A report metadata testing method, device and equipment and storage medium

Abstract

Embodiments of the present application disclose a report metadata testing method, device and equipment and a storage medium. The method comprises: classifying data of acquired metadata to obtain a metadata classification result; analyzing data of each type of metadata in the metadata classification result; generating a metadata case based on the data analysis result; acquiring report metadata to be tested, and testing the report metadata to be tested based on the metadata case to obtain a test result; wherein the report metadata to be tested comprises a plurality of business data types, and each business data type corresponds to corresponding index data. The above technical solution classifies data of metadata, analyzes data from multiple aspects to obtain corresponding data analysis results, generates a metadata case based on the data analysis results, and tests the report metadata to be tested based on the metadata case to obtain a test result, which can improve the efficiency of testing and ensure the accuracy of report metadata testing.

Description

Technical Field

[0001] This invention relates to the field of big data technology, and in particular to a method, apparatus, device, and storage medium for testing report metadata. Background Technology

[0002] Financial reports serve as crucial tools for data presentation and decision support in the financial industry, making their accuracy and reliability paramount. However, with the continuous maintenance of reports each year, their complexity and data volume increase. Traditional methods rely on two approaches: firstly, manually writing test cases, which is inefficient and prone to errors; and secondly, using automated testing tools to batch screenshot or export data from financial reports and compare the report data with database data. This method, however, may fail if the source data has non-standard formats (such as merged cells or missing fields), and it also depends on data cleaning—dirty data must be cleaned beforehand—otherwise the automated results are unreliable. Summary of the Invention

[0003] In view of this, the present invention provides a method, apparatus, device and storage medium for testing report metadata, which can improve the efficiency of testing and ensure the accuracy of report metadata testing.

[0004] According to one aspect of the present invention, an embodiment of the present invention provides a method for testing report metadata, the method comprising:

[0005] Obtain metadata from the original report and classify the metadata to obtain metadata classification results;

[0006] Data analysis is performed on the metadata of each type in the metadata classification results to obtain the corresponding data analysis results;

[0007] Generate metadata examples based on the data analysis results;

[0008] Obtain the metadata of the report to be tested, and test the metadata of the report to be tested based on the metadata case to obtain the test results; wherein, the metadata of the report to be tested includes multiple business data types, and each business data type corresponds to the corresponding indicator data.

[0009] According to another aspect of the present invention, embodiments of the present invention also provide a report metadata testing apparatus, the apparatus comprising:

[0010] The metadata classification module is used to obtain metadata from the original report and classify the metadata to obtain the metadata classification result;

[0011] The metadata analysis module is used to perform data analysis on the metadata of each type in the metadata classification results and obtain the corresponding data analysis results.

[0012] The test case generation module is used to generate metadata cases based on the data analysis results.

[0013] The test result output module is used to obtain the metadata of the report to be tested provided by a third-party organization, test the metadata of the report to be tested based on the metadata case, and obtain the test results; wherein, the metadata of the report to be tested includes multiple business data types, and each of the business data types corresponds to the corresponding indicator data.

[0014] According to another aspect of the present invention, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the report metadata testing method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions for causing a processor to execute and implement the report metadata testing method described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, an embodiment of the present invention also provides a computer program product, characterized in that the computer program product includes a computer program, which, when executed by a processor, implements the report metadata testing method described in any embodiment of the present invention.

[0020] The above-described technical solution of this invention improves testing efficiency and ensures the accuracy of report metadata testing by classifying the acquired metadata into categories; performing data analysis on the metadata of each type in the metadata classification results; generating metadata cases based on the data analysis results; acquiring the metadata of the report to be tested; and testing the metadata of the report to be tested based on the metadata cases.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating a report metadata testing method provided in an embodiment of the present invention;

[0024] Figure 2 A flowchart illustrating another report metadata testing method provided in an embodiment of the present invention;

[0025] Figure 3 A schematic diagram of an architecture for design and testing driven by business metadata, management metadata, and technical metadata, provided in an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of an architecture for testing report metadata provided in an embodiment of the present invention;

[0027] Figure 5 This is a structural block diagram of a report metadata testing device provided in an embodiment of the present invention;

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] In one embodiment, Figure 1 This is a flowchart illustrating a report metadata testing method according to an embodiment of the present invention. This embodiment is applicable to situations where metadata in a report is being tested. The method can be executed by a report metadata testing device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0032] S110. Obtain the metadata from the original report and classify the metadata to obtain the metadata classification result.

[0033] Metadata refers to data that describes data and is primarily used to provide contextual information about the data. It helps users understand the meaning, source, location, and ownership of the data. In this embodiment, metadata types may include business metadata, technical metadata, and management metadata.

[0034] In this embodiment, relevant original financial industry reports can be obtained from third-party financial institutions. These original reports contain multi-source data, including but not limited to metadata obtained from external data sources, metadata obtained from data warehouses, and metadata imported manually by users. In this embodiment, the metadata types or categories contained in these multi-source reports can be categorized and summarized to obtain corresponding metadata classification results. In some embodiments, a data classification method can be predefined, and multi-source metadata can be classified using this predefined method. Of course, in addition to the above classification method, other methods in the prior art can also be used to classify metadata; this embodiment does not impose specific limitations here.

[0035] S120. Perform data analysis on the metadata of each type in the metadata classification results to obtain the corresponding data analysis results.

[0036] Data analysis can include, but is not limited to, data lineage analysis, data impact analysis, data end-to-end analysis, and data indicator consistency analysis.

[0037] In this embodiment, data analysis and preprocessing are performed on various types of metadata after metadata classification to facilitate subsequent metadata analysis processes. This can be understood as performing data lineage analysis, data impact analysis, data end-to-end analysis, and data indicator consistency analysis on technical metadata, management metadata, and business metadata to obtain corresponding data lineage analysis results, data impact analysis results, data end-to-end analysis results, and data indicator consistency analysis results. Of course, in addition to the above-mentioned data analysis, other data analyses may also be included; this embodiment does not impose specific limitations.

[0038] S130, Example of generating metadata based on data analysis results.

[0039] The metadata case contains test data values ​​for specific metrics in different business types, which are generated into various types of test data values.

[0040] In this embodiment, when generating metadata cases, relevant relationships and constraints are first established based on various data analysis results. Then, a metadata modeling process is performed, which can be understood as establishing an outline and system for the metadata. Based on this, resource cataloging is established, i.e., establishing relevant content and schemes. Finally, various types of metadata cases are generated, i.e., generating specific test data values. Specifically, based on the data analysis results, metadata modeling is performed on different types of metadata to obtain modeling results. Data resource cataloging is determined from the modeling results. Data resource cataloging includes: resource catalog, asset catalog, and service catalog. The resource catalog represents the catalog of all metadata resources. The asset catalog includes database information, schema information, table-level information, field information, field code information, index information, and constraint information corresponding to all metadata. The service catalog includes data catalogs and shared data catalogs that users can access according to their permissions. The case type for metadata case generation is determined, the target information corresponding to the case type in the asset catalog is obtained, and the corresponding metadata case is generated based on the target information.

[0041] S140. Obtain the metadata of the report to be tested, and test the metadata of the report to be tested based on the metadata case to obtain the test results; wherein, the metadata of the report to be tested includes multiple business data types, and each business data type corresponds to the corresponding indicator data.

[0042] The metadata of the report to be tested can be understood as the metadata of the report that needs to be tested. The business data type can include, but is not limited to, various business types in the financial industry such as loan business and deposit business. Each business type corresponds to corresponding indicator data. For example, for loan business, the corresponding indicator data can include, but is not limited to, personal loans, consumer loans, etc. Each indicator data has a corresponding data value, which is the indicator data value provided by a third-party financial institution and is the indicator data value that needs to be tested.

[0043] In this embodiment, the metadata of the report to be tested can be tested through metadata cases to obtain the corresponding test results. In some embodiments, the first test data value of the indicator data corresponding to each business data type in the metadata of the report to be tested can be determined first. Based on this, the target metadata case corresponding to the first test data value is found in the metadata cases, and the second test data value of the indicator data corresponding to each business data type in the target metadata case is obtained. The first test data value and the second test data value are then compared, and the test result is determined based on the comparison result. Of course, in addition to the above testing method, other methods can also be used for testing. This embodiment does not impose specific limitations here.

[0044] The above-described technical solution of this invention improves testing efficiency and ensures the accuracy of report metadata testing by classifying metadata, performing multi-faceted data analysis to obtain corresponding data analysis results, generating metadata cases based on the data analysis results, and testing the metadata of the report to be tested based on the metadata cases.

[0045] In one embodiment, the method further includes:

[0046] The test results are fed back to a third-party organization so that the organization can verify the data based on the test results.

[0047] In this embodiment, the obtained test results are generally fed back to a third-party organization so that the third-party organization can perform corresponding follow-up processing based on the test results.

[0048] In one embodiment, Figure 2 This is a flowchart of another report metadata testing method provided in an embodiment of the present invention. Based on the above embodiments, this embodiment performs data classification on the metadata to obtain metadata classification results; performs data analysis on the metadata of each type in the metadata classification results to obtain corresponding data analysis results; generates metadata cases based on the data analysis results; and tests the metadata of the report to be tested based on the metadata cases to obtain test results for further refinement.

[0049] like Figure 2As shown, the report metadata testing method in this embodiment may specifically include the following steps:

[0050] S210. Obtain the metadata from the original report and determine the type to which the metadata belongs.

[0051] In this embodiment, the attribution type of metadata is determined, which is mainly divided into three categories: business metadata, technical metadata, and management metadata. This classification method helps organizations to effectively govern and utilize metadata.

[0052] S220. Divide metadata into business metadata, technical metadata and management metadata according to their ownership type, and classify the data accordingly.

[0053] In this embodiment, after determining the attribution type of the metadata, the metadata is divided into business metadata, technical metadata, and management metadata according to the attribution type, and the data is categorized according to business metadata, technical metadata, and management metadata.

[0054] For example, to facilitate a better understanding of different types of metadata-driven design tests, Figure 3 This is a schematic diagram illustrating an architecture for design and testing driven by business metadata, management metadata, and technical metadata, as provided in an embodiment of the present invention. Figure 3 As shown, this approach ensures comprehensive coverage of reports across different presentation levels, not only from the perspective of business data itself but also from technical and management dimensions. The testing methodology includes: Business Metadata-Driven Design: Business metadata defines the business meaning and rules of the data; data analysis and application are designed based on business domain understanding. Technical Metadata-Driven Design: Technical metadata clarifies the storage and structure of data, clarifies data relationships, and supports data lineage tracing and impact analysis; analysis is designed based on application development and system integration. Management Metadata-Driven Design: Management metadata defines the operational attributes of data, including organizational departments and users; data management responsibilities and access scope; and test analysis is designed from a data security management perspective.

[0055] S230. Perform data lineage analysis on the metadata of each type to obtain the first data analysis result.

[0056] In this embodiment, data lineage analysis is performed on various types of metadata to obtain data lineage analysis results. Lineage analysis analyzes the upstream data information of metadata to trace the source and processing of metadata. It is the natural formation of a relationship between data throughout the entire life cycle of data, from generation, processing, integration, flow to final extinction.

[0057] S240. Perform data impact analysis on various types of metadata to obtain the second data analysis result.

[0058] In this embodiment, data impact analysis is performed on various types of metadata to obtain the data impact analysis results. Specifically, data impact analysis analyzes downstream data information of the metadata to understand the potential impact of metadata changes.

[0059] S250. Perform full-link data analysis on various types of metadata to obtain the third data analysis result.

[0060] In this embodiment, full-chain data analysis is performed on various types of metadata to obtain full-chain data analysis results. The full-chain analysis is a combination of lineage analysis and impact analysis, which is used to show the origin and development of the data.

[0061] S260. Perform consistency analysis on the indicators of each type of metadata to obtain the fourth data analysis result.

[0062] In this embodiment, a consistency analysis of various types of metadata is performed to obtain the consistency analysis results. Specifically, the consistency analysis ensures that the same business metric has a unified definition, calculation logic, and data source throughout the entire organization.

[0063] S270. The first data analysis result, the second data analysis result, the third data analysis result, and the fourth data analysis result are taken as the target data analysis result.

[0064] In this embodiment, based on the results of data lineage analysis, data impact analysis, data end-to-end analysis, and indicator consistency analysis, the data relationships corresponding to each type of metadata are determined. This can be understood as follows: after performing the above data analysis, the data relationships between the data in each type of metadata can be known.

[0065] S280. Based on the data analysis results, perform metadata modeling on different types of metadata to obtain modeling results; among which, metadata modeling includes: metadata requirement analysis, conceptual modeling, logical modeling and physical modeling.

[0066] In this embodiment, metadata modeling is performed on different types of metadata based on the data analysis results to obtain the modeling results. In this embodiment, metadata modeling is equivalent to the process of establishing a metadata outline system. Metadata modeling includes: metadata requirements analysis, conceptual modeling, logical modeling, and physical modeling. Specifically, metadata requirements analysis involves classifying data types according to the business characteristics and reporting requirements; conceptual modeling involves classifying and categorizing the basic elements in the data dictionary after the report is entered into the database, namely entities, attributes, domains, keys, and relationships; logical modeling involves analyzing the data structure based on conceptual modeling and referring to the database logical design to determine the relational schema of the database tables, etc.; and physical modeling involves analyzing the actual data structure based on logical modeling and referring to the database physical design, including naming specific actual data, data field types, and any necessary stored procedures and triggers, etc.

[0067] S290. Determine the data resource catalog in the modeling results; wherein, the data resource catalog includes: resource catalog, asset catalog and service catalog; the resource catalog represents the catalog of all metadata resources; the asset catalog includes the database information, schema information, table-level information, field information, field code information, index information and constraint information corresponding to all metadata; the service catalog includes the data catalog and shared data catalog that users can use according to their permissions.

[0068] Among them, data resource cataloging can be understood as a related branch system under the modeling results.

[0069] In this embodiment, a data resource catalog is determined in the modeling results. The data resource catalog includes: a resource catalog, an asset catalog, and a service catalog. The resource catalog represents a catalog of all metadata resources. The asset catalog includes database information, schema information, table-level information, field information, field code information, index information, and constraint information corresponding to all metadata. The service catalog includes data catalogs that users can use according to their permissions and shared data catalogs. One type is determined by user permissions, data permissions, etc., for direct or indirect use, and the other type is an externally shared interface that provides encryption, tagging, and other referencing functions.

[0070] S2100. Determine the case type for generating metadata cases, obtain the target information corresponding to the case type in the asset catalog, and generate the corresponding metadata cases based on the target information.

[0071] The target information can be understood as one of the pieces of information contained in the asset catalog. Different pieces of information can generate different metadata cases.

[0072] In this embodiment, the case type for generating metadata cases is determined, the target information corresponding to the case type in the asset catalog is obtained, and the corresponding metadata case is generated based on the target information. The metadata case includes at least: report template metadata case, report dimension metadata case, report index metadata case, report detail metadata case, report summary metadata case, report cell formula metadata case, report multi-level drill-down metadata case, and report storage path metadata case.

[0073] Specifically, for report template metadata examples, such as the number of rows, columns, and cell format attributes, is the report template format data consistent? For report dimension metadata examples, such as time, geography, currency, institution, and department, is the report dimension data consistent? For report indicator metadata examples, such as indicator requirements based on industry classification, banking, insurance, securities, etc., is the report indicator data consistent? For report detail metadata examples, such as the specific data content of the report and the requirements for viewing detailed report data after data processing, is the report indicator data consistent? For report summary metadata examples, such as summary data statistics based on different dimensions such as time (year, quarter, month, week, day), geography, and institution (1, 2, ..., N), is the report summary data consistent? For report cell formula metadata examples, such as obtaining target parameter values ​​through calculation formulas in various report cells, is the report formula data consistent? Examples of multi-level drill-down metadata in reports include drilling down data between the main report and sub-reports, analyzing data from summary data to detailed relationships, and dynamically interacting data based on different dimensions and drill-down paths. The test verifies the consistency of data across different drill-down levels. Another example is report storage path metadata, using a naming convention such as storage path\year\month\day\dimension\report number\version\report name, etc. The test verifies the consistency of downloaded storage paths.

[0074] S2110. Obtain the metadata of the report to be tested, and determine the first test data value of the indicator data corresponding to each business data type in the metadata of the report to be tested.

[0075] In this embodiment, the metadata of the report to be tested is obtained, and the first test data value of the indicator data corresponding to each business data type in the metadata of the report to be tested is determined.

[0076] S2120. Locate the target metadata case corresponding to the first test data value in the metadata case, and obtain the second test data value of the indicator data corresponding to each business data type in the target metadata case.

[0077] In this embodiment, the target metadata case is a metadata case selected from the metadata cases that corresponds to the first test data value. The target metadata case corresponding to the first test data value is searched within the metadata cases, and the second test data values ​​of the indicator data corresponding to each business data type in the target metadata case are obtained.

[0078] S2130. Compare the first test data value with the second test data value to obtain the comparison result, and determine the test result based on the comparison result.

[0079] In this embodiment, the first test data value and the second test data value are compared to obtain the comparison result, and the test result is determined based on the comparison result. Specifically, if the test data values ​​match, it means that the first test data value is correct; if the test data values ​​do not match, it means that the first test data value is incorrect and data feedback is required.

[0080] The technical solution described in this embodiment divides metadata into business metadata, technical metadata, and management metadata, and performs data classification. It then conducts data lineage analysis, data impact analysis, data end-to-end analysis, and indicator consistency analysis on each type of metadata. Based on the data analysis results, it models different types of metadata, obtains modeling results, further determines the final data resource cataloging to be preprocessed, determines the case type for metadata case generation, obtains the target information corresponding to the case type in the asset catalog, generates corresponding metadata cases based on the target information, determines the first test data value for the indicator data corresponding to each business data type in the metadata of the report to be tested, searches for the target metadata case corresponding to the first test data value in the metadata case, obtains the second test data value for the indicator data corresponding to each business data type in the target metadata case, and compares the first test data value with the second test data value to obtain the comparison result. This approach further improves testing efficiency and ensures the accuracy of report metadata testing.

[0081] In one embodiment, to facilitate a better understanding of the architecture and process of report metadata testing, Figure 4 This is a schematic diagram of an architecture for testing report metadata provided in an embodiment of the present invention. In this embodiment, by defining metadata-driven design specifications and standardizing attribute classification, and establishing metadata modeling, a data cataloging system for data asset management is formed to ensure the correctness of system data processing. Finally, the consistency of the displayed report data is judged by testing the target report according to the target test cases. This avoids the data shortcomings of the above two technical solutions and ensures more accurate report testing. Figure 4As shown, the report metadata testing mainly includes the following aspects: 1) Different types of metadata-driven design: including the acquisition of multi-source metadata, metadata classification, metadata analysis, metadata modeling, and metadata resource cataloging processes; 2) Metadata case generation: including report template metadata cases, report dimension metadata cases, report indicator metadata cases, report detail metadata cases, report summary metadata cases, report cell formula metadata cases, report multi-level drill-down metadata cases, and report storage path metadata cases, etc.; 3) Automatic comparison of report testing and result output: including testing the metadata of the report to be tested based on the metadata cases, obtaining test results, specifically, determining the first test data value of the indicator data corresponding to each business data type in the metadata of the report to be tested; finding the target metadata case corresponding to the first test data value in the metadata cases, and obtaining the second test data value of the indicator data corresponding to each business data type in the target metadata case; comparing the first test data value with the second test data value to obtain the comparison result, and determining the test result based on the comparison result.

[0082] In one embodiment, Figure 5 This is a structural block diagram of a report metadata testing device according to an embodiment of the present invention. This device is suitable for testing metadata in reports and can be implemented in hardware or software. It can be configured in an electronic device to implement a report metadata testing method according to an embodiment of the present invention. Figure 5 As shown, the device includes: a metadata classification module 510, a metadata analysis module 520, a test case generation module 530, and a test result output module 540.

[0083] The metadata classification module 510 is used to obtain metadata from the original report and classify the metadata to obtain the metadata classification result.

[0084] Metadata analysis module 520 is used to perform data analysis on each type of metadata in the metadata classification results to obtain the corresponding data analysis results;

[0085] Test case generation module 530 is used to generate metadata cases based on the data analysis results;

[0086] The test result output module 540 is used to obtain the metadata of the report to be tested provided by a third-party organization, test the metadata of the report to be tested based on the metadata case, and obtain the test results; wherein, the metadata of the report to be tested includes multiple business data types, and each business data type corresponds to the corresponding indicator data.

[0087] In this embodiment of the invention, the metadata classification module and the metadata analysis module obtain corresponding data analysis results by classifying metadata and performing multi-faceted data analysis. Based on this, the test case generation module generates metadata cases based on the data analysis results and tests the metadata of the report to be tested based on the metadata cases to obtain test results. This can improve the efficiency of testing and ensure the accuracy of report metadata testing.

[0088] In one embodiment, the metadata classification module 510 includes:

[0089] Attribution type determination unit, used to determine the attribution type of the metadata;

[0090] The data classification unit is used to divide the metadata into business metadata, technical metadata and management metadata according to the classification type, and to classify the data.

[0091] In one embodiment, the metadata analysis module 520 includes:

[0092] The lineage analysis unit is used to perform lineage analysis on various types of metadata to obtain the first data analysis result.

[0093] The impact analysis unit is used to perform data impact analysis on various types of metadata to obtain the second data analysis results.

[0094] The end-to-end analysis unit is used to perform end-to-end data analysis on various types of metadata to obtain third-party data analysis results.

[0095] The consistency analysis unit is used to perform indicator consistency analysis on various types of metadata to obtain the fourth data analysis result.

[0096] The correlation determination unit is used to take the first data analysis result, the second data analysis result, the third data analysis result, and the fourth data analysis result as the target analysis result.

[0097] In one embodiment, the test case generation module 530 includes:

[0098] The metadata modeling unit is used to perform metadata modeling on different types of metadata based on the data analysis results, and obtain modeling results; wherein, the metadata modeling includes: metadata requirement analysis, conceptual modeling, logical modeling and physical modeling;

[0099] A resource cataloging unit is used to determine the data resource cataloging in the modeling results; wherein, the data resource cataloging includes: a resource catalog, an asset catalog, and a service catalog; the resource catalog represents a catalog of all metadata resources; the asset catalog includes database information, schema information, table-level information, field information, field code information, index information, and constraint information corresponding to all metadata; the service catalog includes a data catalog and a shared data catalog that users can use according to their permissions;

[0100] The metadata case generation unit is used to determine the case type for generating the metadata case, obtain the target information corresponding to the case type in the asset catalog, and generate the corresponding metadata case based on the target information; wherein, the metadata case includes at least: report template metadata case, report dimension metadata case, report indicator metadata case, report detail metadata case, report summary metadata case, report cell formula metadata case, report multi-level drill-down metadata case, and report storage path metadata case.

[0101] In one embodiment, the metadata case includes second test data values ​​of indicator data corresponding to different business data types; correspondingly, the test result output module 540 includes:

[0102] The first data value determination unit is used to determine the first test data value of the indicator data corresponding to each of the business data types in the metadata of the report to be tested.

[0103] The second data value determination unit is used to find the target metadata case corresponding to the first test data value in the metadata case, and to obtain the second test data value of the indicator data corresponding to each of the business data types in the target metadata case.

[0104] The test result determination unit is used to compare the first test data value with the second test data value to obtain a comparison result, and determine the test result based on the comparison result.

[0105] In one embodiment, the method further includes:

[0106] The test results are then fed back to a third-party organization so that the organization can verify the data based on the test results.

[0107] The report metadata testing device provided in this embodiment of the invention can execute the report metadata testing method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0108] In one embodiment, Figure 6This is a schematic diagram of an electronic device provided for an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0109] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0110] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0111] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as report metadata testing methods.

[0112] In some embodiments, the report metadata testing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the report metadata testing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the report metadata testing method by any other suitable means (e.g., by means of firmware).

[0113] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0114] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable report metadata testing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0115] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0116] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0117] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0118] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0119] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0120] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for testing report metadata, characterized in that, The method includes: Obtain metadata from the original report and classify the metadata to obtain metadata classification results; Data analysis is performed on the metadata of each type in the metadata classification results to obtain the corresponding data analysis results; Generate metadata cases based on the data analysis results; Obtain the metadata of the report to be tested, test the metadata of the report to be tested based on the metadata case, and obtain the test results; wherein, the metadata of the report to be tested includes multiple business data types, and each business data type corresponds to the corresponding indicator data; The example of generating metadata based on the data analysis results includes: Based on the data analysis results, metadata modeling is performed on different types of metadata to obtain modeling results; wherein, the metadata modeling includes: metadata requirements analysis, conceptual modeling, logical modeling and physical modeling; The data resource catalog is determined in the modeling results; wherein, the data resource catalog includes: a resource catalog, an asset catalog, and a service catalog; the resource catalog represents a catalog of all metadata resources; the asset catalog includes database information, schema information, table-level information, field information, field code information, index information, and constraint information corresponding to all metadata; the service catalog includes a data catalog and a shared data catalog that users can use according to their permissions; Determine the case type for generating the metadata case, obtain the target information corresponding to the case type in the asset catalog, and generate the corresponding metadata case based on the target information.

2. The method according to claim 1, characterized in that, The process of classifying the report metadata to obtain metadata classification results includes: Determine the attribution type of the metadata; The metadata is divided into business metadata, technical metadata, and management metadata according to the aforementioned attribution type, and then the data is categorized.

3. The method according to claim 1, characterized in that, The data analysis of each type of metadata in the metadata classification results to obtain the corresponding data analysis results includes: Data lineage analysis is performed on various types of metadata to obtain the first data analysis results; Data impact analysis was performed on various types of metadata to obtain the second data analysis results; A third data analysis result is obtained by performing full-link data analysis on various types of metadata. A consistency analysis of metrics was performed on various types of metadata to obtain the fourth data analysis result; The first data analysis result, the second data analysis result, the third data analysis result, and the fourth data analysis result are taken as the target data analysis result.

4. The method according to claim 1, characterized in that, The metadata case includes second test data values ​​for indicator data corresponding to different business data types; correspondingly, the testing of the metadata of the report to be tested based on the metadata case to obtain test results includes: Determine the first test data value of the indicator data corresponding to each of the business data types in the metadata of the report to be tested; The target metadata case corresponding to the first test data value is found in the metadata case, and the second test data value of the indicator data corresponding to each of the business data types in the target metadata case is obtained. The first test data value is compared with the second test data value to obtain the comparison result, and the test result is determined based on the comparison result.

5. The method according to claim 1, characterized in that, The method further includes: The test results are then fed back to a third-party organization so that the organization can verify the data based on the test results.

6. A report metadata testing device, characterized in that, The device includes: The metadata classification module is used to obtain metadata from the original report and classify the metadata to obtain the metadata classification result; The metadata analysis module is used to perform data analysis on the metadata of each type in the metadata classification results and obtain the corresponding data analysis results. The test case generation module is used to generate metadata cases based on the data analysis results. The test result output module is used to obtain the metadata of the report to be tested provided by a third-party organization, test the metadata of the report to be tested based on the metadata case, and obtain the test result; wherein, the metadata of the report to be tested includes multiple business data types, and each of the business data types corresponds to the corresponding indicator data; The test case generation module includes: The metadata modeling unit is used to perform metadata modeling on different types of metadata based on the data analysis results, and obtain modeling results; wherein, the metadata modeling includes: metadata requirement analysis, conceptual modeling, logical modeling and physical modeling; A resource cataloging unit is used to determine the data resource cataloging in the modeling results; wherein, the data resource cataloging includes: a resource catalog, an asset catalog, and a service catalog; the resource catalog represents a catalog of all metadata resources; the asset catalog includes database information, schema information, table-level information, field information, field code information, index information, and constraint information corresponding to all metadata; the service catalog includes a data catalog and a shared data catalog that users can use according to their permissions; The metadata case generation unit is used to determine the case type for generating the metadata case, obtain the target information corresponding to the case type in the asset catalog, and generate the corresponding metadata case based on the target information; wherein, the metadata case includes at least: report template metadata case, report dimension metadata case, report indicator metadata case, report detail metadata case, report summary metadata case, report cell formula metadata case, report multi-level drill-down metadata case, and report storage path metadata case.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the report metadata testing method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the report metadata testing method according to any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the report metadata testing method according to any one of claims 1-5.

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