CN116628048B - Asset data management method and system based on time axis - Google Patents
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Abstract
The application provides an asset data management method and system based on a time axis, wherein the method comprises the following steps: acquiring an asset data source based on a time axis; compressing an asset data source and transmitting the asset data source in real time; extracting an asset data source, and establishing a standardized asset management table on a time axis, wherein the asset management table comprises an asset data structure and a data association index between management tables; and searching the asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to perform automatic scheme processing on the abnormal data, if so, selecting an abnormal time point by the abnormal data monitoring model based on a time axis in a reverse order, and processing the abnormal data and associated data. The application can perform real-time monitoring and treatment on the asset data in full life cycle, achieves the effects of unified specification, timely and effective performance and saving labor cost, and prevents dirty data generation and irrecoverable production data loss caused by lack of the specification, monitoring and treatment.
Description
Technical Field
The application relates to the technical field of fixed asset data management, in particular to an asset data management method and system based on a time axis.
Background
With the increasing popularity of networking and information technology, the amount of data produced by humans is growing exponentially. The advent of a vast number of new data sources has resulted in the explosive growth of unstructured, semi-structured data. The units of information data are exploded by the level of TB-PB-EB-ZB. The data processing tasks behind the information we create have far beyond what can be handled by current human resources, as well as in the field of asset management. How to manage and use such data is becoming a significant issue. In the digital transformation of various industries, management measures of data are not in place, and management systems are not standardized, so that the data is finally changed into dirty data.
An asset card is a record of fixed asset information owned by a company or organization, and includes information such as the name, number, date of purchase, cost, depreciation method, and residual value of the asset. By tracking and managing each asset, asset cards can help companies understand their asset financial status and ensure accurate tax calculations and report revenue, which are typically created and maintained by the accounting department or asset management team of the enterprise. The management of the existing asset data is focused on the management of asset card data, and the operation of the data maintenance level is performed around the business contents such as the change, the accounting and the depreciation of the asset data, the operation is mainly embodied in the aspects of the confirmation of the existing data, the guarantee of the promotion of normal business logic, the continuity of upstream and downstream data, the verification of the uniqueness of the asset data and the like, and belongs to a hysteresis compensation operation without the global unification of the industry level, without the capability of preventing and finding problems and without the value of mining the data. Features are also included in terms of data normalization, and inconsistencies in the description of the same asset data among different data sources can also prevent downstream traffic from occurring.
The existing asset data management is mostly data recording and storage, is deficient in data application analysis, specification formulation and data management and control modes, does not have instantaneity, and cannot timely make corresponding data strategies based on dynamic changes of the asset data. In such special situations, asset data problems are generally found in a lagging way, then the error correction is performed manually, the process involves more nodes, the error correction difficulty is high, and the error correction difficulty increases exponentially along with the lagging time.
Therefore, in response to the problems, there is a need to propose a better time-axis-based asset data management method and system.
Disclosure of Invention
Accordingly, it is an object of the present application to provide an improved asset data management method and system based on a timeline.
Based on the above object, in one aspect, the present application provides a method for managing asset data based on a time axis, wherein the method comprises the steps of:
acquiring an asset data source based on a time axis;
compressing an asset data source and transmitting the asset data source in real time;
extracting an asset data source, and establishing a standardized asset management table on a time axis, wherein the asset management table comprises an asset data structure and a data association index between management tables;
and searching the asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to perform automatic scheme processing on the abnormal data, if so, selecting an abnormal time point by the abnormal data monitoring model based on a time axis in a reverse order, processing the abnormal data and associated data, and feeding back a processing result.
In some embodiments of the time-axis based asset data management method according to the present application, the time-axis based asset data management method further comprises:
if not, the automatic scheme processing is not carried out on the abnormal data, the abnormal time point is manually and reversely selected based on the time axis, and the abnormal data and the associated data are processed.
In some embodiments of the timeline-based asset data management methods according to the present application, the asset management table contains asset numbers, asset categories, asset origins, cumulative depreciations, net asset values, residual values rates, subtractive preparation, depreciation methods, projected usage times, cumulative depreciation times.
In some embodiments of the timeline-based asset data management methods according to the present application, the asset management table supports data entry, changes, submission, auditing, asset metering depreciation, asset monthly business operations.
In some embodiments of the asset data management method based on a time axis according to the present application, the method for establishing a standardized asset management table on a time axis specifically includes:
extracting an asset data source, and decoding the extracted asset data source through a decoder;
acquiring a decoded asset data source, creating at least one group of data storage tables, and integrating a plurality of groups of data storage tables;
establishing a centralized data storage warehouse based on a plurality of groups of data storage tables;
and acquiring an updating operation, updating the original data storage warehouse based on the updating operation, copying and storing the original data storage warehouse data, and marking a time tag.
In some embodiments of the timeline-based asset data management method according to the present application, a method of updating an original data store based on an update operation, specifically comprises:
identifying update operation logic;
the update operation triggers the monitoring logic when the update operation is normally executed;
the monitoring logic acquires data of the data storage warehouse at the current time point to perform data storage operation, and meanwhile, the data is updated to the latest in the data storage warehouse, and the data is asynchronously executed by combining the MQ.
In some embodiments of the asset data management method based on time axis according to the present application, the method for processing abnormal data and associated data specifically includes:
providing an abnormal information subscription service for abnormal data results occurring in the detection process, and pushing the abnormal data results to key role accounts or mailboxes of subscription messages in real time;
reminding a system optimal processing scheme according to the current state of the data;
the reminding method for carrying out the optimal system processing scheme according to the current state of the data further comprises the following steps: self-healing of outlier data and a time-axis based linear rollback operation.
In another aspect of the present application, there is also provided a time-axis-based asset data management system, including:
the system comprises a data source acquisition module, a data source generation module and a data source generation module, wherein the data source acquisition module is used for acquiring an asset data source based on a time axis;
the data transmission module is used for compressing the asset data source and transmitting the asset data source in real time;
the management table service module is used for extracting an asset data source and establishing a standardized asset management table on a time axis, wherein the asset management table comprises an asset data structure and a data association index between the management tables;
the abnormal data processing module is used for searching the asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to perform automatic scheme processing on the abnormal data, if yes, selecting an abnormal time point by the abnormal data monitoring model based on a time axis in a reverse order, processing the abnormal data and associated data, and feeding back a processing result.
In some embodiments of the system for chip testing according to the present application, the management table service module includes:
a decoding unit for extracting the asset data source, decoding the extracted asset data source by a decoder;
the storage table integrating unit is used for acquiring the decoded asset data sources, creating at least one group of data storage tables and integrating a plurality of groups of data storage tables;
a storage warehouse establishing unit that establishes a centralized data storage warehouse based on a plurality of sets of data storage tables;
and the data updating unit is used for acquiring the updating operation, updating the original data storage warehouse based on the updating operation, copying and storing the original data storage warehouse data, and marking the time tag.
The application has at least the following beneficial technical effects: the application provides a data management scheme based on a time axis, full life cycle monitoring and linear storage of data, and an operation method for data monitoring and analysis processing, and optimal repair is carried out on abnormal data by utilizing linear characteristics.
The application provides core services in the aspects of data storage, processing and protection by optimizing the structure of the asset management table, optimizing the index setting, buffering, partitioning the sub-table and the like, ensures the rapid processing of the transaction to realize millisecond delay, and achieves the millions of processing events per second.
The application can perform real-time monitoring and treatment on the asset data in full life cycle, achieves the effects of unified specification, timely and effective performance and saving labor cost, and prevents dirty data generation and irrecoverable production data loss caused by lack of the specification, monitoring and treatment.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application and that other embodiments may be obtained according to these drawings without inventive effort for a person skilled in the art.
In the figure:
FIG. 1 illustrates a schematic flow diagram of an implementation of a timeline-based asset data management method in accordance with the present application;
FIG. 2 shows a schematic block diagram of an asset backtracking query in accordance with the present application;
FIG. 3 is a schematic diagram showing an implementation flow of a method for establishing a standardized asset management table on a timeline;
FIG. 4 illustrates a flow diagram of an implementation of a method of updating an original data store repository based on an update operation;
FIG. 5 illustrates a schematic diagram of a timeline-based asset data management system;
FIG. 6 shows a data monitoring flow chart provided by the present application;
fig. 7 shows a schematic diagram of a framework of a management table service module provided according to the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the following embodiments of the present application will be described in further detail with reference to the accompanying drawings.
It should be noted that, in the embodiments of the present application, all the expressions "first" and "second" are used to distinguish two non-identical entities with the same name or non-identical parameters, and it is noted that the "first" and "second" are only used for convenience of expression, and should not be construed as limiting the embodiments of the present application. Furthermore, the terms "comprise" and "have," and any variations thereof, are intended to cover a non-exclusive inclusion, such as a process, method, system, article, or other step or unit that comprises a list of steps or units.
Briefly, the present application provides a method for asset data management based on a timeline, the method comprising in particular obtaining a timeline-based asset data source; compressing an asset data source and transmitting the asset data source in real time; extracting an asset data source, and establishing a standardized asset management table on a time axis, wherein the asset management table comprises an asset data structure and a data association index between management tables; and searching the asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to perform automatic scheme processing on the abnormal data, if so, selecting an abnormal time point by the abnormal data monitoring model based on a time axis in a reverse order, processing the abnormal data and associated data, and feeding back a processing result. The application provides a data management scheme based on a time axis, full life cycle monitoring and linear storage of data, and an operation method for data monitoring and analysis processing, and optimal repair is carried out on abnormal data by utilizing linear characteristics.
In a first aspect of the embodiment of the present application, a method for managing asset data based on a time axis is provided, and fig. 1 shows a schematic implementation flow chart of the method for managing asset data based on the time axis, where the method for managing asset data based on the time axis specifically includes:
step S10, acquiring an asset data source based on a time axis;
step S20, compressing the asset data source and transmitting the asset data source in real time;
step S30, extracting an asset data source, and establishing a standardized asset management table on a time axis, wherein the asset management table comprises an asset data structure and a data association index between management tables;
step S40, searching an asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to perform automatic scheme processing on the abnormal data, if so, selecting an abnormal time point by the abnormal data monitoring model based on a time axis in a reverse order, processing the abnormal data and associated data, and feeding back a processing result;
and S50, if not, carrying out automatic scheme processing on the abnormal data, manually selecting an abnormal time point in reverse order based on a time axis, and processing the abnormal data and the associated data.
The application provides a data management scheme based on a time axis, full life cycle monitoring and linear storage of data, and an operation method for data monitoring and analysis processing, and optimal repair is carried out on abnormal data by utilizing linear characteristics.
The asset management table includes an asset number, an asset type, an asset original value, an accumulated depreciation, an asset net value, a residual value rate, a reduction preparation, a depreciation method, an expected use period number, an accumulated use period number, and an accumulated depreciation period number.
In this embodiment, the asset management table supports data entry, change, submission, audit, asset metering depreciation, asset monthly business operations.
Illustratively, the depreciation, change, month knot, etc. of the asset management table directly affects the direct change of the corresponding ID card data in the database, and therefore, if after the change, specific data that is intended to be viewed or rolled back at any subsequent time for some period of time will not be available. To illustrate this problem, the following is illustrated: in an enterprise, there is a fixed asset office computer, and the asset management table shown in table 1 is obtained by checking in and establishing a card after purchasing in 2023, 1.
TABLE 1
The 2023 month 5 had a 5-phase depreciation, at which time the asset management table information is shown in table 2.
TABLE 2
The time axis mainly describes a serialization form of asset data in a time dimension, when the asset data is changed and stored in a database, the data are sequentially arranged in time, and the data are linearly arranged in time. For example, the current time is 5 months, to view 3 months of asset data, the system provides a query entry, inputs the asset number and the time point of the data to be queried, and the system returns the asset data matching the input time point. The asset backtracking query is shown in figure 2.
At this point, the financial auditor finds that the financial data does not match the asset management table data against the fixed asset subject (1601) in the 2023 general ledger, and needs to view the system management table data at 2023, 4, as shown in table 3.
TABLE 3 Table 3
The traditional method is difficult to quickly display under the condition that the table data is updated, and especially the table data after each operation is not searched at all.
The embodiment of the application also provides a method for establishing a standardized asset management table by using a time axis, and fig. 3 shows a schematic implementation flow chart of the method for establishing the standardized asset management table by using the time axis, wherein the method for establishing the standardized asset management table by using the time axis specifically comprises the following steps:
step S301, extracting an asset data source, and decoding the extracted asset data source through a decoder;
step S302, acquiring a decoded asset data source, creating at least one group of data storage tables, and integrating a plurality of groups of data storage tables;
step S303, a centralized data storage warehouse is built based on a plurality of groups of data storage tables;
step S304, an updating operation is acquired, the original data storage warehouse is updated based on the updating operation, and meanwhile, the original data storage warehouse data is copied and stored for one time, and a time label is marked.
The embodiment of the application also provides a method for updating the original data storage warehouse based on the updating operation, and fig. 4 shows a schematic implementation flow chart of the method for updating the original data storage warehouse based on the updating operation, wherein the method for updating the original data storage warehouse based on the updating operation specifically comprises the following steps:
step S3041, identifying update operation logic;
step S3042, the updating operation is performed normally while the updating operation triggers the monitoring logic;
in step S3043, the monitoring logic acquires the data of the data storage warehouse at the current time point to perform data storage operation, and meanwhile, the data is updated to be up to date in the data storage warehouse, and the data is asynchronously executed in combination with the MQ.
For example: when the asset card AC0001 is subjected to the depreciation operation, the data updating operation of the card in the depreciation logic is normally executed, the updating operation triggers the monitoring logic, the monitoring logic acquires the card data at the current time to perform the data storage operation, and meanwhile, the depreciation data in the card is updated to be latest, and the operation is asynchronously executed by combining with the MQ, so that the problems of repeated code implementation and system maintainability of each service initiator are solved, and the response efficiency and the user experience of the system are improved. A data monitoring flow chart is shown in fig. 6.
For example, the condition that asset data between a business module and a heterogeneous system is inconsistent is common, the condition mainly occurs in the updating process of complex logic, the reasons generally generated are mainly logic defects, data inconsistency caused by network delay, data structure difference of the heterogeneous system and the like, the existence of data problems can cause auditing and tax risks of financial data, and data accuracy is extremely important. Therefore, an automatic analysis and identification service is provided for the result processing of the data behavior, the content of the service is mainly to judge and define the behavior of the data, for example, the data in the balance table of the assets are related in two adjacent asset periods, the initial date of the current month is equal to the final date of the last period, specifically, the initial period depreciation of the current period is equal to the final accumulated depreciation of the last period, and similar business association relations exist among the asset primary value, net value, reduced value preparation and the like. The service is automatically pulled up to run when the script service monitors that the balance data changes by utilizing the matched automatic analysis service in the service association relation preset, and the changed data is checked and checked for service angle. The service content supports self definition and configurability, the service content of the self definition extension can be processed by a content mounting mode at any time, when the preset service can not meet the service requirement, the service can be flexibly extended according to the actual requirement, for example, when the user needs to carry out logic verification on the current period and the number of occurrences of the asset balance data, the mounting and the addition of the service can be carried out automatically, in the use angle, the service logic relation among fields is only written or configured according to the requirement, and the extension service can automatically start to operate along with the monitoring process after the configuration is completed.
It should be noted that the method for processing the abnormal data and the associated data specifically includes: providing an abnormal information subscription service for abnormal data results in the detection process, pushing the abnormal data results in real time for key role accounts or mailboxes of subscription messages, and reminding a system optimal processing scheme according to the current state of the data.
The reminding method for carrying out the optimal processing scheme of the system according to the current state of the data comprises the following steps: self-healing of outlier data and a time-axis based linear rollback operation.
Illustratively, based on financial stringency, no direct automated modification of data is allowed here, providing a semi-automated treatment scheme for abnormal data detection results based on human involvement. And providing an abnormal information subscription service for abnormal data results in the detection process, and pushing the abnormal data results to key role accounts or mailboxes of subscription messages in real time. And reminding a system optimal processing scheme according to the current state of the data while pushing the result, wherein reminding contents are mainly divided into two parts, namely a part I: self-repair of anomalous data. The main countermeasure scene is simpler data problems, such as that field calculation logic in a bill is not self-consistent. The system firstly reminds abnormal data in a message form and then advances the solution of the data problem in an interactive mode. Part two: a linear rollback operation based on a time axis. The method is mainly applied to business scenes which are inconsistent in data among documents, business modules or heterogeneous systems and cannot be self-repaired. The system automatically detects data consistency item by item in a time reverse order mode according to linear data, and the data nodes with the consistency are provided as a part of data results to key roles for a decision processing scheme. In the decision process, the rollback nodes are selected according to subjective judgment on the premise of ensuring the consistency of the data, after the user confirms the time nodes, the system carries out rollback coverage operation on the asset card data corresponding to the time nodes, and meanwhile, the data associated with the time nodes also carry out the backtracking process of the same level.
In a second aspect of the embodiment of the present application, the embodiment of the present application further provides a time-axis-based asset data management system, and fig. 5 shows a schematic structural diagram of the time-axis-based asset data management system, where the time-axis-based asset data management system specifically includes:
a data source acquisition module 100, wherein the data source acquisition module 100 is configured to acquire an asset data source based on a time axis;
the data transmission module 200 is used for compressing the asset data source and transmitting the asset data source in real time;
the management table service module 300 is configured to extract an asset data source, and establish a standardized asset management table on a time axis, where the asset management table includes an asset data structure and a data association index between management tables;
the abnormal data processing module 400 is configured to search the asset management table in real time, identify abnormal data based on a pre-established abnormal data monitoring model, determine whether to perform automatic scheme processing on the abnormal data, if yes, select an abnormal time point based on a reverse order of a time axis by the abnormal data monitoring model, process the abnormal data and associated data, and feed back a processing result.
Fig. 7 shows a schematic structural diagram of a management table service module 300, where the management table service module 300 specifically includes:
a decoding unit 310, wherein the decoding unit 310 is used for extracting an asset data source, and decoding the extracted asset data source through a decoder;
a storage table integrating unit 320, where the storage table integrating unit 320 is configured to obtain the decoded asset data source, create at least one set of data storage tables, and integrate multiple sets of data storage tables;
a storage warehouse creating unit 330, wherein the storage warehouse creating unit 330 creates a centralized data storage warehouse based on a plurality of sets of data storage tables;
and the data updating unit 340 is used for acquiring the updating operation, updating the original data storage warehouse based on the updating operation, copying and storing the original data storage warehouse data, and marking the time tag.
In a third aspect of the embodiments of the present application, there is also provided a computer-readable storage medium storing computer program instructions executable by a processor. Which when executed, performs the method of any of the embodiments described above.
In a fourth aspect of the embodiments of the present application, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program which, when executed by the processor, implements the method of any of the embodiments described above.
A processor and a memory are included in the computer device and may also include: input means and output means. The processor, memory, input devices, and output devices may be connected by a bus or other means, as illustrated by a bus connection. The input device may receive input numeric or character information and generate signal inputs related to chip testing. The output means may comprise a display device such as a display screen.
The memory is used as a non-volatile computer readable storage medium for storing non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions/modules corresponding to the resource monitoring method in the embodiment of the present application. The memory may include a memory program area and a memory data area, wherein the memory program area may store an operating system, at least one application program required for a function; the storage data area may store data created by use of a time-axis-based asset data management method, and the like. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the local module through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor executes various functional applications of the server and data processing, i.e., implements the asset data management method based on the time axis of the above-described method embodiments, by running non-volatile software programs, instructions and modules stored in the memory.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as software or hardware depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
Finally, it should be noted that the computer-readable storage media (e.g., memory) herein can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. By way of example, and not limitation, nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of example, and not limitation, RAM may be available in a variety of forms such as synchronous RAM (DRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The storage devices of the disclosed aspects are intended to comprise, without being limited to, these and other suitable types of memory.
The various illustrative logical blocks, modules, and circuits described in connection with the disclosure herein may be implemented or performed with the following components designed to perform the functions herein: a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP and/or any other such configuration.
The application provides a data management scheme based on a time axis, full life cycle monitoring and linear storage of data, and an operation method for data monitoring and analysis processing, and optimal repair is carried out on abnormal data by utilizing linear characteristics.
The application provides core services in the aspects of data storage, processing and protection by optimizing the structure of the asset management table, optimizing the index setting, buffering, partitioning the sub-table and the like, ensures the rapid processing of the transaction to realize millisecond delay, and achieves the millions of processing events per second.
The foregoing is an exemplary embodiment of the present disclosure, but it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the disclosed embodiments described herein need not be performed in any particular order. Furthermore, although elements of the disclosed embodiments may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
It should be understood that as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly supports the exception. It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items. The foregoing embodiment of the present application has been disclosed with reference to the number of embodiments for the purpose of description only, and does not represent the advantages or disadvantages of the embodiments.
Those of ordinary skill in the art will appreciate that: the above discussion of any embodiment is merely exemplary and is not intended to imply that the scope of the disclosure of embodiments of the application, including the claims, is limited to such examples; combinations of features of the above embodiments or in different embodiments are also possible within the idea of an embodiment of the application, and many other variations of the different aspects of the embodiments of the application as described above exist, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the embodiments should be included in the protection scope of the embodiments of the present application.
Claims (9)
1. A time-axis-based asset data management method, characterized in that the time-axis-based asset data management method comprises the steps of:
acquiring an asset data source based on a time axis;
compressing an asset data source and transmitting the asset data source in real time;
extracting an asset data source, and decoding the extracted asset data source through a decoder;
acquiring a decoded asset data source, creating at least one group of data storage tables, and integrating a plurality of groups of data storage tables;
establishing a centralized data storage warehouse based on a plurality of groups of data storage tables;
acquiring an updating operation, updating an original data storage warehouse based on the updating operation, copying and storing the original data storage warehouse data, and setting a time tag to complete the establishment of a standardized asset management table, wherein the asset management table comprises an asset data structure and a data association index between management tables;
and searching an asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to perform automatic scheme processing on the abnormal data, if so, selecting abnormal time points by the abnormal data monitoring model based on a time axis in a reverse order, processing the abnormal data and associated data, and feeding back a processing result, wherein the associated data are initial data or end data of adjacent assets.
2. The method of claim 1, wherein the timeline-based asset data management method further comprises:
if not, the automatic scheme processing is not carried out on the abnormal data, the abnormal time point is manually and reversely selected based on the time axis, and the abnormal data and the associated data are processed.
3. The method of claim 2, wherein the asset management table contains asset numbers, asset categories, asset origins, cumulative depreciations, net asset values, residual rates, subtractive preparation, depreciation methods, projected usage counts, cumulative usage counts, and cumulative depreciation counts.
4. The method of claim 3, wherein the asset management table is configured to perform business operations of entering, altering, submitting, auditing, accounting for depreciation for assets, and monthly for assets.
5. The method of claim 1, wherein the method of updating the original data storage repository based on the updating operation comprises:
identifying update operation logic;
the update operation triggers the monitoring logic when the update operation is normally executed;
the monitoring logic acquires data of the data storage warehouse at the current time point to perform data storage operation, and meanwhile, the data is updated to the latest in the data storage warehouse, and the data is asynchronously executed by combining the MQ.
6. The method according to claim 5, wherein the method for processing the abnormal data and the associated data specifically comprises:
providing an abnormal information subscription service for abnormal data results occurring in the detection process, and pushing the abnormal data results to key role accounts or mailboxes of subscription messages in real time;
and reminding a system optimal processing scheme according to the current state of the data.
7. The method of claim 6, wherein the reminding method for performing the system-optimized processing scheme according to the current state of the data further comprises: self-healing of outlier data and a time-axis based linear rollback operation.
8. A timeline-based asset data management system, wherein said timeline-based asset data management comprises:
the system comprises a data source acquisition module, a data source generation module and a data source generation module, wherein the data source acquisition module is used for acquiring an asset data source based on a time axis;
the data transmission module is used for compressing the asset data source and transmitting the asset data source in real time;
the management table service module is used for extracting asset data sources and decoding the extracted asset data sources through a decoder; acquiring a decoded asset data source, creating at least one group of data storage tables, and integrating a plurality of groups of data storage tables; establishing a centralized data storage warehouse based on a plurality of groups of data storage tables; acquiring an updating operation, updating an original data storage warehouse based on the updating operation, copying and storing the original data storage warehouse data, and setting a time tag to complete the establishment of a standardized asset management table, wherein the asset management table comprises an asset data structure and a data association index between management tables;
the abnormal data processing module is used for searching the asset management table in real time, identifying abnormal data based on a pre-established abnormal data monitoring model, judging whether to conduct automatic scheme processing on the abnormal data, if yes, selecting abnormal time points by the abnormal data monitoring model based on a time axis in a reverse order, processing the abnormal data and associated data, and feeding back a processing result, wherein the associated data are initial period data or end period data of adjacent assets.
9. The system of claim 8, wherein the management table service module comprises:
a decoding unit for extracting the asset data source, decoding the extracted asset data source by a decoder;
the storage table integrating unit is used for acquiring the decoded asset data sources, creating at least one group of data storage tables and integrating a plurality of groups of data storage tables;
a storage warehouse establishing unit that establishes a centralized data storage warehouse based on a plurality of sets of data storage tables;
and the data updating unit is used for acquiring the updating operation, updating the original data storage warehouse based on the updating operation, copying and storing the original data storage warehouse data, and setting a time tag.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110473077A (en) * | 2019-07-23 | 2019-11-19 | 中国建设银行股份有限公司 | The monitoring and based reminding method of fixed assets abnormal data, device and electronic equipment |
| CN111108735A (en) * | 2017-10-19 | 2020-05-05 | 阿姆Ip有限公司 | Asset update service |
| CN112015464A (en) * | 2020-09-02 | 2020-12-01 | 中国银行股份有限公司 | SVN warehouse authority management method and device |
| CN213024452U (en) * | 2020-08-27 | 2021-04-20 | 北京合众伟奇科技股份有限公司 | Intelligent measurement asset checking system |
| CN116204361A (en) * | 2023-02-03 | 2023-06-02 | 苏州浪潮智能科技有限公司 | Asset management method, system, device and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100205256A1 (en) * | 2009-02-09 | 2010-08-12 | Nguyen Kiet Q | Asset state change event processing |
-
2023
- 2023-07-20 CN CN202310890730.2A patent/CN116628048B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111108735A (en) * | 2017-10-19 | 2020-05-05 | 阿姆Ip有限公司 | Asset update service |
| CN110473077A (en) * | 2019-07-23 | 2019-11-19 | 中国建设银行股份有限公司 | The monitoring and based reminding method of fixed assets abnormal data, device and electronic equipment |
| CN213024452U (en) * | 2020-08-27 | 2021-04-20 | 北京合众伟奇科技股份有限公司 | Intelligent measurement asset checking system |
| CN112015464A (en) * | 2020-09-02 | 2020-12-01 | 中国银行股份有限公司 | SVN warehouse authority management method and device |
| CN116204361A (en) * | 2023-02-03 | 2023-06-02 | 苏州浪潮智能科技有限公司 | Asset management method, system, device and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 面向服务体系架构(SOA)的主数据管理(MDM)和流程监控(PM)研究;贾红龙;;信息技术与信息化(第02期);第78-82页 * |
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