CN112613711A - Water affair big data index management method and system based on six analysis methods - Google Patents
Water affair big data index management method and system based on six analysis methods Download PDFInfo
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Abstract
The invention provides a water affair big data index management method and a system based on a six-analysis method in the technical field of intelligent water affairs, wherein the method comprises the following steps: step S10, acquiring water affair data from each water affair system in real time; step S20, preprocessing the collected water affair data; step S30, creating a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and storing the water affair data with the set data labels in the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element; and step S40, carrying out multidimensional analysis on the water affair data stored in the database based on the data labels, and displaying the water affair data through a visual interface. The invention has the advantages that: the quality and the convenience of water affair data management have greatly been promoted.
Description
Technical Field
The invention relates to the technical field of intelligent water affairs, in particular to a water affair big data index management method and system based on a six-dimension analysis method.
Background
Along with the continuous popularization of intelligent hardware and informatization application, the water affair industry gradually develops towards intelligent water affairs, and massive water affair data are precipitated. The existing water affair enterprises mainly rely on relatively extensive financial indexes and company indexes to carry out statistics on water affair data, but the analyzability and the usability are poor, and the actual application requirements cannot be met.
Therefore, how to provide a water affair big data index management method and system based on the six analysis methods to improve the quality and convenience of water affair data management becomes a problem to be solved urgently.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a water affair big data index management method and system based on a six-analysis method, so that the quality and convenience of water affair data management are improved.
In a first aspect, the invention provides a water affair big data index management method based on a six-analysis method, which comprises the following steps:
step S10, acquiring water affair data from each water affair system in real time;
step S20, preprocessing the collected water affair data;
step S30, creating a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and storing the water affair data with the set data labels in the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element;
and step S40, carrying out multidimensional analysis on the water affair data stored in the database based on the data labels, and displaying the water affair data through a visual interface.
Further, the step S10 is specifically:
and (4) acquiring water affair data from each water affair system in real time by using an ETL tool.
Further, the step S20 specifically includes:
step S21, presetting a data transformation rule and a data filtering rule;
step S22, converting each water affair data collected from each water affair system into a uniform format by using the data conversion rule;
step S23, filtering each water affair data by using the data filtering rule;
and S24, performing MD5 value verification on the water affair data, and eliminating the water affair data which fails in verification.
Further, in step S30, the requirement elements at least include an enterprise operation domain, a production management domain, a pipe network operation domain, an engineering management domain, a business settlement domain, a customer service domain, and a financial management and control domain; the main elements at least comprise customers, users, accounts, sites, stations, facilities and main personnel; the facility at least comprises a valve, a pipeline, intelligent hardware, a meter and a pump set; the main personnel at least comprise customer service personnel, inspection personnel, charging personnel, meter reading personnel, scheduling personnel and management personnel; the regional elements at least comprise a water plant, a pump station, a business office, a company, a group, a DMA (direct memory access) cell, a pipe network partition and a meter reading area; the period elements include at least real time, minutes, hours, days, weeks, months, quarters, and years; the service elements at least comprise resources, quality, safety, income, cost, profit, appeal, efficiency, maintenance, equipment management, asset patrol, user scale, water quantity, water quality, operation and measurement; the logical elements include at least population, maximum, minimum, average, mode, variance, additions, inventories, churns, and accumulations.
Further, the step S40 is specifically:
and carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags through a rule engine to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface.
In a second aspect, the invention provides a water affair big data index management system based on a six-analysis method, which comprises the following modules:
the water affair data acquisition module is used for acquiring water affair data from each water affair system in real time;
the water affair data preprocessing module is used for preprocessing the acquired water affair data;
the data label setting module is used for establishing a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and then storing the water affair data with the set data labels into the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element;
and the water affair data analysis and display module is used for carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags and displaying the water affair data through a visual interface.
Further, the water affair data acquisition module specifically is:
and (4) acquiring water affair data from each water affair system in real time by using an ETL tool.
Further, the water affair data preprocessing module specifically includes:
the rule setting unit is used for presetting a data conversion rule and a data filtering rule;
the format conversion unit is used for converting the water affair data acquired from the water affair systems into a uniform format by using the data conversion rule;
the data filtering unit is used for filtering each water affair data by using the data filtering rule;
and the data checking unit is used for performing MD5 value checking on the water affair data and eliminating the water affair data which fails in checking.
Further, in the data tag setting module, the requirement elements at least include an enterprise management domain, a production management domain, a pipe network operation domain, an engineering management domain, a business settlement domain, a customer service domain and a financial management and control domain; the main elements at least comprise customers, users, accounts, sites, stations, facilities and main personnel; the facility at least comprises a valve, a pipeline, intelligent hardware, a meter and a pump set; the main personnel at least comprise customer service personnel, inspection personnel, charging personnel, meter reading personnel, scheduling personnel and management personnel; the regional elements at least comprise a water plant, a pump station, a business office, a company, a group, a DMA (direct memory access) cell, a pipe network partition and a meter reading area; the period elements include at least real time, minutes, hours, days, weeks, months, quarters, and years; the service elements at least comprise resources, quality, safety, income, cost, profit, appeal, efficiency, maintenance, equipment management, asset patrol, user scale, water quantity, water quality, operation and measurement; the logical elements include at least population, maximum, minimum, average, mode, variance, additions, inventories, churns, and accumulations.
Further, the water affair data analysis display module specifically comprises:
and carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags through a rule engine to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface.
The invention has the advantages that:
1. the method comprises the steps of collecting water affair data from each water affair system, preprocessing format conversion, filtering and verification, setting a data label of each preprocessed water affair data based on a created six-index system, storing the data label into a database, carrying out multi-dimensional analysis on the water affair data through a rule engine and the data label to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface, namely, the water affair data of each water affair system are integrated for unified management, and multi-dimensional big data analysis is carried out on the water affair data through the rule engine and the data label, so that the application value of the water affair data is fully played, a water affair manager can easily analyze and manage the water affair data without technical knowledge of data statistics and IT, and the quality and convenience of water affair data management are greatly improved.
2. By preprocessing format conversion, filtering and verification of the water affair data, unnecessary, defective and incomplete water affair data are removed and converted into a uniform data format, the data quality of the water affair data is greatly improved, and a solid foundation is provided for subsequent big data analysis.
3. By setting the data labels for the water affair data, the retrieval, classification analysis and multi-dimensional analysis of the water affair data in the later period are facilitated, and the application value of the water affair data is further improved.
Drawings
The invention will be further described with reference to the following examples with reference to the accompanying drawings.
FIG. 1 is a flowchart of a water utilities big data index management method based on how-six analysis method according to the present invention.
Fig. 2 is a schematic structural diagram of a water affair big data index management system based on a six-analysis method according to the present invention.
FIG. 3 is a logical diagram of the six-index architecture of the present invention.
Detailed Description
The technical scheme in the embodiment of the application has the following general idea: the water affair data management method comprises the steps of collecting the water affair data from each water affair system, preprocessing the water affair data through format conversion, filtering and verification, setting a data label of the preprocessed water affair data based on a created six-index system, storing the data label into a database, carrying out multi-dimensional analysis and graphic display on the water affair data through a rule engine and the data label, namely carrying out unified management on the water affair data of each water affair system, unifying index apertures of the water affair data, carrying out data analysis through the rule engine which is easy to operate, and carrying out chart display through a humanized interface so as to improve the quality and convenience of water affair data management.
Referring to fig. 1 to 3, a preferred embodiment of a water affair big data index management method based on a six-analysis method according to the present invention includes the following steps:
step S10, acquiring water affair data from each water affair system in real time; the water service system at least comprises a revenue system, a meter reading system, a customer service system, a pipe network GIS system, a water plant SCADA system and a pipe network inspection system;
step S20, preprocessing the collected water affair data;
step S30, creating a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and storing the water affair data with the set data labels in the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element; the water affair data of each water affair system are stored in the database, so that the maintenance, sharing and application of the water affair data are facilitated, and the management cost of the water affair data is reduced;
for example, the user billing data collected from the revenue subsystem of the water service system, and the settable data tag includes demand elements (enterprise business domain, business settlement domain, customer service domain), area elements (business office, company, meter reading area), main elements (user, account, and toll collector), business elements (water volume class, income class, and metering class), logic elements (total, average), and cycle elements (month and year).
And step S40, carrying out multidimensional analysis on the water affair data stored in the database based on the data labels, and displaying the water affair data through a visual interface.
The step S10 specifically includes:
acquiring water affair data from each water affair system in real time by using an ETL (data warehouse technology) tool; and acquiring the water affair data in real time, so that the database always keeps the latest data state.
The step S20 specifically includes:
step S21, presetting a data transformation rule and a data filtering rule;
step S22, converting each water affair data collected from each water affair system into a uniform format by using the data conversion rule; the data are converted into a uniform format so as to facilitate later data analysis and processing;
step S23, filtering each water affair data by using the data filtering rule;
and S24, performing MD5 value verification on the water affair data, and eliminating the water affair data which fails in verification. Checking the MD5 value, namely calculating the MD5 value of the water affair data, comparing whether the calculated MD5 value is consistent with the MD5 value carried by the water affair data, and if the calculated MD5 value is consistent with the MD5 value carried by the water affair data, passing the check; if the two are not consistent, the verification is not passed; the MD5 value check can judge the integrity of the water business data and avoid the water business data from being distorted or lost.
In step S30, the requirement elements at least include an enterprise management domain, a production management domain, a pipe network operation domain, an engineering management domain, a business settlement domain, a customer service domain, and a financial management and control domain; the main elements at least comprise customers, users, accounts, sites, stations, facilities and main personnel; the facility at least comprises a valve, a pipeline, intelligent hardware, a meter and a pump set; the main personnel at least comprise customer service personnel, inspection personnel, charging personnel, meter reading personnel, scheduling personnel and management personnel; the regional elements at least comprise a water plant, a pump station, a business office, a company, a group, a DMA (direct memory access) cell, a pipe network partition and a meter reading area; the period elements include at least real time, minutes, hours, days, weeks, months, quarters, and years; the service elements at least comprise resources, quality, safety, income, cost, profit, appeal, efficiency, maintenance, equipment management, asset patrol, user scale, water quantity, water quality, operation and measurement; the logical elements include at least population, maximum (highest), minimum (lowest), average, mode, variance, additions, inventories, churns, and accumulations.
The step S40 specifically includes:
and carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags through a rule engine to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface.
When the method is specifically implemented, a pair of public key and private key can be created, the private key is used for encrypting the water affair data of the database, and when a user logs in the database through an account number and a password, the public key is used for decrypting the water affair data to analyze the water affair data, so that the safety of the water affair data is improved.
The invention relates to a water affair big data index management system based on a six analysis method, which comprises the following modules:
the water affair data acquisition module is used for acquiring water affair data from each water affair system in real time; the water service system at least comprises a revenue system, a meter reading system, a customer service system, a pipe network GIS system, a water plant SCADA system and a pipe network inspection system;
the water affair data preprocessing module is used for preprocessing the acquired water affair data;
the data label setting module is used for establishing a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and then storing the water affair data with the set data labels into the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element; the water affair data of each water affair system are stored in the database, so that the maintenance, sharing and application of the water affair data are facilitated, and the management cost of the water affair data is reduced;
for example, the user billing data collected from the revenue subsystem of the water service system, and the settable data tag includes demand elements (enterprise business domain, business settlement domain, customer service domain), area elements (business office, company, meter reading area), main elements (user, account, and toll collector), business elements (water volume class, income class, and metering class), logic elements (total, average), and cycle elements (month and year).
And the water affair data analysis and display module is used for carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags and displaying the water affair data through a visual interface.
The water affair data acquisition module specifically is:
acquiring water affair data from each water affair system in real time by using an ETL (data warehouse technology) tool; and acquiring the water affair data in real time, so that the database always keeps the latest data state.
The water affair data preprocessing module specifically comprises:
the rule setting unit is used for presetting a data conversion rule and a data filtering rule;
the format conversion unit is used for converting the water affair data acquired from the water affair systems into a uniform format by using the data conversion rule; the data are converted into a uniform format so as to facilitate later data analysis and processing;
the data filtering unit is used for filtering each water affair data by using the data filtering rule;
and the data checking unit is used for performing MD5 value checking on the water affair data and eliminating the water affair data which fails in checking. Checking the MD5 value, namely calculating the MD5 value of the water affair data, comparing whether the calculated MD5 value is consistent with the MD5 value carried by the water affair data, and if the calculated MD5 value is consistent with the MD5 value carried by the water affair data, passing the check; if the two are not consistent, the verification is not passed; the MD5 value check can judge the integrity of the water business data and avoid the water business data from being distorted or lost.
In the data label setting module, the requirement elements at least comprise an enterprise management domain, a production management domain, a pipe network operation domain, an engineering management domain, a business settlement domain, a customer service domain and a financial management and control domain; the main elements at least comprise customers, users, accounts, sites, stations, facilities and main personnel; the facility at least comprises a valve, a pipeline, intelligent hardware, a meter and a pump set; the main personnel at least comprise customer service personnel, inspection personnel, charging personnel, meter reading personnel, scheduling personnel and management personnel; the regional elements at least comprise a water plant, a pump station, a business office, a company, a group, a DMA (direct memory access) cell, a pipe network partition and a meter reading area; the period elements include at least real time, minutes, hours, days, weeks, months, quarters, and years; the service elements at least comprise resources, quality, safety, income, cost, profit, appeal, efficiency, maintenance, equipment management, asset patrol, user scale, water quantity, water quality, operation and measurement; the logical elements include at least population, maximum (highest), minimum (lowest), average, mode, variance, additions, inventories, churns, and accumulations.
The water affair data analysis display module specifically comprises:
and carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags through a rule engine to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface.
When the method is specifically implemented, a pair of public key and private key can be created, the private key is used for encrypting the water affair data of the database, and when a user logs in the database through an account number and a password, the public key is used for decrypting the water affair data to analyze the water affair data, so that the safety of the water affair data is improved.
In summary, the invention has the advantages that:
1. the method comprises the steps of collecting water affair data from each water affair system, preprocessing format conversion, filtering and verification, setting a data label of each preprocessed water affair data based on a created six-index system, storing the data label into a database, carrying out multi-dimensional analysis on the water affair data through a rule engine and the data label to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface, namely, the water affair data of each water affair system are integrated for unified management, and multi-dimensional big data analysis is carried out on the water affair data through the rule engine and the data label, so that the application value of the water affair data is fully played, a water affair manager can easily analyze and manage the water affair data without technical knowledge of data statistics and IT, and the quality and convenience of water affair data management are greatly improved.
2. By preprocessing format conversion, filtering and verification of the water affair data, unnecessary, defective and incomplete water affair data are removed and converted into a uniform data format, the data quality of the water affair data is greatly improved, and a solid foundation is provided for subsequent big data analysis.
3. By setting the data labels for the water affair data, the retrieval, classification analysis and multi-dimensional analysis of the water affair data in the later period are facilitated, and the application value of the water affair data is further improved.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.
Claims (10)
1. A water affair big data index management method based on a six-analysis method is characterized by comprising the following steps: the method comprises the following steps:
step S10, acquiring water affair data from each water affair system in real time;
step S20, preprocessing the collected water affair data;
step S30, creating a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and storing the water affair data with the set data labels in the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element;
and step S40, carrying out multidimensional analysis on the water affair data stored in the database based on the data labels, and displaying the water affair data through a visual interface.
2. The water affair big data index management method based on the six-analysis method as claimed in claim 1, wherein: the step S10 specifically includes:
and (4) acquiring water affair data from each water affair system in real time by using an ETL tool.
3. The water affair big data index management method based on the six-analysis method as claimed in claim 1, wherein: the step S20 specifically includes:
step S21, presetting a data transformation rule and a data filtering rule;
step S22, converting each water affair data collected from each water affair system into a uniform format by using the data conversion rule;
step S23, filtering each water affair data by using the data filtering rule;
and S24, performing MD5 value verification on the water affair data, and eliminating the water affair data which fails in verification.
4. The water affair big data index management method based on the six-analysis method as claimed in claim 1, wherein: in step S30, the requirement elements at least include an enterprise management domain, a production management domain, a pipe network operation domain, an engineering management domain, a business settlement domain, a customer service domain, and a financial management and control domain; the main elements at least comprise customers, users, accounts, sites, stations, facilities and main personnel; the facility at least comprises a valve, a pipeline, intelligent hardware, a meter and a pump set; the main personnel at least comprise customer service personnel, inspection personnel, charging personnel, meter reading personnel, scheduling personnel and management personnel; the regional elements at least comprise a water plant, a pump station, a business office, a company, a group, a DMA (direct memory access) cell, a pipe network partition and a meter reading area; the period elements include at least real time, minutes, hours, days, weeks, months, quarters, and years; the service elements at least comprise resources, quality, safety, income, cost, profit, appeal, efficiency, maintenance, equipment management, asset patrol, user scale, water quantity, water quality, operation and measurement; the logical elements include at least population, maximum, minimum, average, mode, variance, additions, inventories, churns, and accumulations.
5. The water affair big data index management method based on the six-analysis method as claimed in claim 1, wherein: the step S40 specifically includes:
and carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags through a rule engine to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface.
6. A water affair big data index management system based on a six analysis method is characterized in that: the system comprises the following modules:
the water affair data acquisition module is used for acquiring water affair data from each water affair system in real time;
the water affair data preprocessing module is used for preprocessing the acquired water affair data;
the data label setting module is used for establishing a six-index system and a database, setting data labels of the preprocessed water affair data based on the six-index system, and then storing the water affair data with the set data labels into the database; the six-index system comprises a requirement element, a main element, a region element, a period element, a business element and a logic element;
and the water affair data analysis and display module is used for carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags and displaying the water affair data through a visual interface.
7. The water affair big data index management system based on the six-analysis method as claimed in claim 6, wherein: the water affair data acquisition module specifically is:
and (4) acquiring water affair data from each water affair system in real time by using an ETL tool.
8. The water affair big data index management system based on the six-analysis method as claimed in claim 6, wherein: the water affair data preprocessing module specifically comprises:
the rule setting unit is used for presetting a data conversion rule and a data filtering rule;
the format conversion unit is used for converting the water affair data acquired from the water affair systems into a uniform format by using the data conversion rule;
the data filtering unit is used for filtering each water affair data by using the data filtering rule;
and the data checking unit is used for performing MD5 value checking on the water affair data and eliminating the water affair data which fails in checking.
9. The water affair big data index management system based on the six-analysis method as claimed in claim 6, wherein: in the data label setting module, the requirement elements at least comprise an enterprise management domain, a production management domain, a pipe network operation domain, an engineering management domain, a business settlement domain, a customer service domain and a financial management and control domain; the main elements at least comprise customers, users, accounts, sites, stations, facilities and main personnel; the facility at least comprises a valve, a pipeline, intelligent hardware, a meter and a pump set; the main personnel at least comprise customer service personnel, inspection personnel, charging personnel, meter reading personnel, scheduling personnel and management personnel; the regional elements at least comprise a water plant, a pump station, a business office, a company, a group, a DMA (direct memory access) cell, a pipe network partition and a meter reading area; the period elements include at least real time, minutes, hours, days, weeks, months, quarters, and years; the service elements at least comprise resources, quality, safety, income, cost, profit, appeal, efficiency, maintenance, equipment management, asset patrol, user scale, water quantity, water quality, operation and measurement; the logical elements include at least population, maximum, minimum, average, mode, variance, additions, inventories, churns, and accumulations.
10. The water affair big data index management system based on the six-analysis method as claimed in claim 6, wherein: the water affair data analysis display module specifically comprises:
and carrying out multi-dimensional analysis on the water affair data stored in the database based on the data tags through a rule engine to generate a multi-dimensional analysis report or a knowledge map, and displaying the multi-dimensional analysis report or the knowledge map through a visual interface.
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