Data analysis database mining

A variety of methods have been developed by mathematicians and computer scientists to address this task, which has become known as data mining (see Chapter 9, Section 9.8). Fayyad defined and described the term data mining as the nontrivial extraction of impHcit, previously unknown and potentially useful information from data, or the search for relationships and global patterns that exist in databases [16]. In order to extract information from huge quantities of data and to gain knowledge from this information, the analysis and exploration have to be performed by automatic or semi-automatic methods. Methods applicable for data analysis are presented in Chapter 9. 

Okada, Y., and Fujibuchi, W. (2007) Mining a Large-scale Microarray Database for Similar Gene Expression Modules to Find Distant Relationships between Down Syndrome and Huntington s Disease. Proceedings of Critical Assessment of Microarray Data Analysis 07, Valencia, Spain. 

Phase IV studies can also take the form of retrospective pooled analyses which are designed to reflect the totality of clinical research experience with a new drug which is usually obtained via analysis of pooled clinical trial databases. Such data-mining efforts should not be considered inferior to data obtained from the conduct of an individual clinical trial. In fact, there are substantial benefits of such an approach, as the results of a given trial, especially if the end point is not prespecified to be primary because of power limitations, can be a function of chance. To assure that the results obtained from pooled analyses are not biased, a prespecified data analysis plan is often formulated as the first step, outlining the clear goals of the proposed analysis as well as its methodology. Key to this type of analysis is the definition of the outcome measure. Both efficacy and safety measures can be the focus of these types of analyses. 

The trend is continuing ab initio packages that can calculate vibrational frequencies and their atomic displacements for extended solids are now available. In addition to the analysis of new systems, this also enables older data to be mined again to provide new insights. N-methylacetamide [3,4] and thymine [5,6] are cases in point. The availability of older data is a crucial factor in this data mining and initiatives such as the INS database [7] that enable this are sure to become standard practice. 

The Oracle Edition module includes components that employ the native Oracle lOg data mining capabilities for data stored in that database. These components perform data analysis on the data without moving it out of the database. 

Data warehousing A modern database is where data and information are stored. Connections that are not readily apparent can be uncovered with the use of data mining and OLAP. These techniques are part of data analysis. 

The required data for this research was collected from operation and maintenance reports and direct field observations over a period of two years. Many of the desired information, such as failure occurrence times, reasons of failure, types of repair actions and time to repair were available in mine database, therefore only TBFs values were calculated. All needed calculations related to data analysis and reliability modeling were carried out using Easy/it and Microsoft Excel software. 

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