CN112183379A - Report-oriented multi-dimensional management analysis method and system - Google Patents
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Abstract
The invention discloses a report-oriented multidimensional management analysis method which comprises the following steps that (1) a report data source is uploaded to a data platform to be configured in a guiding manner; (2) carrying out rule query and screening on the configured report data source, decomposing and identifying to generate a plurality of data labels associated with the indexes, matching the data labels with the index labels in the index feature library to generate result data; (3) inquiring result data through a dimension management module, and taking the inquired problem data as an analysis sample; (4) carrying out multi-dimensional comprehensive processing analysis on the analysis sample to generate an analysis result; (5) and filling the analysis result into a data statistical template through a data display module to generate a multidimensional data analysis graph. The data source of the power grid report is processed and analyzed through the data platform, indexes and set dimensions in the data source are extracted, combined analysis is carried out according to the required dimensions, and comprehensive display and analysis of data from multiple layers and multiple aspects are achieved.
Description
Technical Field
The invention belongs to the technical field of report statistical analysis, and particularly relates to a report-oriented multi-dimensional management analysis method and system.
Background
Around the development goals of 'one-strong three-excellent' modern companies and 'two-transformation', the production mode of the smart power grid is changed from the aspect of strategic development of the companies, and the application of new technologies such as artificial intelligence, cloud computing, big data and the like in the field of modern power grid scheduling control is increasingly required; the picking up and formulation of the power grid dispatching information and the formulation of the monitoring information eventualization rule are very urgent, the improvement of the real-time monitoring intellectualization and informatization level of the power grid dispatching is also very urgent, and the requirements of people on the monitoring and analysis of the power grid operation data are higher and higher.
With the development of a power grid system, a large number of user logs can be generated by the system every day, a server needs to store the logs generated by users and perform statistics, analysis and query on the logs, at present, report statistics lacks an independent and professional support, data are scattered in corners of each system, the retrieval difficulty is high, a large number of statistics also need to be manually input and summarized, the working efficiency is low, the difficulty of deep analysis of the power grid indexes by professional staff is high, and therefore deep information is difficult to obtain, and the data are not beneficial to multi-dimensional analysis and display.
Therefore, in order to solve the above technical problems, it is necessary to develop a report-oriented multi-dimensional analysis method and apparatus.
Disclosure of Invention
The invention aims to provide a report-oriented multi-dimensional management analysis method which improves the flexibility and query efficiency of reports and analyzes report data in a multi-dimensional manner.
The invention also aims to provide a report-oriented multi-dimensional management analysis system.
The technical scheme of the invention is as follows:
a report-oriented multi-dimensional management analysis method comprises the following steps:
(1) the method comprises the steps that a user side inputs and uploads a report data source to a data platform, and the report data source is configured in a guiding mode;
(2) inputting a configured report data source into a data identification model, performing rule query and screening on the report data source, decomposing and identifying to generate a plurality of data tags associated with indexes, matching the data tags with index tags in an index feature library through an index tag matching module according to a preset index tag rule, and generating result data;
(3) inquiring result data according to a set dimension condition through a dimension management module, displaying the result data through multiple dimensions, and taking the inquired problem data as an analysis sample;
(4) carrying out multi-dimensional comprehensive processing analysis on the analysis sample in the step (3) through an analysis module to generate an analysis result;
(5) and filling the analysis result into a preset data statistical template through a data display module to generate a multi-dimensional data analysis graph.
In the above technical solution, the step (1) specifically includes the following steps:
(1-1) judging the starting time and the ending time of a report data source, and dividing data into a plurality of data segments in sequence according to a preset time period;
and (1-2) sequencing according to the earliest starting time in each data segment, and sequentially outputting the data segments containing the report data source as data to be counted.
In the above technical solution, in the step (2), index content is recommended for a history index or a recent common index of a user side, wherein operation counting is performed according to the history index or the recent common index of the user side, the number of selection times corresponding to each index is recorded, frequent items of the selected indexes are recorded, and minimum items of the frequent items are compared after each user selects an index, so that real-time recommendation of optimal frequent items of data is realized.
In the above technical solution, the method for establishing the data identification model in step (3) includes the following steps:
s1, acquiring an original report data source as an input parameter;
s2, inputting the input parameters into an SVM model for training, and obtaining a training model when the training times reach a preset training number or the training accuracy reaches a preset training value;
and S3, inputting the input parameters into the training model for testing, and obtaining a data identification model when the testing times reach a preset testing number or the testing accuracy reaches a preset testing value.
In the above technical solution, the establishment of the index feature library included in the data recognition model includes the following steps:
q1., decomposing according to the report data source, identifying and extracting the keyword information associated with the report index to obtain index characteristics;
q2, extracting the index features, and creating and generating an index label;
q3., editing the created index label, and aggregating a plurality of index labels to form an index feature library.
In the above technical solution, in the step (3), the dimension management module establishes dimensions corresponding to power grid regulation and control, and establishes corresponding dimension tables for the dimensions, respectively, wherein main dimensions are analyzed according to an existing relationship of power grid regulation and control, generally including main dimensions such as date, time, voltage level, area, station, responsibility area, alarm type, five groups, and the like, and the dimension tables are established for the dimensions, respectively.
In the technical scheme, the indexes comprise population, GDP, electric quantity, skill, scheduling, power generation scheduling, mode, protection, safety, economy, energy conservation, environmental protection, high quality, year, month and day.
In the technical scheme, the dimensionality comprises date, time, voltage level, area, station, responsibility area, alarm type and five groups, wherein the time is the time of the day, the five groups comprise accidents, abnormity, out-of-limit, displacement and notification, and the alarm type comprises accident information, telemetering out-of-limit, remote signaling displacement and alarm direct transmission.
A report-oriented multi-dimensional management analysis system comprises:
the client is used for inputting and uploading a report data source;
the data platform is used for receiving the report data source by a user, processing and analyzing the report data source and generating a multi-dimensional data analysis chart according to the selected dimension condition of the index set; wherein the data platform comprises:
the data acquisition module is used for acquiring a report data source in real time according to a preset time period;
the data identification module is used for inputting the report data source into a data identification model to obtain a data label of the report data source, matching the data label with an index label of an index feature library and generating result data;
the dimension management module is used for inquiring the result data according to the selected dimension condition and generating an analysis sample;
the analysis module is used for carrying out multi-dimensional processing on the analysis sample according to the dimensional condition and the index label to generate an analysis result;
and the data display module is used for filling the analysis result into the statistical template in the data display module to generate a multidimensional data analysis graph.
The multidimensional management and analysis system provides a rich multidimensional analysis basis for each index data, and can display the report data source of the power grid from multidimensional analysis, scrolling and drilling among dimensions and triggerable linkage realization among the dimensions.
The multidimensional data analysis graph can show the multidimensional data display of the required power grid report for people in different levels, so that the multidimensional data can be comprehensively displayed.
The invention has the advantages and positive effects that:
1. the data source of the power grid report is processed and analyzed through the data platform, indexes and set dimensions in the data source are extracted, combined analysis is carried out according to the required dimensions, multiple display themes are provided for data analysis of a power grid system, comprehensive, rich and multi-level display of the data is achieved, and meanwhile, the data are comprehensively displayed and analyzed from multiple layers and multiple sides by combining multi-dimensional data linkage and multi-dimensional analysis.
Detailed Description
The present invention will be described in further detail with reference to specific examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the scope of the invention in any way.
Example 1
The invention relates to a report-oriented multi-dimensional management analysis method, which comprises the following steps:
(1) the method comprises the steps that a user side inputs and uploads a report data source to a data platform, and the report data source is configured in a guiding mode;
(2) inputting a configured report data source into a data identification model, performing rule query and screening on the report data source, decomposing and identifying to generate a plurality of data tags associated with indexes, matching the data tags with index tags in an index feature library through an index tag matching module according to a preset index tag rule, and generating result data;
(3) inquiring result data according to a set dimension condition through a dimension management module, displaying the result data through multiple dimensions, and taking the inquired problem data as an analysis sample;
(4) carrying out multi-dimensional comprehensive processing analysis on the analysis sample in the step (3) through an analysis module to generate an analysis result;
(5) and filling the analysis result into a preset data statistical template through a data display module to generate a multi-dimensional data analysis graph.
Further, the step (1) specifically includes:
(1-1) judging the starting time and the ending time of a report data source, and sequentially dividing the data into a plurality of data segments according to a preset time period, wherein the starting time and the ending time of the report data source can be recorded when the report data source records the data at the background, in order to obtain the report data source in real time in the step, but in order to avoid the condition that a server is crashed due to overlarge calculation amount of all data at the same time, the technical scheme adopts a method for obtaining the data in an interval: presetting a time interval, namely a preset time period, judging the starting time and the ending time in system data, and carrying out partition processing on data generated by the system;
(1-2) sequencing according to the earliest starting time in each data segment, and sequentially outputting the data segments containing the report data source as data to be counted; wherein, in the step (1-2), the report data source is divided according to a preset time period, and then the data to be counted is output in sequence, and the data to be counted is in the form of data segments and the data to be counted in the time interval is output in sequence.
Further, in the step (2), index content is recommended to the historical index or the latest commonly used index of the user side, wherein operation counting is performed according to the historical index or the latest commonly used index of the user side, the number of selection times corresponding to each index is recorded, frequent items of the selected indexes are recorded, and the minimum items of the frequent items are compared after each user selects the index, so that the optimal frequent items are recommended to the user side in real time.
Further, the method for establishing the data identification model in the step (3) includes the following steps:
s1, acquiring an original report data source as an input parameter;
s2, inputting the input parameters into an SVM model for training, and obtaining a training model when the training times reach a preset training number or the training accuracy reaches a preset training value;
and S3, inputting the input parameters into the training model for testing, and obtaining a data identification model when the testing times reach a preset testing number or the testing accuracy reaches a preset testing value.
Further, the establishing step of the index feature library included in the data identification model comprises:
q1., decomposing according to the report data source, identifying and extracting the keyword information associated with the report index to obtain index characteristics;
q2, extracting the index features, and creating and generating an index label;
q3., editing the created index label, and aggregating a plurality of index labels to form an index feature library.
Further, in the step (3), the dimensionality management module establishes dimensionalities corresponding to power grid regulation and control, and establishes corresponding dimensionality tables for the dimensionalities respectively, wherein main dimensionalities are analyzed according to the existing power grid regulation and control relation, and generally comprise main dimensionalities of date, time, voltage level, area, station, responsibility area, alarm type, five groups and the like, and the dimensionality tables are established for the dimensionalities respectively.
The dimensionality comprises date, time, voltage level, area, station, responsibility area, alarm type and five groups, wherein the time is the time of day, the five groups comprise accidents, abnormity, out-of-limit, displacement and notification, and the alarm type comprises accident information, telemetering out-of-limit, telecommand displacement and alarm direct transmission.
Example 2
On the basis of embodiment 1, the invention provides a report-oriented multidimensional management and analysis system, which comprises:
the client is used for inputting and uploading a report data source;
the data platform is used for receiving the report data source by a user, processing and analyzing the report data source and generating a multi-dimensional data analysis chart according to the selected dimension condition of the index set; wherein the data platform comprises:
the data acquisition module is used for acquiring a report data source in real time according to a preset time period;
the data identification module is used for inputting the report data source into a data identification model to obtain a data label of the report data source, matching the data label with an index label of an index feature library and generating result data;
the dimension management module is used for inquiring the result data according to the selected dimension condition and generating an analysis sample;
the analysis module is used for carrying out multi-dimensional processing on the analysis sample according to the dimensional condition and the index label to generate an analysis result;
and the data display module is used for filling the analysis result into the statistical template in the data display module to generate a multidimensional data analysis graph.
The multidimensional management and analysis system provides a rich multidimensional analysis basis for each index data, and can display the report data source of the power grid from multidimensional analysis, scrolling and drilling among dimensions and triggerable linkage realization among the dimensions.
The multidimensional data analysis graph can show the multidimensional data display of the required power grid report for people in different levels, so that the multidimensional data can be comprehensively displayed.
The invention has been described in an illustrative manner, and it is to be understood that any simple variations, modifications or other equivalent changes which can be made by one skilled in the art without departing from the spirit of the invention fall within the scope of the invention.
Claims (10)
1. A report-oriented multi-dimensional management analysis method is characterized in that: the method comprises the following steps:
(1) the method comprises the steps that a user side inputs and uploads a report data source to a data platform, and the report data source is configured in a guiding mode;
(2) inputting a configured report data source into a data identification model, performing rule query and screening on the report data source, decomposing and identifying to generate a plurality of data tags associated with indexes, matching the data tags with index tags in an index feature library through an index tag matching module according to a preset index tag rule, and generating result data;
(3) inquiring result data according to a set dimension condition through a dimension management module, displaying the result data through multiple dimensions, and taking the inquired problem data as an analysis sample;
(4) carrying out multi-dimensional comprehensive processing analysis on the analysis sample in the step (3) through an analysis module to generate an analysis result;
(5) and filling the analysis result into a preset data statistical template through a data display module to generate a multi-dimensional data analysis graph.
2. The multidimensional management and analysis method according to claim 1, wherein the step (1) specifically comprises the steps of:
(1-1) judging the starting time and the ending time of a report data source, and dividing data into a plurality of data segments in sequence according to a preset time period;
and (1-2) sequencing according to the earliest starting time in each data segment, and sequentially outputting the data segments containing the report data source as data to be counted.
3. The multidimensional management analysis method of claim 2, wherein: in the step (2), index content is recommended to the historical index or the recent common index of the user side, wherein operation counting is performed according to the historical index or the recent common index of the user side, the number of selection times corresponding to each index is recorded, frequent items of the selected indexes are recorded, and the minimum items of the frequent items are compared after each user selects the indexes, so that the optimal frequent items are recommended to the user side in real time.
4. The multidimensional management analysis method of claim 3, wherein: the method for establishing the data identification model in the step (3) comprises the following steps:
s1, acquiring an original report data source as an input parameter;
s2, inputting the input parameters into an SVM model for training, and obtaining a training model when the training times reach a preset training number or the training accuracy reaches a preset training value;
and S3, inputting the input parameters into the training model for testing, and obtaining a data identification model when the testing times reach a preset testing number or the testing accuracy reaches a preset testing value.
5. The multidimensional management and analysis method according to claim 4, wherein the establishment of the index feature library included in the data recognition model comprises the following steps:
q1., decomposing according to the report data source, identifying and extracting the keyword information associated with the report index to obtain index characteristics;
q2, extracting the index features, and creating and generating an index label;
q3., editing the created index label, and aggregating a plurality of index labels to form an index feature library.
6. The multidimensional management analysis method of claim 5, wherein: in the step (3), the dimensionality management module establishes dimensionalities corresponding to power grid regulation and control, and establishes corresponding dimensionality tables for the dimensionalities respectively, wherein main dimensionalities are analyzed according to the existing relation of the power grid regulation and control, and generally comprise main dimensionalities such as date, time, voltage level, area, station, responsibility area, alarm type, five-class grouping and the like, and the dimensionality tables are established for the dimensionalities respectively.
7. The multidimensional management analysis method of claim 6, wherein: the indexes comprise population, GDP, electric quantity, skills, menses, scheduling, power generation scheduling, mode, protection, safety, economy, energy conservation, environmental protection, high quality, year, month and day.
8. The multidimensional management analysis method of claim 7, wherein: the dimensionality comprises date, time, voltage level, area, station, responsibility area, alarm type and five groups, wherein the time is the time of day, the five groups comprise accident, abnormity, out-of-limit, deflection and notification, and the alarm type comprises accident information, telemetering out-of-limit, telecommand deflection and alarm direct transmission.
9. A report-oriented multi-dimensional management analysis system comprises:
the client is used for inputting and uploading a report data source;
the data platform is used for receiving the report data source by a user, processing and analyzing the report data source and generating a multi-dimensional data analysis chart according to the selected dimension condition of the index set; wherein the data platform comprises:
the data acquisition module is used for acquiring a report data source in real time according to a preset time period;
the data identification module is used for inputting the report data source into a data identification model to obtain a data label of the report data source, matching the data label with an index label of an index feature library and generating result data;
the dimension management module is used for inquiring the result data according to the selected dimension condition and generating an analysis sample;
the analysis module is used for carrying out multi-dimensional processing on the analysis sample according to the dimensional condition and the index label to generate an analysis result;
and the data display module is used for filling the analysis result into the statistical template in the data display module to generate a multidimensional data analysis graph.
The multidimensional management and analysis system provides a rich multidimensional analysis basis for each index data, and can display the report data source of the power grid from multidimensional analysis, scrolling and drilling among dimensions and triggerable linkage realization among the dimensions.
The multidimensional data analysis graph can show the multidimensional data display of the required power grid report for people in different levels, so that the multidimensional data can be comprehensively displayed.
10. A computer-readable storage medium characterized by: the computer readable storage medium includes a stored computer program that: wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the multidimensional management analysis method of any one of claims 1-8.
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| CN113268514A (en) * | 2021-05-26 | 2021-08-17 | 深圳壹账通智能科技有限公司 | Multidimensional data statistical method and device, electronic equipment and storage medium |
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