In Addition, with data mining they would be able to determine which part is more important and is need to be prepared every month comparing to other parts. rnThis thesis will give the initial concept about data mining model that most likely will be used in Sales and Marketing Department - After Sales Department. The initial concept will cover:rn- The appropriate data warehouse schemarn- Data mining tasks and techniques that is best to use in this modelrn- The suitable type of OLAP according to data warehouse schemarnAlso the Implementation of the initial concept will be covered in this thesis. Expectantly, this thesis will give DaimlerChrysler an initial point to build their data mining model before applying data mining in their system.

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Availability

B00061

(wh)

Available

Detail Information

Series Title

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Call Number

61

Publisher

: Swiss German University., 2005

Collation

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Language

English

ISBN/ISSN

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Classification

NONE

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Business intelligence
Data mining
IT
Data warehousing

Specific Detail Info

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Statement of Responsibility

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