Diminishing downsides of data mining

John Wang; Xiaohua Hu; Dan Zhu

doi:10.1504/IJBIDM.2007.013936

Diminishing downsides of data mining

John Wang, Xiaohua Hu, Dan Zhu

Information Management and Business Analytics

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Data Mining (DM) helps deliver tremendous insights for businesses into the problems they face and aids in identifying new opportunities. It further helps businesses to solve more complex problems and make smarter decisions. DM is a potentially powerful tool for companies; however, more research is needed to measure the benefits of DM. This paper represents a study of the effectiveness of DM in a commercial perspective. First, statistical issues are given. It is followed by data accuracy and standardisation. Diverse problems related to the information used for conducting a DM research are identified. Also, the technical challenges and potential roadblocks in an organisation itself are described.

Original language	English
Pages (from-to)	177-196
Number of pages	20
Journal	International Journal of Business Intelligence and Data Mining
Volume	2
Issue number	2
DOIs	https://doi.org/10.1504/IJBIDM.2007.013936
State	Published - 2007

Keywords

DM
Data mining
Disaster planning
Explanatory factors
Monitoring
Organisational issues: statistical issues
Usability

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1504/IJBIDM.2007.013936

Cite this

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title = "Diminishing downsides of data mining",

abstract = "Data Mining (DM) helps deliver tremendous insights for businesses into the problems they face and aids in identifying new opportunities. It further helps businesses to solve more complex problems and make smarter decisions. DM is a potentially powerful tool for companies; however, more research is needed to measure the benefits of DM. This paper represents a study of the effectiveness of DM in a commercial perspective. First, statistical issues are given. It is followed by data accuracy and standardisation. Diverse problems related to the information used for conducting a DM research are identified. Also, the technical challenges and potential roadblocks in an organisation itself are described.",

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AU - Zhu, Dan

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AB - Data Mining (DM) helps deliver tremendous insights for businesses into the problems they face and aids in identifying new opportunities. It further helps businesses to solve more complex problems and make smarter decisions. DM is a potentially powerful tool for companies; however, more research is needed to measure the benefits of DM. This paper represents a study of the effectiveness of DM in a commercial perspective. First, statistical issues are given. It is followed by data accuracy and standardisation. Diverse problems related to the information used for conducting a DM research are identified. Also, the technical challenges and potential roadblocks in an organisation itself are described.

KW - DM

KW - Data mining

KW - Disaster planning

KW - Explanatory factors

KW - Monitoring

KW - Organisational issues: statistical issues

KW - Usability

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EP - 196

JO - International Journal of Business Intelligence and Data Mining

JF - International Journal of Business Intelligence and Data Mining

IS - 2

ER -

Diminishing downsides of data mining

Abstract

Keywords

UN SDGs

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