CN116610762B - Management method, equipment and medium for enterprise data assets - Google Patents
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Abstract
The application discloses a management method, equipment and medium of enterprise data assets, and relates to the technical field of data processing methods based on management purposes. The method comprises the following steps: determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise; determining a business owner corresponding to the data asset, and determining whether the data asset is consistent with business data or not through the business owner; if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to obtain a quality report corresponding to the data asset; and determining the appointed data asset with the data quality problem in the data asset according to the quality report, and performing traceability analysis on the appointed data asset to realize quality management on the appointed data asset.
Description
Technical Field
The application relates to the technical field of data processing methods based on management purposes, in particular to a method, equipment and medium for managing enterprise data assets.
Background
For enterprises, data assets are data resources owned or controlled by the enterprises and organizations, which can bring future economic benefits to the enterprises and organizations, such as sales data, user information, financial information, etc. inside the enterprises.
With the advent of the digital economic age, market bodies have been continually expanding in demand for data management, which is an efficient engine for mining data values, which is beneficial to maximizing business value for enterprises. However, the business system of the enterprise has a lot of data generated in the operation process, and has great difficulty in asset management, and is difficult to provide implementation and guidance for the technology, business and data personnel participating in the data asset inventory.
Disclosure of Invention
In order to solve the above problems, the present application proposes a method for managing enterprise data assets, including:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
performing service tracing on the data asset to determine a service owner corresponding to the data asset, and determining whether the data asset is consistent with the service data through the service owner; wherein the business owner is used for characterizing a responsible attribution main body of the data asset;
If yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to acquire a quality report corresponding to the data asset;
and determining a designated data asset with a data quality problem in the data assets according to the quality report, and performing traceability analysis on the designated data asset to realize quality management on the designated data asset.
In one implementation manner of the present application, service tracing is performed on the data assets to determine service owners corresponding to the data assets respectively, which specifically includes:
determining the type of tracing to be performed on the data asset; wherein the trace-source type at least comprises one or more of the following: system tracing, data quality problem tracing and business attribute tracing;
according to the tracing type, a first responsibility attribution main body corresponding to an application system for generating the data asset, a second responsibility attribution main body for supervising and reporting the data asset and a third responsibility attribution main body corresponding to the data asset and belonging to the business field of business data;
And determining a business owner corresponding to the data asset according to the first responsibility attribution main body, the second responsibility attribution main body and the third responsibility attribution main body.
In one implementation of the present application, the tracing analysis is performed on the specified data asset to implement quality management of the specified data asset, and specifically includes:
determining business circulation logic of the data asset, and determining a designated business node for circulating the designated data asset according to the business circulation logic so as to perform root cause analysis on the data quality problem of the designated data asset through the designated business node;
generating a blood edge link where the specified data asset is located through a preset blood edge analysis tool, and determining a quality influence range corresponding to the specified data asset according to the blood edge link; the blood-edge link is composed of a plurality of data nodes corresponding to the data assets, and the data nodes at least comprise an asset data table.
In one implementation of the present application, determining, according to the blood-edge link, a quality impact range corresponding to the specified data asset specifically includes:
Determining an upstream data node and a downstream data node of the data node where the specified data asset is located according to the blood-edge link;
the source data node corresponding to the appointed data asset is screened out from the upstream data nodes, and the target data node corresponding to the appointed data asset is screened out from the downstream data nodes;
and determining a local blood edge link between the target data node and the data node where the specified data asset is located, and determining a quality influence range corresponding to the specified data asset according to the local blood edge link.
In one implementation of the present application, determining the security level corresponding to the data asset specifically includes:
determining an influence object which can generate an influence effect by the data asset and the influence degree corresponding to the influence object;
performing feature recognition on the data asset, and determining general data features in the data asset; wherein the generic data feature is used to characterize usage rights of the data asset;
and acquiring a preset security level rule, and matching the influence object, the influence degree and the general data characteristic with the security level rule to determine the security level corresponding to the data asset.
In one implementation manner of the present application, quality inspection is performed on the data asset corresponding to each security level through the quality inspection script, which specifically includes:
determining each asset data table to which the data asset corresponding to each security level belongs;
performing quality check on the specified field in the asset data table through the quality check script to determine whether the specified field meets corresponding check standards; wherein the quality check comprises at least one or more of the following: non-empty checking, uniqueness checking, data format checking, numerical format checking, value constraint checking.
In one implementation of the present application, after root cause analysis of the data quality problem for the specified data asset, the method further comprises:
determining a question type corresponding to the specified data asset, so as to determine whether the data quality question is associated with the data asset model according to the question type;
if yes, redefining the data asset model according to the business data attribute corresponding to the appointed data asset, and updating the quality check script according to the redefined data asset model.
In one implementation of the present application, before determining the data asset model corresponding to the enterprise, the method further includes:
type division is carried out on data assets generated by enterprises in the operation process, so that data assets with different asset types are obtained; wherein the asset types include at least a canonical data asset, a base data asset, an integrated data asset, an extraction data asset, and an application data asset;
for each asset type of data asset, dividing the attribute of the data asset into a business attribute, a management attribute and a technical attribute according to the asset characteristics of the data asset;
and constructing a data asset model corresponding to the enterprise according to the attribute.
The embodiment of the application provides management equipment of enterprise data assets, which comprises the following components:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
Performing service tracing on the data asset to determine a service owner corresponding to the data asset, and determining whether the data asset is consistent with the service data through the service owner; wherein the business owner is used for characterizing a responsible attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to acquire a quality report corresponding to the data asset;
and determining a designated data asset with a data quality problem in the data assets according to the quality report, and performing traceability analysis on the designated data asset to realize quality management on the designated data asset.
Embodiments of the present application provide a non-volatile computer storage medium storing computer-executable instructions configured to:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
Performing service tracing on the data asset to determine a service owner corresponding to the data asset, and determining whether the data asset is consistent with the service data through the service owner; wherein the business owner is used for characterizing a responsible attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to acquire a quality report corresponding to the data asset;
and determining a designated data asset with a data quality problem in the data assets according to the quality report, and performing traceability analysis on the designated data asset to realize quality management on the designated data asset.
The management method of the enterprise data assets provided by the application has the following beneficial effects:
and generating data assets corresponding to the enterprise based on a data asset model defined in advance, and further performing data verification on the data assets through the determined service owners, so that the data accuracy is ensured. The data assets are classified safely, the type primary screening of the data assets is realized, and the appointed data assets with the data quality problem can be detected in time by carrying out quality check on the data assets with different security grades. The tracing analysis is carried out on the appointed data asset, so that the tracing of the root cause and the influence range of the data quality problem is realized, the data asset quality is improved, and the foundation is laid for the data asset sharing application, evaluation and valuation.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method for managing enterprise data assets according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an enterprise data asset management device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
As shown in fig. 1, a method for managing enterprise data assets provided by an embodiment of the present application includes:
101: and determining a data asset model corresponding to the enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain the data asset corresponding to the enterprise.
The management of the data assets can fully exert the data value, promote the data to be energized in enterprises, but if the value of the data assets is to be protected, delivered and improved, the range of the data assets in the enterprises needs to be defined, and the management flow and the standard of the data assets are designed.
In an embodiment of the present application, data assets can be categorized into five types, canonical data assets, base data assets, integrated data assets, extract data assets, and application data assets. The standard data assets comprise data standards and data dictionaries, the basic data assets comprise exchange interfaces, component D models and the like, the integrated data assets comprise data of integrated interfaces, source-attached assets, integrated models, public computing, public access, application computing and the like, the extracted data assets comprise indexes, labels and the like, and the application data assets comprise reports, self-service query data and the like. Each class of data assets includes information including numbers, classifications, english names, chinese names, home departments, data standards, data security classifications, quality rules, etc. For each asset type described above, the server may divide the attributes of the data asset into business attributes, management attributes, and technical attributes based on the asset characteristics of the data asset. The management attribute mainly comprises a registration party, registration time, a home department and a use department, the technical attribute mainly comprises a data category and a data definition, and the service attribute mainly comprises a service purpose, a service definition, a service rule and the like.
After determining the attributes, the server can construct a data asset model corresponding to the enterprise according to different types of data assets and the attributes corresponding to the data assets. It should be noted that, the data asset model is only a simple definition of the data asset and does not include actual data, so after determining the data asset model corresponding to the enterprise, the server needs to obtain service data corresponding to the data asset model from the preset database based on the data asset model, so as to instantiate the data asset model to obtain the data asset corresponding to the enterprise. The data assets are in the form of ledgers, including one or more asset data tables.
102: performing business tracing on the data asset to determine a business owner corresponding to the data asset, and determining whether the data asset is consistent with business data or not through the business owner; wherein the business owner is used to characterize the responsible home agent of the data asset.
The process realizes the definition and collection of the data asset, and after the collection of the data asset is completed, the corresponding instantiation data of the data asset is confirmed to ensure the accuracy of the data asset. By tracing the business of the data asset, the business owner corresponding to the data asset can be determined, and the business owner is used for representing the responsibility attribution main body of the data asset.
It should be noted that, the service trace source required to be performed by the data asset includes a plurality of trace source types, where the trace source types at least include one or more of the following: system tracing, data quality problem tracing and business attribute tracing. The system tracing is to trace the first responsibility attribution main body corresponding to the application system generating the data asset, the data quality problem tracing is to trace the second responsibility attribution main body supervising the reported data asset, and the business attribute tracing is to trace the third responsibility attribution main body of the business domain to which the business data corresponding to the data asset belongs. According to the tracing type, the server can determine the business owner corresponding to the data asset from multiple dimensions, and the business owner can be the responsibility attribution department or the responsibility attribution person.
After determining the business owner corresponding to the data asset, the business owner can determine whether the data asset is consistent with the business data in the preset database. If the content of the data assets is consistent, the content of the data assets is accurate, and the subsequent management flow can be performed.
103: if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to obtain a quality report corresponding to the data asset.
In the embodiment of the application, different data assets have different application ranges, attributes and the like, and corresponding security levels also have different levels. After confirming the security level of the data asset, the server performs corresponding security level marking on the data asset. Therefore, after the security level of the data asset is distinguished, hierarchical management of the data asset can be realized, and management efficiency is improved.
It should be noted that the marking of the security level may be performed manually or automatically, and the security level is determined according to the influence object, the influence degree, and the general data characteristics of the data asset. The server may determine an influence object that determines that the data asset is capable of generating an influence effect, and an influence degree corresponding to the influence object. The influencing object includes public rights, personal rights, legal rights of the enterprise, and the influencing extent includes serious damage, general damage, slight damage and no damage. For a data asset, the server may also perform feature recognition on it to determine generic data features in the data asset. The generic data features are used to characterize usage rights of the data asset, e.g., the generic data features may represent that the data asset is used for financial institution critical business usage, is generally disclosed for a particular person, and is only accessed or used for objects that must be known.
After determining the influence object, the influence degree and the general data characteristics, the server needs to acquire a preset security level rule, wherein the security level rule is a setting rule of the security level of the data asset, and each security level corresponds to the corresponding influence object, the influence degree and the general data characteristics. In this way, the security level corresponding to the data asset can be determined by matching the impact object, impact level, and general data characteristics with the security level rules. After the security level is obtained, the server also needs to prompt the data asset with a corresponding level mark.
The quality of the data assets can directly influence the sharing, application and evaluation of the data assets, so that the server can confirm the data quality requirements of various data assets from multiple angles, generate quality check scripts, and perform quality check on the data assets corresponding to each security level by periodically executing the quality check scripts to obtain quality reports corresponding to the data assets, wherein the quality reports can directly reflect the quality condition of the data assets, and are more convenient to locate and process the data assets with data quality.
Specifically, when the quality check is performed on the data asset, each asset data table to which the data asset corresponding to each security level belongs is first determined, and then, the quality check is performed on the designated field in the asset data table through the quality check script to determine whether the designated field meets the corresponding check standard. Wherein the quality check comprises at least one or more of the following: the method comprises the steps of non-empty checking, uniqueness checking, data format checking, numerical format checking and value constraint checking, and can realize the integrity checking, the uniqueness checking and the validity checking of the data asset.
After the quality inspection script is executed to obtain a corresponding inspection result, the server can carry out statistical analysis on the inspection result, evaluate the quality condition of the data asset of each security level and generate a corresponding quality report.
104: and determining the appointed data asset with the data quality problem in the data asset according to the quality report, and performing traceability analysis on the appointed data asset to realize quality management on the appointed data asset.
After the quality report of the data asset is obtained, the server can determine the appointed data asset with the data quality problem in the data asset according to the quality report, and then trace the appointed data asset to analyze the source tracing, trace the quality problem generation reason and the data influence range of the appointed data asset, and is beneficial to the relevant manager to take corresponding management measures for the appointed data asset, so as to realize the quality management of the appointed data asset.
The objective to be achieved by the traceability analysis mainly comprises two aspects, namely, root cause analysis on the specified data asset and analysis on the influence of the specified data asset on the upstream and downstream data assets in the circulation process of the specified data asset.
The root cause analysis is mainly performed through a service development channel and a service development flow, a server needs to determine service circulation logic of data assets, and a designated service node for circulating designated data assets is determined according to the service circulation logic. After locating the specified service node corresponding to the specified data asset, the server can conduct root cause analysis on the data quality problem of the specified data asset based on the specified service node, so that the data asset quality problem is determined to be generated in the service process, and therefore the corresponding service process is analyzed and processed, and the data quality problem can be solved.
The upstream and downstream impact analysis is based on the blood relationship of the data asset. Any data from generation, ETL processing, fusion, flow to final extinction, a relationship is formed between the data to express the association between the data, which is the blood relationship. In the process of processing data assets, from a data source to final data generation, once data of one link has quality problems and is not detected in time, the data information can finally flow into a target data table, so that the quality of the result data is reduced. In the embodiment of the application, the server can generate the blood edge link where the specified data asset is located through a preset blood edge analysis tool, and determine the quality influence range corresponding to the specified data asset according to the blood edge link. The blood edge link is composed of a plurality of data nodes corresponding to the data assets, and the data nodes at least comprise an asset data table.
When determining the quality influence range corresponding to the specified data asset, the method specifically comprises the following steps:
and the server determines an upstream data node and a downstream data node of the data node where the specified data asset is located according to the blood-edge link. And screening the source data nodes corresponding to the specified data assets from the upstream data nodes, and screening the target data nodes corresponding to the specified data assets from the downstream data nodes. After the source data node and the target data node are obtained, the server can determine a local blood edge link between the target data node and the data node where the specified data asset is located, and then determine a quality influence range corresponding to the specified data asset according to the local blood edge link. That is, the data nodes included in the local blood edge link are all data nodes located at the downstream of the data node where the specified data asset is located, and in the process of data processing and circulation, the data nodes in the local blood edge link are affected by the specified data asset, if the specified data asset is processed in time, the influence on the downstream data node can be reduced.
In the embodiment of the application, after the root cause analysis is carried out on the data quality problem of the appointed data asset, the server can determine the problem type corresponding to the appointed data asset, and further determine whether the detected data quality problem is related to the data asset model according to the problem type. If there is an association, the problem that indicates that the currently specified data asset exists is not an actual data quality problem, but rather is a quality problem caused by the fact that the definition of the data asset in the data asset model is inconsistent with the actual data asset, for example, the data quality problem is represented by that the data length is inconsistent with the data length defined by the data asset model, and the data length is possibly recorded in error when the business data is collected to form the data asset, which is not a quality problem caused by the fact that the data itself presents quality problems. Therefore, redefining the data asset model according to the business data attribute corresponding to the appointed data asset, and updating the corresponding quality check script according to the redefined data asset model. In this way, the data quality problem that exists in the specified data asset can be solved.
The above is a method embodiment of the present application. Based on the same thought, some embodiments of the present application also provide a device and a non-volatile computer storage medium corresponding to the above method.
Fig. 2 is a schematic structural diagram of an enterprise data asset management device according to an embodiment of the present application. As shown in fig. 2, includes:
at least one processor; the method comprises the steps of,
at least one processor in communication with the memory; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
performing business tracing on the data asset to determine a business owner corresponding to the data asset, and determining whether the data asset is consistent with business data or not through the business owner; wherein the business owner is used for representing a responsibility attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to obtain a quality report corresponding to the data asset;
and determining the appointed data asset with the data quality problem in the data asset according to the quality report, and performing traceability analysis on the appointed data asset to realize quality management on the appointed data asset.
Embodiments of the present application provide a non-volatile storage medium storing computer-executable instructions, the executable instructions comprising:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
performing business tracing on the data asset to determine a business owner corresponding to the data asset, and determining whether the data asset is consistent with business data or not through the business owner; wherein the business owner is used for representing a responsibility attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to obtain a quality report corresponding to the data asset;
and determining the appointed data asset with the data quality problem in the data asset according to the quality report, and performing traceability analysis on the appointed data asset to realize quality management on the appointed data asset.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for the apparatus and medium embodiments, the description is relatively simple, as it is substantially similar to the method embodiments, with reference to the section of the method embodiments being relevant.
The devices and media provided in the embodiments of the present application are in one-to-one correspondence with the methods, so that the devices and media also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not repeated here.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (7)
1. A method of managing enterprise data assets, the method comprising:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
performing service tracing on the data asset to determine a service owner corresponding to the data asset, and determining whether the data asset is consistent with the service data through the service owner; wherein the business owner is used for characterizing a responsible attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to acquire a quality report corresponding to the data asset;
Determining a specified data asset with a data quality problem in the data assets according to the quality report, and performing traceability analysis on the specified data asset to realize quality management on the specified data asset;
performing service tracing on the data assets to determine service owners corresponding to the data assets respectively, wherein the service tracing comprises the following steps:
determining the type of tracing to be performed on the data asset; wherein the trace-source type at least comprises one or more of the following: system tracing, data quality problem tracing and business attribute tracing;
according to the tracing type, a first responsibility attribution main body corresponding to an application system for generating the data asset, a second responsibility attribution main body for supervising and reporting the data asset and a third responsibility attribution main body corresponding to the data asset and belonging to the business field of business data;
determining a business owner corresponding to the data asset according to the first responsibility attribution main body, the second responsibility attribution main body and the third responsibility attribution main body;
performing traceability analysis on the specified data asset to realize quality management on the specified data asset, wherein the method specifically comprises the following steps:
Determining business circulation logic of the data asset, and determining a designated business node for circulating the designated data asset according to the business circulation logic so as to perform root cause analysis on the data quality problem of the designated data asset through the designated business node;
generating a blood edge link where the specified data asset is located through a preset blood edge analysis tool, and determining a quality influence range corresponding to the specified data asset according to the blood edge link; wherein, the blood-edge link is composed of a plurality of data nodes corresponding to the data assets, and the data nodes at least comprise an asset data table;
according to the blood edge link, determining a quality influence range corresponding to the specified data asset specifically comprises the following steps:
determining an upstream data node and a downstream data node of the data node where the specified data asset is located according to the blood-edge link;
the source data node corresponding to the appointed data asset is screened out from the upstream data nodes, and the target data node corresponding to the appointed data asset is screened out from the downstream data nodes;
and determining a local blood edge link between the target data node and the data node where the specified data asset is located, and determining a quality influence range corresponding to the specified data asset according to the local blood edge link.
2. The method for managing an enterprise data asset according to claim 1, wherein determining the security level corresponding to the data asset comprises:
determining an influence object which can generate an influence effect by the data asset and the influence degree corresponding to the influence object;
performing feature recognition on the data asset, and determining general data features in the data asset; wherein the generic data feature is used to characterize usage rights of the data asset;
and acquiring a preset security level rule, and matching the influence object, the influence degree and the general data characteristic with the security level rule to determine the security level corresponding to the data asset.
3. The method for managing enterprise data assets according to claim 1, wherein the quality inspection script is used for quality inspection of the data assets corresponding to the security levels, and specifically comprises:
determining each asset data table to which the data asset corresponding to each security level belongs;
performing quality check on the specified field in the asset data table through the quality check script to determine whether the specified field meets corresponding check standards; wherein the quality check comprises at least one or more of the following: non-empty checking, uniqueness checking, data format checking, numerical format checking, value constraint checking.
4. The method of claim 1, wherein after root cause analysis of the data quality problem for the specified data asset, the method further comprises:
determining a question type corresponding to the specified data asset, so as to determine whether the data quality question is associated with the data asset model according to the question type;
if yes, redefining the data asset model according to the business data attribute corresponding to the appointed data asset, and updating the quality check script according to the redefined data asset model.
5. The method of claim 1, wherein prior to determining the data asset model for the enterprise, the method further comprises:
type division is carried out on data assets generated by enterprises in the operation process, so that data assets with different asset types are obtained; wherein the asset types include at least a canonical data asset, a base data asset, an integrated data asset, an extraction data asset, and an application data asset;
for each asset type of data asset, dividing the attribute of the data asset into a business attribute, a management attribute and a technical attribute according to the asset characteristics of the data asset;
And constructing a data asset model corresponding to the enterprise according to the attribute.
6. An enterprise data asset management device, the device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
performing service tracing on the data asset to determine a service owner corresponding to the data asset, and determining whether the data asset is consistent with the service data through the service owner; wherein the business owner is used for characterizing a responsible attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to acquire a quality report corresponding to the data asset;
Determining a specified data asset with a data quality problem in the data assets according to the quality report, and performing traceability analysis on the specified data asset to realize quality management on the specified data asset;
performing service tracing on the data assets to determine service owners corresponding to the data assets respectively, wherein the service tracing comprises the following steps:
determining the type of tracing to be performed on the data asset; wherein the trace-source type at least comprises one or more of the following: system tracing, data quality problem tracing and business attribute tracing;
according to the tracing type, a first responsibility attribution main body corresponding to an application system for generating the data asset, a second responsibility attribution main body for supervising and reporting the data asset and a third responsibility attribution main body corresponding to the data asset and belonging to the business field of business data;
determining a business owner corresponding to the data asset according to the first responsibility attribution main body, the second responsibility attribution main body and the third responsibility attribution main body;
performing traceability analysis on the specified data asset to realize quality management on the specified data asset, wherein the method specifically comprises the following steps:
Determining business circulation logic of the data asset, and determining a designated business node for circulating the designated data asset according to the business circulation logic so as to perform root cause analysis on the data quality problem of the designated data asset through the designated business node;
generating a blood edge link where the specified data asset is located through a preset blood edge analysis tool, and determining a quality influence range corresponding to the specified data asset according to the blood edge link; wherein, the blood-edge link is composed of a plurality of data nodes corresponding to the data assets, and the data nodes at least comprise an asset data table;
according to the blood edge link, determining a quality influence range corresponding to the specified data asset specifically comprises the following steps:
determining an upstream data node and a downstream data node of the data node where the specified data asset is located according to the blood-edge link;
the source data node corresponding to the appointed data asset is screened out from the upstream data nodes, and the target data node corresponding to the appointed data asset is screened out from the downstream data nodes;
and determining a local blood edge link between the target data node and the data node where the specified data asset is located, and determining a quality influence range corresponding to the specified data asset according to the local blood edge link.
7. A non-transitory computer storage medium storing computer-executable instructions, the computer-executable instructions configured to:
determining a data asset model corresponding to an enterprise, and acquiring business data corresponding to the data asset model from a preset database based on the data asset model so as to instantiate the data asset model to obtain data assets corresponding to the enterprise;
performing service tracing on the data asset to determine a service owner corresponding to the data asset, and determining whether the data asset is consistent with the service data through the service owner; wherein the business owner is used for characterizing a responsible attribution main body of the data asset;
if yes, determining the security level corresponding to the data asset, acquiring a preset quality check script, and performing quality check on the data asset corresponding to each security level through the quality check script to acquire a quality report corresponding to the data asset;
determining a specified data asset with a data quality problem in the data assets according to the quality report, and performing traceability analysis on the specified data asset to realize quality management on the specified data asset;
Performing service tracing on the data assets to determine service owners corresponding to the data assets respectively, wherein the service tracing comprises the following steps:
determining the type of tracing to be performed on the data asset; wherein the trace-source type at least comprises one or more of the following: system tracing, data quality problem tracing and business attribute tracing;
according to the tracing type, a first responsibility attribution main body corresponding to an application system for generating the data asset, a second responsibility attribution main body for supervising and reporting the data asset and a third responsibility attribution main body corresponding to the data asset and belonging to the business field of business data;
determining a business owner corresponding to the data asset according to the first responsibility attribution main body, the second responsibility attribution main body and the third responsibility attribution main body;
performing traceability analysis on the specified data asset to realize quality management on the specified data asset, wherein the method specifically comprises the following steps:
determining business circulation logic of the data asset, and determining a designated business node for circulating the designated data asset according to the business circulation logic so as to perform root cause analysis on the data quality problem of the designated data asset through the designated business node;
Generating a blood edge link where the specified data asset is located through a preset blood edge analysis tool, and determining a quality influence range corresponding to the specified data asset according to the blood edge link; wherein, the blood-edge link is composed of a plurality of data nodes corresponding to the data assets, and the data nodes at least comprise an asset data table;
according to the blood edge link, determining a quality influence range corresponding to the specified data asset specifically comprises the following steps:
determining an upstream data node and a downstream data node of the data node where the specified data asset is located according to the blood-edge link;
the source data node corresponding to the appointed data asset is screened out from the upstream data nodes, and the target data node corresponding to the appointed data asset is screened out from the downstream data nodes;
and determining a local blood edge link between the target data node and the data node where the specified data asset is located, and determining a quality influence range corresponding to the specified data asset according to the local blood edge link.
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