CN115422146B - A Construction and Application Method of Standardized Database for Enterprises in Xinjiang Region - Google Patents

Abstract

The invention relates to the technical field of enterprise standardized database construction, and discloses a method for constructing and applying an enterprise standardized database in Xinjiang, which comprises the following steps: s1, acquiring a data feature a for constructing a standardized database and a data feature b under the current enterprise running state in the Internet, and generating a data table under the relevance of the current data feature a and the data feature b. According to the method, through the relevance among different data characteristics, an abnormal data generation source is generated according to a real digital interval, an abnormal data cleaning instruction is obtained, abnormal data is cleaned at regular time, so that an enterprise database can be constructed in a standardized mode, the decision efficiency of an enterprise is greatly improved, and the normalized data characteristics under the current construction standard can be supplemented by automatically repairing the residual data information which does not reach the fit standard, so that a normal operation work frame under the current enterprise standardized database is established.

Description

A Construction and Application Method of Standardized Database for Enterprises in Xinjiang Region

technical field

The invention relates to the technical field of enterprise standardization database construction, in particular to a construction and application method of enterprise standardization database in Xinjiang region.

Background technique

Xinjiang Uygur Autonomous Region, referred to as Xin, is one of the five ethnic minority autonomous regions in China. It is located in the northwest region and its capital is Urumqi. One of the eight 10 million-kilowatt wind power bases. However, the construction sites of wind farms and photovoltaic power stations in Xinjiang are mostly far away from the load center, and the geographical location of the load center is quite different, showing the characteristics of reverse distribution. This feature determines that the wind power/photovoltaic development model in Xinjiang is based on large-scale centralized development. A large number of wind farms and photovoltaic power stations are gathered on the same bus, and after being raised to high voltage by transformers, they are transported to the load center for consumption over long distances. At present, DC transmission is a more reliable and economical power transmission method than AC transmission for thousands of kilometers of power transmission without a drop point in the middle. The need to transmit electric energy to the load center, and with the continuous development of the economy in Xinjiang, many enterprises have emerged as the times require, and while many enterprises are developing, the issue of database construction and application is particularly important.

The current database is difficult to build in a standardized mode. Enterprises cannot establish a complete database of big data information indicators, which cannot improve the efficiency of corporate decision-making. Moreover, it is difficult to automatically repair the remaining data information that does not meet the standards, and it is impossible to complete the current construction. The normalized data characteristics under the standard make it impossible to establish a normal operation work framework under the current enterprise standardized database.

Contents of the invention

The purpose of the present invention is to provide a method for constructing and applying a standardized database for enterprises in Xinjiang, so as to solve the problems raised in the above-mentioned background technology.

In order to achieve the above object, the present invention provides the following technical solutions: a method for constructing and applying a standardized database for enterprises in Xinjiang, comprising the following steps:

S1. Collect the data feature a and the data feature b under the current operating state of the enterprise in the Internet, generate a data table with the correlation between the current data feature a and data feature b, and create multiple sets of data display on the data table Model, and assign unique numbers to multiple sets of data display models according to the numbers of 1, 2...N;

S2. Perform in-depth analysis of the current data feature a and data feature b based on the established multi-group data display model, generate the variable type under the correlation and the MDS element with the same attribute, and convert the variable type through the converter for data conversion , copy the data source in the standard format generated in the MDS element;

S3. Query the remaining variable types without correlation and the remaining elements without the same attributes, divide and mark the remaining variable types and remaining elements on the data display model, and demonstrate the remaining variable types through the ghost function simulation The future change trend line of the remaining variable data, and simulate and demonstrate the future change trend line of the remaining data under the remaining elements through the derivative function, calculate the real digital interval between the future change trend line of the remaining variable data and the future change trend line of the remaining data, and establish two the threshold range between

S4. According to the construction standard of the standardized database in the Internet, sort out the remaining variable types and remaining elements, select the remaining data information with a degree of agreement with the construction standard of more than 85-95%, and use the data circulation strategy to eliminate the data that does not meet the standard. Information, and automatically repair the remaining data information, complete the normalized data characteristics under the current construction standard, and combine the data source to establish a normal operation work framework under the current enterprise standardized database;

S5. Transfer the established normal operation work framework to the enterprise work model architecture, send normal operation instructions intermittently, observe whether the enterprise operation data is abnormal, and establish a work model architecture consistent with the enterprise work model by editing the work logic under the normal operation work framework The data collection port in the remote terminal collects and monitors the daily operation data in real time, generates collection points and monitoring points, and analyzes the final index library through data coding.

Optionally, within the threshold range, the source of abnormal data is generated according to the real number interval, and the source of abnormal data is compared with the data feature a of the standardized database according to the number of occurrences of the source of abnormal data to obtain an abnormal data cleaning instruction, And regularly clean abnormal data.

Optionally, after the data source is generated, the distributed network probes search for the data information under the current data characteristics, record all the search paths of the network probes at the same time, and establish the current data information operation according to all the obtained search paths The basic logic under the trajectory.

Optionally, after completing the normalized data features under the current construction standard, quality inspection and standardized data training should be performed on the normalized data features to obtain a standardized data training set.

Optionally, before parsing, the indicator library collects and monitors the daily operation data, creates multiple service terminals and service interfaces under the current daily operation data, desensitizes the daily operation data and amplifies the signal, Form the final indicator library.

Optionally, after the collection points and monitoring points are generated, multiple sets of feature information under the current data collection port should be automatically sorted out, and multiple sets of feature information are rearranged and classified according to type and storage size, and multiple sets of feature information are established. Independent transmission channels under group feature information.

Optionally, after the analysis of the index library, an index column under the daily operation data is generated in the index library, and a data trigger button is established according to the corresponding data information in the index column. When the data trigger button generates an instruction, the index library is automatically selected Duplicate data in and generate extra parameters, and format the extra parameters.

Optionally, the normal operation work frame is created based on multiple data elements under the data source, where the data elements include data length, data name, data type, data format, data start position and data end position.

Compared with the prior art, the beneficial effect of the present invention is: the method generates abnormal data occurrence sources according to the real digital interval through the correlation between different data features, obtains abnormal data cleaning instructions, and regularly cleans the abnormal data, It enables the enterprise database to be constructed in a standardized mode, which is conducive to the establishment of a complete big data information index database, greatly improving the efficiency of enterprise decision-making, and by automatically repairing the remaining data information that does not meet the standard, it can complement the current construction standard The characteristics of normalized data under the normalized data, and then establish the normal operation framework under the current enterprise standardized database, making the enterprise database more standardized and streamlined, which is conducive to the precise management of information in various departments of the enterprise, and has certain market promotion prospects.

Detailed ways

The following clearly and completely describes the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

The invention provides a method for constructing and applying a standardized database for enterprises in Xinjiang, comprising the following steps:

S1. Collect the data feature a and the data feature b under the current operating state of the enterprise in the Internet, generate a data table with the correlation between the current data feature a and data feature b, and create multiple sets of data display on the data table Model, and assign unique numbers to multiple sets of data display models according to the numbers of 1, 2...N;

S2. Perform in-depth analysis of the current data feature a and data feature b based on the established multi-group data display model, generate the variable type under the correlation and the MDS element with the same attribute, and convert the variable type through the converter for data conversion , copy the data source in the standard format generated in the MDS element;

S3. Query the remaining variable types without correlation and the remaining elements without the same attributes, divide and mark the remaining variable types and remaining elements on the data display model, and demonstrate the remaining variable types through the ghost function simulation The future change trend line of the remaining variable data, and simulate and demonstrate the future change trend line of the remaining data under the remaining elements through the derivative function, calculate the real digital interval between the future change trend line of the remaining variable data and the future change trend line of the remaining data, and establish two Within the threshold range, the abnormal data source is generated according to the real number interval, and the abnormal data source is compared with the data feature a of the standardized database according to the number of occurrences of the abnormal data source, and the abnormal data cleaning instruction is obtained. , and regularly clean abnormal data;

S4. According to the construction standard of the standardized database in the Internet, sort out the remaining variable types and remaining elements, select the remaining data information with a degree of agreement with the construction standard of more than 85-95%, and use the data circulation strategy to eliminate the data that does not meet the standard. Information, and automatically repair the remaining data information, complete the normalized data characteristics under the current construction standard, and combine the data source to establish a normal operation work framework under the current enterprise standardized database;

S5. Transfer the established normal operation work framework to the enterprise work model architecture, send normal operation instructions intermittently, observe whether the enterprise operation data is abnormal, and establish a work model architecture consistent with the enterprise work model by editing the work logic under the normal operation work framework The data collection port in the remote terminal collects and monitors the daily operation data in real time, generates collection points and monitoring points, and analyzes the final index library through data coding.

Further: After the data source is generated, the data information under the current data characteristics is searched through the distributed network probes, and all the search paths of the network probes are recorded at the same time, and the current data information running track is established according to all the search paths obtained. Basic logic, at the same time build the editing mechanism and operation authority under the basic logic, judge the content and process of data information, and analyze whether the current data information running track has shifted. Before the content judgment and process judgment, the current inspection personnel should also be dealt with Collect basic information and analyze whether the current testing personnel have judgment authority.

Further: After completing the normalized data features under the current construction standards, quality inspection and standardized data training should be carried out on the normalized data features, and a standardized data training set should be obtained.

Further: before the analysis of the indicator library, the daily operation data is collected and monitored, and multiple service terminals and service interfaces under the current daily operation data are created, and the daily operation data is desensitized and the signal is amplified to form the final Indicator library.

Further: After the collection points and monitoring points are generated, they should also automatically sort out multiple sets of feature information under the current data collection port, rearrange and classify multiple sets of feature information according to type and storage size, and establish multiple sets of feature information Under the independent transmission channel, connect the independent transmission channel with the external server, use the optimal transmission line in the external server to optimize the independent transmission channel in real time, know the transmission path under the current independent transmission channel, and connect the optimal transmission line Send to an independent transmission channel for channel construction.

Further: After the indicator library is analyzed, the index column under the daily operation data is generated in the indicator library, and the data trigger button is established according to the corresponding data information in the index column. When the data trigger button generates an instruction, the repetition in the indicator library is automatically selected. Data and generate additional parameters, and format the additional parameters, then perform visual interface query on the additional parameters, and add new resource parameters to render and make the visual interface. Among them, the data editing of the current page is required before the visual query And data planning, data planning includes data parameters and data attributes.

Further: The normal operation work framework is created based on multiple data elements under the data source, where the data elements include data length, data name, data type, data format, data start position and data end position.

Take a chemical company A in Xinjiang as an example to explain the construction of the database:

There are many classifications of enterprise data characteristics, and the construction of standard databases is carried out from different data attributions. Take the human data as an example for specific illustrations.

First of all, set the data characteristic a of building a standardized human resource database in chemical enterprises as the distribution of standard personnel, specifically 20-30% of R&D personnel, 30-40% of ordinary technical personnel, 40-50% of operating workers, and 10-50% of logistics support personnel. 20%; the data feature b under the current operating status of enterprise A is the actual personnel distribution, specifically 20% for R&D personnel, 30% for ordinary technical personnel, 40% for operating workers, and 10% for logistics support personnel;

According to the above data characteristics, generate a data table under the correlation between the current manpower distribution data feature a and the actual personnel data feature b, and establish 1. R&D personnel, 2. Ordinary technical personnel, 3. Operators, 4. Logistics on the data table Multiple sets of data display models for security personnel;

Based on the above-mentioned 4 sets of data display models established above, the current standard personnel distribution data feature a and the actual personnel distribution data feature b are deeply analyzed, and it is found that the educational background distribution is a variable type that is related to the personnel distribution and MDS that produces the same attribute Element, after the variable type is converted into data by the converter, copy the data of educational background distribution in the MDS element to generate a data source in a standard format; the educational background of the MDS element with the same attribute is undergraduate or above; undergraduate or above basic entry R & D personnel; undergraduates basically enter ordinary technical personnel;

Query the remaining variable types without correlation and the remaining elements that do not produce the same attributes as undergraduates, and divide and mark the remaining variable types and remaining elements, that is, the personnel below the undergraduates on the data display model, and the personnel below the undergraduates Can be used as an assistant to join the research and development personnel, can be used as an assistant to join the ordinary technicians, can join the operation workers, and can join the logistics support staff;

Demonstrate the future change trend line of the remaining variable data under the remaining variable type through the ghost function simulation, and demonstrate the future change trend line of the remaining data of the remaining elements under the undergraduate degree through the derivative function simulation, and calculate the future change trend line of the remaining variable data and the future change of the remaining data For the real number interval between the trend lines, establish the threshold range between the two. For example, in this enterprise A, the threshold range of the proportion of scientific research personnel with undergraduates and below is 0-5%, and the source of abnormal data is generated according to the real number interval , according to the number of occurrences of abnormal data sources, compare the proportion of personnel with a bachelor’s degree or below in the proportion of abnormal data sources among scientific researchers and the data feature a of the standardized database, get the abnormal data cleaning instructions, and regularly clean the abnormal data; prompt The data of the scientific research personnel of the personnel below the undergraduate degree in the enterprise is abnormal, which needs to be cleaned up and adjusted;

According to the construction standard of the standardized database in the Internet, use the above method to sort out the remaining variable types and remaining elements, that is, to sort out the proportion of scientific research personnel with undergraduates and below, and select those with a degree of agreement with the construction standard of more than 85-95%. The remaining data information adopts the data circulation strategy to eliminate the data information that does not meet the standard, and reminds the remaining data information, automatically repairs, complements the normalized data characteristics under the current construction standard, and combines the data source to establish the current Work framework for normal operation of staffing under the enterprise standardized database;

Transfer the established staffing normal operation work framework to the enterprise work model architecture, send normal operation instructions intermittently, observe whether there is any abnormality in the enterprise operation data, and establish an enterprise work model architecture by editing the work logic under the normal operation work framework The data collection port in the remote terminal collects and monitors the daily operation data in real time, generates collection points and monitoring points, and analyzes the final index library through data coding.

Through the correlation between different data features, this method generates abnormal data sources according to the real digital interval, obtains abnormal data cleaning instructions, and regularly cleans abnormal data, so that enterprise databases can be constructed in a standardized mode, which is beneficial Establish a complete big data information index database, which greatly improves the decision-making efficiency of enterprises, and by automatically repairing the remaining data information that does not meet the standards, it can complement the normalized data characteristics under the current construction standards, and then establish the current enterprise standardized database Under the normal operation framework, the enterprise database is more standardized and streamlined, which is conducive to the precise management of information in various departments of the enterprise, and has certain market promotion prospects.

Although the embodiments of the present invention have been shown and described, those skilled in the art can understand that various changes, modifications and substitutions can be made to these embodiments without departing from the principle and spirit of the present invention. and modifications, the scope of the invention is defined by the appended claims and their equivalents.

Claims (5)

1. The method for constructing and applying the enterprise standardized database in the Xinjiang area is characterized by comprising the following steps of:

s1, acquiring a data feature a for constructing a standardized database and a data feature b under the current enterprise running state in the Internet, generating a data table under the correlation of the current data feature a and the data feature b, establishing a plurality of groups of data display models on the data table, and endowing the plurality of groups of data display models with unique numbers according to the number numbers of 1 and 2.

S2, carrying out deep analysis on the current data feature a and the data feature b according to the established multi-group data display model, generating variable types under relevance and MDS elements with the same attribute, carrying out data conversion on the variable types through a converter, and copying the variable types into the MDS elements to generate a data source under a standard format;

s3, inquiring the residual variable types under the condition that no relevance is generated and the residual elements with the same attribute are not generated, dividing and zoning the residual variable types and the residual elements on a data display model, simulating and demonstrating the residual variable data future change trend line under the residual variable types through the meditation function, simulating and demonstrating the residual variable data future change trend line under the residual elements through the guide function, calculating the real digital interval between the residual variable data future change trend line and the residual variable data future change trend line, and establishing a threshold range between the residual variable data future change trend line and the residual variable data future change trend line;

s4, carding the types of the residual variables and the residual elements according to the construction standard of the standardized database in the Internet, selecting residual data information which has the coincidence degree of more than 85-95% with the construction standard, removing the data information which does not reach the coincidence standard by adopting a data circulation strategy mode, automatically repairing the residual data information, supplementing the normalized data characteristics under the current construction standard, and establishing a normal operation working frame under the current enterprise standardized database by combining with a data source;

s5, transmitting the established normal operation work frame to an enterprise work model framework, intermittently transmitting normal operation instructions, observing whether abnormal operation data of the enterprise occur, establishing a data acquisition port in the enterprise work model framework by editing work logic under the normal operation work frame, acquiring and monitoring daily operation data in real time by a remote terminal acquisition mode, generating acquisition points and monitoring points, and analyzing a final index library by data coding;

generating an abnormal data generating source according to the real digital interval in the threshold range, comparing the abnormal data generating source with the data characteristic a of the standardized database according to the occurrence times of the abnormal data generating source to obtain an abnormal data cleaning instruction, and cleaning the abnormal data at fixed time;

after the data source is generated, searching data information under the current data characteristics through the distributed network probe, recording all searching paths of the network probe, and establishing basic logic under the current data information running track according to all the obtained searching paths;

after the normalized data features under the current construction standard are complemented, quality inspection and normalized data training are also carried out on the normalized data features, and a normalized data training set is obtained.

2. The method for building and applying the standardized database of the enterprises in the Xinjiang area according to claim 1, wherein the index library is used for forming a final index library after desensitizing and amplifying signals of daily operation data by collecting and monitoring daily operation data and creating a plurality of service terminals and service interfaces under the current daily operation data before analysis.

3. The method for constructing and applying the standardized database of the enterprises in the Xinjiang area according to claim 1, wherein after the acquisition points and the monitoring points are generated, a plurality of sets of characteristic information under the current data acquisition port are automatically carded out, and after the plurality of sets of characteristic information are rearranged and classified according to types and storage sizes, independent transmission channels under the plurality of sets of characteristic information are established.

4. The method for building and applying the standardized database of the enterprises in the Xinjiang area according to claim 1, wherein after the analysis of the index database, an index column under daily operation data is generated in the index database, a data trigger button is built according to corresponding data information in the index column, after an instruction is generated by the data trigger button, repeated data in the index database are automatically selected, additional parameters are generated, and formatting processing is carried out on the additional parameters.

5. The method for building and applying the standardized database of the enterprises in the Xinjiang area according to claim 1, wherein the normal operation work framework is created based on a plurality of data elements under a data source, wherein the data elements comprise a data length, a data name, a data type, a data format, a data starting position and a data terminal position.