Actually, data mining has a lot of applications. But, I do not know its applications in business intelligence, organisational management, Business Process Management and etc.
Do you have any idea about that?
Business Intelligence technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.
Data mining tools are so vital in getting BI and could serve different domains, depends on what you really want to search.
Data mining is part of Business intelligence tool.
It help BI in providing phenomena, overview,holistic view of organization condition.
By DM decision maker have valid ground to decide of action to be purpose or achieve organizational goal(decision support).
With DM, BI can predict or prescribe action on dashboard visualization on competitor,market condition,consumer behavior etc.
Thank you. Do you have any articles about DM in BI?
Actually, I want to define an AI project in management or BI for a company. Unfortunately, they do not have any familiarity with AI. So, they cannot define an AI project themselves. Do you know any done project in this field?
You will want to read Sabherwal and Becerra-Fernandez book on business intelligence. This is a great summary of BI that relates how DM fits in.
Sabherwal, R., and Becerra-Fernandez, I. 2011. Business Intelligence, Technologies and Management. Hoboken, NJ: John Wiley & Sons, Inc. .
Business Intelligence is often a completely separate sect from Database Administration and Database Development. Business Intelligence, at the highest level, includes three main facets:
Data mining has in mind:
Representation language model includes assumptions and constraints used in the representation used.
Evaluation of the model include the use of cross-validation techniques for predictability and application of principles such as maximum likelihood or minimum description to evaluate the quality of the model specification.
Search Method: search can be divided into model parameters and determine the criteria used to find models.
based on this, its application in this field is given by:
The development of data mining technology is at a turning point with respect to its consolidation in applications. There are several elements that make it applicable, and a reality that demand; however, a number of challenges that undermine their credibility. One is that the products are expensive, so consumers can find a cost / benefit ratio unproductive.
The application of data mining, and allows the discovery of knowledge to the commercial sector, supports research on biological branch, found in it an irreplaceable to face the flood of data produced by genomic and proteomic research tool. In this sense, it is necessary to further develop computational tools tional suitable for use in various projects and raise the level of knowledge about its utility for researchers.
Today I accidentally came across to this question and despite more than obvious late in response or perhaps that there no exist some active followers I will try to give an answer that possible be of some use. Data mining in BI can't be seen as separate part out of BI system - simplified data acquisition, data storage, data preparation, data analysis, visualization, decision support and forming action plan. It is very likely that in an absence of any kind of interaction no form of the intelligence can be perceived so the BI needs final actions not only decisions. Data mining techniques complement other BI approaches/tools OLAP, AD-HOC Queries, Dashboards, simulation techniques, statistical methods, etc. Usually DM are used in situations where these, other techniques can't provide solution to the detected problem while there exists plethora of data produced by processes related to the problem. Here's the list of some DM applications in BI or better as part of the BI system:
* Customer churn prediction in telecommunication
* Recommender system
* Loyalty program
* Cross-selling (e.g. Market basket analysis)
* Target marketing (customer segmentation)
* Assessing credit/loan risk (as a part of decision support system)
* Credit card frauds
* Predicting machine/device failure/malfunction
* etc.
Hope this helps.
Dear Vahid, a bit late to the game, but I recommend you to have a look into the area of process mining, which has many data mining applications in BPM. See for example my recent article, in which we predict all kinds of aspects of running instances of a business process using data mining techniques. We describe many similar works in our related work section.
https://www.researchgate.net/publication/311492449_Predictive_Business_Process_Monitoring_with_LSTM_Neural_Networks
Article Predictive Business Process Monitoring with LSTM Neural Networks
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