Data drilling

Abstract: Currently, the concept of Data Mining is increasingly recognized as an important tool in information management because of the increasing amount of information. This study aims to classify the number of passengers at the airport Hang Nadim Batam. A very large sum of these huge amounts of data wants data for the new knowledge of the data. Data drilling is a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify relevant information and large databases. One technique known in data mining is grouping, which is the process of grouping a number of data or objects into a cluster (group). Each of these clusters will contain data that is as similar as possible and different from the objects in the other clusters. In this case we can select the price data as the initial cluster center, then calculate the distance between each data in the cluster center and determine the nearest cluster, then average averages of all groups, so that the existing process is not the same. After the process is done quickly by using RapidMiner, create clusters in grouping the number of passengers. Where the variable used is the first variable, namely: the number of passengers coming, the number of passengers departing, the number of transits that transit. Where will present data on the number of passengers a lot, medium and small.

Abstract: The invention relates to a configurable multidimensional dynamic data graph group association method. According to the method provided by the invention, a group of associated dimension graphs simultaneously show multiple dimensions of a data cube; by clicking one dimension graph, other associated dimension graphs can vary correspondingly according to the clicked content; each dimension graph may perform up and down data drilling, and meanwhile, other associated dimension graphs can vary according to the content of up and down drilling. A configuration file used in the method comprises a back-end data cube description file, a front-end associated graph group description file and an instrument panel description file; and a back-end data logic, a front-end multidimensional associated graph group and an instrument panel page layout are decoupled. The method described in the invention may be applied in an OLAP system and a commercial intelligent system.

Abstract: The invention discloses a multidimensional data model modeling method of a power grid regulation and control integration system. An existing relation model of the power grid regulation and control integration system is seamlessly converted into a multidimensional data model for supporting follow-up multidimensional observing, data drilling, complicated multidimensional data set calculating and the like. Relevant standards are formed in the multidimensional data model modeling process, and it is of great significance to promote scientific development of a power grid and increase the management level of the power grid.

Abstract: The invention provides a data drilling device and a data drilling method. The data drilling device comprises a data setting unit, a parameter processing unit and an inquiry processing unit. The data setting unit is used for grouping fields in a report, selecting a main field in each group, setting a page address and a fixed parameter for each field; the parameter processing unit is used for obtaining the value of the main field in the field group with a field selected by a user as a dynamic parameter corresponding to the field selected by the user after the user selects the value of any field in the report and sends a drilling request; and the inquiry processing unit is used for generating inquiring conditions according to the fixed parameter and the dynamic parameter corresponding to the field selected by the user, and inquiring the report with the page address corresponding to the field selected by the user, thereby completing drilling. By adopting the technical scheme, different field data can be drilled, the association with the fields in other reports can be realized through the main field in the field group, and the report drilling can be simplified.