Gas data analysis method, system and terminal based on data architecture platform

Abstract

The invention discloses a gas data analysis method and system based on a data architecture platform and a terminal, and the method comprises the steps: obtaining to-be-processed data of a gas platform, carrying out the preprocessing of the to-be-processed data, and obtaining target to-be-processed data; according to the data architecture platform, performing function demand analysis on the target to-be-processed data to obtain a first analysis result, performing gas pipe network analysis on the target to-be-processed data to obtain a second analysis result, and performing data security analysis on the target to-be-processed data to obtain a third analysis result; and obtaining a target analysis result according to the first analysis result, the second analysis result and the third analysis result, and displaying the target analysis result. According to the invention, the data standard can be unified, so that the data can be integrated and shared conveniently, the efficiency of data calling and data analysis is improved, and the safety of gas use is also improved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a gas data analysis method, system, terminal and computer-readable storage medium based on a data architecture platform. Background Art

[0002] In recent years, data has become an important production factor and strategic resource in various industries. In the gas business, it is necessary to make better use of data resources and achieve goals such as business process optimization, intelligent decision-making, and risk management through analysis and mining.

[0003] At present, the traditional data management model can no longer meet the current rapid development needs. Although a large amount of business system data assets have been accumulated, these data are still stored in various business systems. The lack of unified data standards makes it difficult to integrate and share these data, resulting in the process of data call and data analysis becoming difficult and inefficient, thus affecting the safety of gas use.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The main purpose of the present invention is to provide a gas data analysis method based on a data architecture platform, aiming to solve the problem that the prior art lacks a unified data standard, making data difficult to integrate and share, resulting in the difficulty and low efficiency of data call and data analysis, thereby affecting the safety of gas use.

[0006] To achieve the above object, the present invention provides a gas data analysis method, system and terminal based on a data architecture platform. The gas data analysis method based on the data architecture platform comprises the following steps:

[0007] Acquire the data to be processed of the gas platform, pre-process the data to be processed, and obtain target data to be processed;

[0008] Performing a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, performing a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and performing a data security analysis on the target data to be processed to obtain a third analysis result;

[0009] A target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed.

[0010] Optionally, the gas data analysis method based on the data architecture platform, wherein the data to be processed of the gas platform is obtained, the data to be processed is preprocessed to obtain target data to be processed, and the method further includes:

[0011] Obtain resource information of the gas platform, wherein the resource information includes cloud platform resources, server resources, network resources, storage resources, computer room resources and security resources;

[0012] Acquire processing requirements of the gas platform, wherein the processing requirements include data integration, data governance, data analysis, data services and data applications;

[0013] A corresponding data architecture platform is constructed according to the resource information and the processing requirements.

[0014] Optionally, the acquiring the data to be processed of the gas platform and preprocessing the data to be processed to obtain target data to be processed specifically includes:

[0015] Acquire a data collection range, and collect data on the gas platform according to the data range to obtain data to be processed, wherein the data to be processed includes unstructured data, semi-structured data, structured data, and real-time data;

[0016] Obtain target data standards, perform standardization processing on the data to be processed according to the target data standards to obtain standardized data, and perform data cleaning on the standardized data to obtain target data to be processed, wherein the standardization processing includes data definition, data classification and format conversion.

[0017] Optionally, the gas data analysis method based on the data architecture platform, wherein the function requirement analysis of the target data to be processed is performed according to the data architecture platform to obtain a first analysis result, specifically including:

[0018] Performing data storage analysis on the target data to be processed according to the data computing storage platform of the data architecture platform to obtain storage analysis results;

[0019] Analyzing the data quality of the target data to be processed to obtain a quality analysis result, and analyzing the data link of the target data to be processed to obtain a link analysis result;

[0020] The storage analysis result, the quality analysis result and the link analysis result are combined to obtain a first analysis result of the target data to be processed.

[0021] Optionally, the gas data analysis method based on the data architecture platform, wherein the gas pipeline network analysis is performed on the target data to be processed to obtain the second analysis result, specifically includes:

[0022] Performing pipe network data screening on the target data to be processed to obtain target pipe network data, and establishing a corresponding pipe network data analysis model according to the target pipe network data;

[0023] Performing pipeline failure analysis on the target data to be processed according to the pipeline network data analysis model to obtain pipeline analysis results, and performing gas supply forecasting analysis on the target data to be processed to obtain gas supply usage results;

[0024] The pipeline analysis result and the gas package utility result are combined to obtain a second analysis result.

[0025] Optionally, the gas data analysis method based on the data architecture platform, wherein the data security analysis is performed on the target data to be processed to obtain a third analysis result, specifically including:

[0026] Performing IP access analysis and port access analysis on the target data to be processed to obtain network security results, and performing data audit on the target data to be processed to obtain data security results;

[0027] Performing application layer security analysis on the target data to be processed to obtain application security results, wherein the application layer security analysis includes user authentication analysis, data transmission analysis and user authority analysis;

[0028] The network security result, the data security result and the application security result are combined to obtain a third analysis result.

[0029] Optionally, the gas data analysis method based on the data architecture platform, wherein the target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed, and then further includes:

[0030] If there is alarm information in the target analysis result, historical alarm information of the target analysis result within a preset time is extracted and displayed, wherein the historical alarm information includes alarm time, alarm status, alarm strategy, alarm object and alarm content.

[0031] Optionally, the gas data analysis method based on the data architecture platform, wherein the gas data analysis system based on the data architecture platform includes:

[0032] A data acquisition module is used to acquire the data to be processed of the gas platform, pre-process the data to be processed, and obtain target data to be processed;

[0033] A data analysis module, configured to perform a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, perform a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and perform a data security analysis on the target data to be processed to obtain a third analysis result;

[0034] A result display module is used to obtain a target analysis result according to the first analysis result, the second analysis result and the third analysis result, and to display the target analysis result.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a gas data analysis program based on a data architecture platform stored in the memory and executable on the processor, wherein the gas data analysis program based on the data architecture platform, when executed by the processor, implements the steps of the gas data analysis method based on the data architecture platform as described above.

[0036] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a gas data analysis program based on a data architecture platform, and when the gas data analysis program based on the data architecture platform is executed by a processor, the steps of the gas data analysis method based on the data architecture platform as described above are implemented.

[0037] In the present invention, the data to be processed of the gas platform is obtained, the data to be processed is preprocessed to obtain the target data to be processed; the functional requirements of the target data to be processed are analyzed according to the data architecture platform to obtain the first analysis result, the gas pipeline network analysis of the target data to be processed is performed to obtain the second analysis result, the data security analysis of the target data to be processed is performed to obtain the third analysis result; the target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed. The present invention can unify data standards to facilitate data integration and sharing, improve the efficiency of data calling and data analysis, and also improve the safety of gas use. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a preferred embodiment of the gas data analysis method based on the data architecture platform in the present invention;

[0039] Figure 2 It is a structural diagram of a preferred embodiment of a gas data analysis system based on a data architecture platform in the present invention;

[0040] Figure 3 It is a schematic diagram of the operating environment of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0042] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0043] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0044] The gas data analysis method based on the data architecture platform described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the gas data analysis method based on the data architecture platform includes the following steps:

[0045] Step S10: Acquire the data to be processed of the gas platform, and pre-process the data to be processed to obtain target data to be processed.

[0046] The step S10 comprises:

[0047] Step S11, acquiring a data collection range, and collecting data on the gas platform according to the data range to obtain data to be processed, wherein the data to be processed includes unstructured data, semi-structured data, structured data and real-time data;

[0048] Step S12, obtaining the target data standard, performing standardization processing on the data to be processed according to the target data standard to obtain standardized data, and performing data cleaning on the standardized data to obtain the target data to be processed, wherein the standardization processing includes data definition, data classification and format conversion.

[0049] Specifically, in an embodiment of the present invention, before analyzing the corresponding data in the gas platform, it is necessary to build a corresponding data architecture platform, specifically, obtain resource information of the gas platform, wherein the resource information includes cloud platform resources, server resources, network resources, storage resources, computer room resources and security resources; obtain processing requirements of the gas platform, wherein the processing requirements include data integration, data governance, data analysis, data services and data applications; build a corresponding data architecture platform according to the resource information and the processing requirements, and this data architecture platform includes a data computing and storage platform, a data development platform, a data governance platform, a data service platform and a data visualization platform.

[0050] Among them, the data computing and storage platform can first optimize the writing scenario and the query performance of massive data. The column storage supports the design of adding auxiliary row storage tables (for example, stash auxiliary tables), and supports the Auto StashMerge process to automatically merge the data in the stash row storage table into a column storage format, which is transparent to the user; secondly, it supports the approval of application instances and the adjustment of node IPs, among which the deletion of instances supports secure deletion using password verification; then, it also supports exporting the instance node list to a file, including node name, IP port, plane, node master and standby roles, CPU usage (number of cores), CPU usage, memory usage, disk usage, bin / data directory and environment variables, etc.; finally, it supports efficient one-click health checks on instances, for example, one-click quick completion of instance distributed routing, connectivity between CN / DN, master and standby delays, blocking locks, transaction age, node core files, machine networks, disk usage, number of alarms, etc.

[0051] The data development platform supports project creation, change and termination, and can maintain project information; supports project branch management, collaborative data development with multiple people, supports operations such as baseline building, branch comparison, branch merging, branch freezing, packaging and publishing; supports demand management, defines and assigns responsibilities for requirements, and binds them to synchronization tasks and development tasks to ensure the implementation of each requirement; supports data research, supports the classification and definition of source systems by business departments; also supports data architecture and development, specifically including supporting data architecture construction, graphically constructing data architecture modes such as lake-warehouse integration, lake-warehouse separation, data lake, data warehouse, etc., and supports custom data architecture and data development without data architecture; supports data model management, supports the selection of table structures in data sources for reverse engineering creation; supports unified management of standardized data development processes, supports template mode and script mode, and supports switching; supports the execution of configured synchronization tasks or development tasks according to a certain period or rule, supports custom task groups, and realizes the management of scheduling tasks.

[0052] The data governance platform first supports the construction and management of data standards, specifically, supports the definition and management of basic standards, indicator standards, business terms, dimension standards and public codes; supports naming specifications, defines and manages table-level and field-level naming rules; supports standard application functions mainly for business personnel, mainly including the application of root words, codes, and data standards. Secondly, it supports data standard maintenance and data quality management. The data standard maintenance specifically includes supporting the management and maintenance of root word libraries, public codes, and basic data standards; supports the definition and configuration of basic information, value domain information, sensitivity level, importance level, metadata mapping relationship and other related information of data basic standards from the dimensions of business, technology, and management; the data instruction management specifically includes supporting the construction of data quality modules, providing custom quality rule construction in addition to general rule templates to meet the verification requirements outside the general rule templates, and supporting the collection, subscription, and tagging of inspection rules; supports the process configuration of data quality management, supports the construction of data quality tasks from metadata, business systems, databases, etc., and can verify and generate quality reports according to the scheduling cycle to display the verification results.

[0053] The data service platform supports multiple graphical logic components, provides process control, data processing, error capture and log, parallel and concurrent, functional and other logic components, and realizes visual orchestration of complex business through logic components; supports online unit debugging, online application debugging, supports concurrency and exception handling components; supports interface mock, editing interface function and parameter testing; and also supports storage methods such as built-in tables, hashes, and strings.

[0054] The data visualization platform supports visualization components and editing functions and operation and maintenance and data management functions. Specifically, the visualization components and editing functions use components to achieve data linkage filtering, page switching and jumping, menus, navigation, search and other user interaction effects; it also provides custom chart components to achieve secondary development chart capabilities. Users develop the required chart effects according to the platform specifications, build WebService to publish, or deploy the code to the specified location of the platform through platform operation and maintenance. When users use custom charts, they configure data according to platform specifications. The operation and maintenance and data management functions can provide functions such as user management, permission management, briefing management, template management, resource management (for example, font management, image management, etc.), message center and log statistics.

[0055] Afterwards, it is necessary to obtain the data collection scope, and collect data from the gas platform within the data scope through data collection technology (for example, Flume data collection technology) to obtain the data to be processed, wherein the data to be processed includes unstructured data, semi-structured data, structured data and real-time data, so as to realize the collection of various types of multi-source heterogeneous data provided by the source data layer, and complete the distributed storage of various types of data; then, obtain the target data standard of the data governance platform, wherein the target data standard is a set of management systems, control processes, and technical tools, which are a unified benchmark in data resource development, and perform operations such as adding, importing, querying, and modifying standard types such as master data standards and public code standards, and use unified data definition, data classification, record format and conversion, encoding, etc. to realize data standardization, that is, the data to be processed is standardized according to the target data standard to obtain standardized data, wherein the standardized processing includes data definition, data classification and format conversion, and the standardized data is cleaned to obtain the target data to be processed.

[0056] Step S20: performing a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, performing a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and performing a data security analysis on the target data to be processed to obtain a third analysis result.

[0057] The step S20 comprises:

[0058] Step S21: Perform data storage analysis on the target data to be processed according to the data computing storage platform of the data architecture platform to obtain storage analysis results;

[0059] Step S22, analyzing the data quality of the target data to be processed to obtain a quality analysis result, and analyzing the data link of the target data to be processed to obtain a link analysis result;

[0060] Step S23, combining the storage analysis result, the quality analysis result and the link analysis result to obtain a first analysis result of the target data to be processed;

[0061] Step S24, performing pipe network data screening on the target data to be processed to obtain target pipe network data, and establishing a corresponding pipe network data analysis model according to the target pipe network data;

[0062] Step S25: performing pipeline failure analysis on the target data to be processed according to the pipeline network data analysis model to obtain pipeline analysis results, and performing gas supply forecasting analysis on the target data to be processed to obtain gas supply usage results;

[0063] Step S26, combining the pipeline analysis result and the gas package utility result to obtain a second analysis result;

[0064] Step S27, performing IP access analysis and port access analysis on the target data to be processed to obtain a network security result, and performing data audit on the target data to be processed to obtain a data security result;

[0065] Step S28: performing application layer security analysis on the target data to be processed to obtain application security results, wherein the application layer security analysis includes user authentication analysis, data transmission analysis and user authority analysis;

[0066] Step S29: Combine the network security result, the data security result and the application security result to obtain a third analysis result.

[0067] Specifically, in an embodiment of the present invention, after obtaining the target data to be processed, it is necessary to perform data analysis on the target data to be processed. Specifically, data storage analysis is performed on the target data to be processed according to the data computing and storage platform of the data architecture platform to obtain storage analysis results. The purpose is to integrate multiple data from different sources, truly realize data management, and provide a distributed ultra-large-scale online relational data warehouse. The business scenario is for online high-performance data analysis. If unified cluster management is required, cluster supply, management and monitoring are supported; centralized management of multiple services, multiple clusters and remote cluster management are supported; if online analytical processing is required, multiple pairs of operands can be calculated at one time, and the execution engine adopts a volcano model to realize batch reading and batch processing by processing a group of tuples at a time; the data quality of the target data to be processed is analyzed to obtain a quality analysis result, and the data quality will be monitored in the process, and various data quality situations will be monitored and statistically alarmed, and the data link of the target data to be processed is analyzed to obtain a link analysis result; the storage analysis result, the quality analysis result and the link analysis result are combined to obtain a first analysis result of the target data to be processed.

[0068] Afterwards, pipeline failure analysis is needed to provide important support for the optimal design of urban gas pipeline transmission and distribution systems, gas storage facility selection and design, energy planning and scheduling, environmental protection and energy conservation, emergency response and safety management, etc., which will help improve the operating efficiency of the gas pipeline network and make it safer and more stable. Specifically, the target data to be processed is screened for pipeline network data to obtain target pipeline network data, and a corresponding pipeline network data analysis model is established according to the target pipeline network data; the target data to be processed is subjected to pipeline failure analysis according to the pipeline network data analysis model to obtain pipeline analysis results, through which the weak links, key areas and important nodes of the pipeline network can be more accurately understood, providing an important basis for the optimal design of the pipeline transmission and distribution network, which is helpful to improve the design level and operation efficiency of the pipeline network and reduce the occurrence rate of safety risk accidents; through the pipeline analysis results, the pipeline network can be reasonably optimized, the pipeline network facilities that will cause a wide range of impacts can be reduced, and the amount of gas loss caused by failures can be reduced; through the pipeline analysis results, the inspection and maintenance plans can be better planned, thereby improving the inspection and maintenance efficiency, reducing losses, and improving service quality; through the pipeline analysis results, the key links of the pipeline network can be better identified, and the management, safety reinforcement and inspection and protection of the key links can be strengthened in a targeted manner, and effective technical means can be strengthened for key parts, thereby reducing the accident rate, reducing the impact range after the accident, and improving the emergency response capability after the accident, thereby improving the overall operation efficiency and safety of the pipeline network.

[0069] A gas supply forecast analysis is performed on the target data to be processed to obtain a gas supply usage result. The gas supply usage result can be used to determine a reasonable gas storage scale and method to meet the gas demand in different time periods and different regions; the gas supply usage result can be used to reasonably plan the gas supply and dispatch gas resources to reasonably ensure the supply of gas for users' basic living needs and improve the ability to respond to sudden safety incidents; it can also optimize the gas supply structure, improve energy utilization efficiency, and reduce the impact on the environment; then, the pipeline analysis result and the gas package usage result are combined to obtain a second analysis result.

[0070] Afterwards, in order to prevent the hardware, software and data of data information from being destroyed, changed or leaked due to accidental or malicious reasons, it is necessary to conduct security demand analysis, including network layer security analysis, data layer security analysis and application layer security analysis; for network layer security analysis, specifically, IP access analysis and port access analysis are performed on the target data to be processed to obtain network security results. If there are abnormalities in the network security results, IP access control, MAC address binding and port access control can be performed to enhance the security of the network layer, wherein the IP access control is to isolate the network from the link layer or restrict network access through mechanisms such as ACL access control rules and WLAN configured on switches or routers, thereby enhancing the security of the network layer; the MAC address binding is to set the MAC address binding of the switch to the server and maintenance personnel's equipment, prohibiting illegal and unauthorized devices from connecting to the data platform network, and isolating illegal operations from network access points; the port access control is to perform hardware and software access control, MAC address binding and port access control. Firewall equipment is used to configure security access rules to prevent illegal intrusion, thereby protecting the security of the network layer; for data layer security analysis, specifically, in order to prevent internal personnel from deliberately modifying data by using their responsibilities and authority, a database audit function is set for key data tables to record all added records, deleted records and modified records for key tables, and data audits are regularly performed on the target data to be processed to obtain data security results and promptly discover illegal data operations by internal personnel; for application layer security analysis, the application layer mainly provides WebService services for business systems to access the database, and application layer security is mainly on WebService. Specifically, an application layer security analysis is performed on the target data to be processed to obtain application security results, wherein the application layer security analysis includes user authentication analysis, data transmission analysis and user authority analysis, and then the network security result, the data security result and the application security result are combined to obtain a third analysis result.

[0071] Step S30: obtain a target analysis result according to the first analysis result, the second analysis result and the third analysis result, and display the target analysis result.

[0072] Specifically, a target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed through a data visualization platform of a data architecture platform.

[0073] Furthermore, if there is alarm information in the target analysis result, the historical alarm information of the target analysis result within a preset time is extracted and displayed, wherein the historical alarm information includes the alarm time, alarm status, alarm strategy, alarm object and alarm content, so as to remind relevant technical personnel to handle it in a timely manner.

[0074] Furthermore, if Figure 2 As shown, based on the above-mentioned gas data analysis method based on the data architecture platform, the present invention also provides a gas data analysis system based on the data architecture platform, and the gas data analysis system based on the data architecture platform includes:

[0075] The data acquisition module 51 is used to acquire the data to be processed of the gas platform, pre-process the data to be processed, and obtain target data to be processed;

[0076] The data analysis module 52 is used to perform a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, perform a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and perform a data security analysis on the target data to be processed to obtain a third analysis result;

[0077] The result display module 53 is used to obtain a target analysis result according to the first analysis result, the second analysis result and the third analysis result, and to display the target analysis result.

[0078] Furthermore, if Figure 3 As shown, based on the above-mentioned gas data analysis method based on the data architecture platform, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0079] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a gas data analysis program 40 based on a data architecture platform is stored on the memory 20, and the gas data analysis program 40 based on the data architecture platform can be executed by the processor 10, thereby realizing the gas data analysis method based on the data architecture platform in the present application.

[0080] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the gas data analysis method based on the data architecture platform.

[0081] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components of the terminal communicate with each other via a system bus.

[0082] In one embodiment, when the processor 10 executes the program 40 for gas data analysis based on the data architecture platform in the memory 20, the following steps are implemented:

[0083] Acquire the data to be processed of the gas platform, pre-process the data to be processed, and obtain target data to be processed;

[0084] Performing a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, performing a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and performing a data security analysis on the target data to be processed to obtain a third analysis result;

[0085] A target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed.

[0086] The step of obtaining the data to be processed of the gas platform and preprocessing the data to be processed to obtain target data to be processed may also include:

[0087] Obtain resource information of the gas platform, wherein the resource information includes cloud platform resources, server resources, network resources, storage resources, computer room resources and security resources;

[0088] Acquire processing requirements of the gas platform, wherein the processing requirements include data integration, data governance, data analysis, data services and data applications;

[0089] A corresponding data architecture platform is constructed according to the resource information and the processing requirements.

[0090] The step of obtaining the data to be processed of the gas platform and preprocessing the data to be processed to obtain target data to be processed specifically includes:

[0091] Acquire a data collection range, and collect data on the gas platform according to the data range to obtain data to be processed, wherein the data to be processed includes unstructured data, semi-structured data, structured data, and real-time data;

[0092] Obtain target data standards, perform standardization processing on the data to be processed according to the target data standards to obtain standardized data, and perform data cleaning on the standardized data to obtain target data to be processed, wherein the standardization processing includes data definition, data classification and format conversion.

[0093] The step of performing functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result specifically includes:

[0094] Performing data storage analysis on the target data to be processed according to the data computing storage platform of the data architecture platform to obtain storage analysis results;

[0095] Analyzing the data quality of the target data to be processed to obtain a quality analysis result, and analyzing the data link of the target data to be processed to obtain a link analysis result;

[0096] The storage analysis result, the quality analysis result and the link analysis result are combined to obtain a first analysis result of the target data to be processed.

[0097] The gas pipeline network analysis is performed on the target data to be processed to obtain a second analysis result, which specifically includes:

[0098] Performing pipe network data screening on the target data to be processed to obtain target pipe network data, and establishing a corresponding pipe network data analysis model according to the target pipe network data;

[0099] Performing pipeline failure analysis on the target data to be processed according to the pipeline network data analysis model to obtain pipeline analysis results, and performing gas supply forecasting analysis on the target data to be processed to obtain gas supply usage results;

[0100] The pipeline analysis result and the gas package utility result are combined to obtain a second analysis result.

[0101] The performing of data security analysis on the target data to be processed to obtain a third analysis result specifically includes:

[0102] Performing IP access analysis and port access analysis on the target data to be processed to obtain network security results, and performing data audit on the target data to be processed to obtain data security results;

[0103] Performing application layer security analysis on the target data to be processed to obtain application security results, wherein the application layer security analysis includes user authentication analysis, data transmission analysis and user authority analysis;

[0104] The network security result, the data security result and the application security result are combined to obtain a third analysis result.

[0105] The step of obtaining a target analysis result according to the first analysis result, the second analysis result and the third analysis result, and displaying the target analysis result, further includes:

[0106] If there is alarm information in the target analysis result, historical alarm information of the target analysis result within a preset time is extracted and displayed, wherein the historical alarm information includes alarm time, alarm status, alarm strategy, alarm object and alarm content.

[0107] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a gas data analysis program based on a data architecture platform, and when the gas data analysis program based on the data architecture platform is executed by a processor, the steps of the gas data analysis method based on the data architecture platform as described above are implemented.

[0108] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0109] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0110] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A gas data analysis method based on a data architecture platform, characterized in that: The gas data analysis method based on the data architecture platform includes: Acquire the data to be processed of the gas platform, pre-process the data to be processed, and obtain target data to be processed; Performing a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, performing a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and performing a data security analysis on the target data to be processed to obtain a third analysis result; A target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed.

2. The gas data analysis method based on the data architecture platform according to claim 1 is characterized in that: The step of obtaining the data to be processed of the gas platform and preprocessing the data to be processed to obtain target data to be processed also includes: Obtain resource information of the gas platform, wherein the resource information includes cloud platform resources, server resources, network resources, storage resources, computer room resources and security resources; Acquire processing requirements of the gas platform, wherein the processing requirements include data integration, data governance, data analysis, data services and data applications; A corresponding data architecture platform is constructed according to the resource information and the processing requirements.

3. The gas data analysis method based on the data architecture platform according to claim 2 is characterized in that: The obtaining of the data to be processed of the gas platform and preprocessing the data to be processed to obtain target data to be processed specifically includes: Acquire a data collection range, and collect data on the gas platform according to the data range to obtain data to be processed, wherein the data to be processed includes unstructured data, semi-structured data, structured data, and real-time data; Obtain target data standards, perform standardization processing on the data to be processed according to the target data standards to obtain standardized data, and perform data cleaning on the standardized data to obtain target data to be processed, wherein the standardization processing includes data definition, data classification and format conversion.

4. The gas data analysis method based on the data architecture platform according to claim 1 is characterized in that: The performing functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result specifically includes: Performing data storage analysis on the target data to be processed according to the data computing storage platform of the data architecture platform to obtain storage analysis results; Analyzing the data quality of the target data to be processed to obtain a quality analysis result, and analyzing the data link of the target data to be processed to obtain a link analysis result; The storage analysis result, the quality analysis result and the link analysis result are combined to obtain a first analysis result of the target data to be processed.

5. The gas data analysis method based on the data architecture platform according to claim 1 is characterized in that: The gas pipeline network analysis is performed on the target data to be processed to obtain a second analysis result, specifically including: Performing pipe network data screening on the target data to be processed to obtain target pipe network data, and establishing a corresponding pipe network data analysis model according to the target pipe network data; Performing pipeline failure analysis on the target data to be processed according to the pipeline network data analysis model to obtain pipeline analysis results, and performing gas supply forecasting analysis on the target data to be processed to obtain gas supply usage results; The pipeline analysis result and the gas package utility result are combined to obtain a second analysis result.

6. The gas data analysis method based on the data architecture platform according to claim 1 is characterized in that: The performing of data security analysis on the target data to be processed to obtain a third analysis result specifically includes: Performing IP access analysis and port access analysis on the target data to be processed to obtain network security results, and performing data audit on the target data to be processed to obtain data security results; Performing application layer security analysis on the target data to be processed to obtain application security results, wherein the application layer security analysis includes user authentication analysis, data transmission analysis and user authority analysis; The network security result, the data security result and the application security result are combined to obtain a third analysis result.

7. The gas data analysis method based on the data architecture platform according to claim 1 is characterized in that: The target analysis result is obtained according to the first analysis result, the second analysis result and the third analysis result, and the target analysis result is displayed, and then the following further comprises: If there is alarm information in the target analysis result, historical alarm information of the target analysis result within a preset time is extracted and displayed, wherein the historical alarm information includes alarm time, alarm status, alarm strategy, alarm object and alarm content.

8. A gas data analysis system based on a data architecture platform, characterized in that: The gas data analysis system based on the data architecture platform includes: A data acquisition module is used to acquire the data to be processed of the gas platform, pre-process the data to be processed, and obtain target data to be processed; A data analysis module, configured to perform a functional requirement analysis on the target data to be processed according to the data architecture platform to obtain a first analysis result, perform a gas pipeline network analysis on the target data to be processed to obtain a second analysis result, and perform a data security analysis on the target data to be processed to obtain a third analysis result; A result display module is used to obtain a target analysis result according to the first analysis result, the second analysis result and the third analysis result, and to display the target analysis result.

9. A terminal, characterized in that: The terminal includes a memory, a processor, and a gas data analysis program based on a data architecture platform stored in the memory and executable on the processor. When the gas data analysis program based on the data architecture platform is executed by the processor, the steps of the gas data analysis method based on the data architecture platform as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer-readable storage medium stores a gas data analysis program based on a data architecture platform. When the gas data analysis program based on the data architecture platform is executed by a processor, the steps of the gas data analysis method based on the data architecture platform as described in any one of claims 1-7 are implemented.

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