Data mining is designed for the extraction of knowledge or knowledge from large amounts of data, by automatic or semi-automatic. Industrial or operational use of this data in the professional world can solve a variety of problems, ranging from the management of the customer relationship to preventive maintenance, through the detection of fraud and the optimization of websites.
Exploring data follows in the escalation of the use of business data in business intelligence. It reveals important information, such as turnover. Data mining is used to classify the facts and to provide variables or parameters that explain why the turnover of one period is higher than another thanks to Industrial Automation Service Providers.
Applications
Nowadays, data mining techniques can be used in completely different areas with very specific goals. Companies analyze the data, with this technique, consumer behavior to identify similarities. Marketing companies use data mining to reduce the cost of acquiring a new customer prospects by ranking based on criteria allowing them to increase rates to questionnaires.
These same companies, and others such as banks, mobile operators and insurers looking through data mining to minimize attrition (or churn) of their customers as the cost of keeping a customer is less important than acquiring a new one.
Other examples in other areas could be found, but what can be seen now is that all these uses allow us to characterize a complex phenomenon (human behavior), to better understand, to reduce search costs and revenues associated with it, or to improve the quality of the process thanks to Industrial Automation Service Providers.
Research and focus groups
Universities such as Constance in Germany, Dortmund , North Carolina, United States of Waikato in New Zealand, and the University of Lyon in France, conducted research to find new and improved algorithms old. They also developed software for their students, teachers and researchers to progress in this area, thus benefit the industry in their progress.
On the other hand, many inter-professional groups and associations are created to reflect and support the development of data mining. The first of these professional groups in the field is the interest group of the Association for Computing Machinery on knowledge management.
This research and financially meaningful results require specialized teams in data mining to conduct a methodical work in structured projects. If the heat exchange fluid is poured into the insulation pores, the oxidation decomposition process is triggered there. The oxidation process produces heat.
The heat produced is added to the heat of the system, already present in the insulation. Thus the insulation temperatures continue to rise and may even exceed the auto-ignition point; at this point, if the air enters the insulation and comes into contact with the oxidized and degraded fluid, fires can immediately develop.
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