Data analysis method, device, computer equipment and storage medium

Abstract

The present application relates to a data analysis method, apparatus, computer equipment, storage medium and computer program product. The method comprises: obtaining target resource billing data reported by a multi-cloud management system; the target resource billing data comprises service items and attribute information corresponding to the service items; hierarchically grouping the service items according to preset grouping rules and attribute information corresponding to the service items to obtain hierarchical grouping results, and determining the cost data corresponding to each service item in the service catalog; based on the target resource billing data and the cost data corresponding to the service items, obtaining data analysis results for each hierarchical grouping result. The use of this method can improve the accuracy of data analysis results.

Description

Technical Field

[0001] The present application relates to the field of cloud computing technology, and in particular to a data analysis method, apparatus, computer equipment, storage medium, and computer program product. Background Art

[0002] With the development of cloud computing technology, cloud service technology has emerged. Enterprises can choose cloud service technology and shift from traditional self-built computer rooms to deploying businesses in the cloud. Among them, the cost analysis of cloud computing resources can help cloud service providers understand the cost structure and improve operational efficiency.

[0003] In the traditional method, the cloud resources requested by users are grouped by tags based on the basic data of the configuration management database CMDB (Configuration Management Database), and the cloud resource costs are allocated according to the preset tag groups to obtain the costs of each department or project.

[0004] However, in traditional methods, since the cloud resource costs are allocated to departments or projects, the resulting cost analysis has a large granularity, which will conceal the true cost source of the cloud computing resources applied for by users, and only focuses on costs. The dimension of data analysis is relatively single, resulting in poor accuracy of data analysis. Summary of the invention

[0005] Based on this, it is necessary to provide a data analysis method, apparatus, computer equipment, computer-readable storage medium and computer program product to address the above technical issues.

[0006] In a first aspect, the present application provides a data analysis method, comprising:

[0007] Obtain target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items;

[0008] hierarchically grouping the service items according to preset grouping rules and attribute information corresponding to the service items to obtain hierarchical grouping results, and determining cost data corresponding to each of the service items in the service catalog;

[0009] Based on the target resource billing data and the cost data corresponding to the service items, a data analysis result of each hierarchical grouping result is obtained.

[0010] In the above data management method, by receiving the target resource billing data reported by the multi-cloud management system and taking the service item as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules. The cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis.

[0011] In one of the embodiments, obtaining the target resource billing data reported by the multi-cloud management system includes:

[0012] Obtain the initial resource billing data reported by the multi-cloud management system;

[0013] In each of the initial resource billing data, invalid resource billing data without a contract number in the attribute information is eliminated to obtain target resource billing data.

[0014] In this embodiment, invalid resource billing data will interfere with the statistics and analysis of actual resource usage. By eliminating invalid resource billing data, redundant information can be eliminated, thereby improving the accuracy of data analysis by the data analysis system.

[0015] In one embodiment, the obtaining of initial resource billing data reported by the multi-cloud management system includes:

[0016] Receive initial resource billing data regularly reported by each multi-cloud management system, and store the initial resource billing data in a service item list;

[0017] According to a preset period, the initial resource billing data in the service item list is obtained.

[0018] In this embodiment, by storing the initial resource billing data and obtaining the initial resource billing data from the service item list according to a preset period, cross-year billing of cloud resource usage of customers of the cloud service provider can be achieved.

[0019] In one of the embodiments, after obtaining the target resource billing data reported by the multi-cloud management system, the method further includes:

[0020] Matching the service item number corresponding to the standard service item in the service catalog with the service item number in each of the target resource billing data to obtain a matching result;

[0021] In the case that the matching result is a match, the step of hierarchically grouping the service items according to the preset grouping rule and the attribute information corresponding to the service items is performed to obtain the hierarchical grouping result of the service items.

[0022] In this embodiment, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, the correctness of the service items that incur costs can be ensured, the omission of the service items that incur costs can be prevented, and the accuracy of data analysis can be improved.

[0023] In one embodiment, the method further comprises:

[0024] In the case that the matching result is a mismatch, the service item corresponding to the service item number in the target resource billing data is classified into types according to a preset processing rule to obtain cost data corresponding to the service item.

[0025] In this embodiment, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, it can be ensured that all service items that incur costs can be recorded, preventing service items from being missed and improving the accuracy of data analysis.

[0026] In one of the embodiments, when the matching result is a mismatch, the service item corresponding to the service item number in the target resource billing data is classified into types according to a preset processing rule to obtain cost data corresponding to the service item, including:

[0027] If the matching result is no match, searching the service item corresponding to the service item number by a preset field to obtain a search result;

[0028] When the retrieval result contains the preset field, or when the service item corresponding to the service item number is target type data and the resource occupancy is not empty, the service item corresponding to the service item number is determined as a virtual machine type service item, and the cost data of the virtual machine type service item is obtained.

[0029] In this embodiment, by detecting the service items in the resource billing data and determining the matching relationship between the service items and the standard service items, it can be ensured that all service items that incur costs can be recorded, preventing service items from being missed and improving the accuracy of data analysis.

[0030] In one embodiment, the step of hierarchically grouping the service items according to a preset grouping rule and the attribute information corresponding to the service items to obtain the hierarchical grouping results of the service items includes:

[0031] In the service item list, obtain the attribute information corresponding to each service item respectively;

[0032] In response to a screening operation on each attribute information of the service item, determining target attribute information in each attribute information;

[0033] An attribute combination is constructed based on the target attribute information, and service items with the same attribute combination are determined as a hierarchical grouping result of the service items.

[0034] In this embodiment, by constructing a hierarchical grouping result of the service items through target attribute information, data analysis can be performed on the target resource billing data based on business needs, and the attribute information is grouped according to the service item dimension, and the data analysis results are displayed according to the hierarchical grouping result of the service item dimension, which can improve the accuracy of the cost source in the data analysis, and thereby improve the accuracy of the data analysis.

[0035] In a second aspect, the present application also provides a data analysis device, comprising:

[0036] A first acquisition module is used to acquire target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items;

[0037] A first grouping module, configured to hierarchically group the service items according to a preset grouping rule and attribute information corresponding to the service items, obtain hierarchical grouping results of the service items, and determine cost data corresponding to each of the service items in a service catalog;

[0038] A calculation module is used to obtain data analysis results in each of the hierarchical grouping results based on the resource billing data and the cost data corresponding to the service items.

[0039] In the above data management method, by receiving the target resource billing data reported by the multi-cloud management system and taking the service item as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules. The cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis.

[0040] In one of the embodiments, the first acquisition module is specifically used to acquire initial resource billing data reported by the multi-cloud management system;

[0041] In each of the initial resource billing data, invalid resource billing data without a contract number in the attribute information is eliminated to obtain target resource billing data.

[0042] In this embodiment, invalid resource billing data will interfere with the statistics and analysis of actual resource usage. By eliminating invalid resource billing data, redundant information can be eliminated, thereby improving the accuracy of data analysis by the data analysis system.

[0043] In one of the embodiments, the first acquisition module is specifically used to receive initial resource billing data regularly reported by each multi-cloud management system, and store the initial resource billing data in the service item list;

[0044] According to a preset period, the initial resource billing data in the service item list is obtained.

[0045] In this embodiment, by storing the initial resource billing data and obtaining the initial resource billing data from the service item list according to a preset period, cross-year billing of cloud resource usage of customers of the cloud service provider can be achieved.

[0046] In one embodiment, the device further comprises:

[0047] A matching module, used to match the service item number corresponding to the standard service item in the service catalog with the service item number in each target resource billing data to obtain a matching result;

[0048] The second grouping module is used to execute the step of hierarchically grouping the service items according to the preset grouping rules and the attribute information corresponding to the service items to obtain the hierarchical grouping results of the service items when the matching result is a match.

[0049] In this embodiment, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, the correctness of the service items that incur costs can be ensured, the omission of the service items that incur costs can be prevented, and the accuracy of data analysis can be improved.

[0050] In one embodiment, the device further comprises:

[0051] The classification module is used to classify the service items corresponding to the service item numbers in the target resource billing data according to preset processing rules when the matching result is a mismatch, so as to obtain cost data corresponding to the service items.

[0052] In this embodiment, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, it can be ensured that all service items that incur costs can be recorded, preventing service items from being missed and improving the accuracy of data analysis.

[0053] In one embodiment, the division module is specifically used to retrieve the service item corresponding to the service item number by a preset field to obtain a search result when the matching result is a mismatch;

[0054] When the retrieval result contains the preset field, or when the service item corresponding to the service item number is target type data and the resource occupancy is not empty, the service item corresponding to the service item number is determined as a virtual machine type service item, and the cost data of the virtual machine type service item is obtained.

[0055] In this embodiment, by detecting the service items in the resource billing data and determining the matching relationship between the service items and the standard service items, it can be ensured that all service items that incur costs can be recorded, preventing service items from being missed and improving the accuracy of data analysis.

[0056] In one embodiment, the first grouping module is specifically used to obtain attribute information corresponding to each service item in the service item list;

[0057] In response to a screening operation on each attribute information of the service item, determining target attribute information in each attribute information;

[0058] An attribute combination is constructed based on the target attribute information, and service items with the same attribute combination are determined as a hierarchical grouping result of the service items.

[0059] In this embodiment, by constructing a hierarchical grouping result of the service items through target attribute information, data analysis can be performed on the target resource billing data based on business needs, and the attribute information is grouped according to the service item dimension, and the data analysis results are displayed according to the hierarchical grouping result of the service item dimension, which can improve the accuracy of the cost source in the data analysis, and thereby improve the accuracy of the data analysis.

[0060] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0061] Obtain target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items;

[0062] hierarchically grouping the service items according to preset grouping rules and attribute information corresponding to the service items to obtain hierarchical grouping results, and determining cost data corresponding to each of the service items in the service catalog;

[0063] Based on the target resource billing data and the cost data corresponding to the service items, a data analysis result of each of the hierarchical grouping results is obtained.

[0064] In the above data management method, by receiving the target resource billing data reported by the multi-cloud management system and taking the service item as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules. The cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis.

[0065] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0066] Obtain target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items;

[0067] hierarchically grouping the service items according to preset grouping rules and attribute information corresponding to the service items to obtain hierarchical grouping results, and determining cost data corresponding to each of the service items in the service catalog;

[0068] Based on the target resource billing data and the cost data corresponding to the service items, a data analysis result of each of the hierarchical grouping results is obtained.

[0069] In the above data management method, by receiving the target resource billing data reported by the multi-cloud management system and taking the service item as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules. The cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis.

[0070] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0071] Obtain target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items;

[0072] hierarchically grouping the service items according to preset grouping rules and attribute information corresponding to the service items to obtain hierarchical grouping results, and determining cost data corresponding to each of the service items in the service catalog;

[0073] Based on the target resource billing data and the cost data corresponding to the service items, a data analysis result of each of the hierarchical grouping results is obtained.

[0074] In the above data management method, by receiving the target resource billing data reported by the multi-cloud management system and taking the service item as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules. The cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis.

[0075] The above-mentioned cost analysis method, device, computer equipment, storage medium and computer program product obtain the target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items; the service items are hierarchically grouped according to the preset grouping rules and the attribute information corresponding to the service items to obtain the hierarchical grouping results, and the cost data corresponding to each of the service items is determined in the service catalog; based on the target resource billing data and the cost data corresponding to the service items, the data analysis results of each of the hierarchical grouping results are obtained. By adopting this method, by receiving the target resource billing data reported by the multi-cloud management system, and taking the service items as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules, the cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0077] Figure 1 An application environment diagram of a data analysis method in one embodiment;

[0078] Figure 2 A schematic diagram of a data analysis method in one embodiment;

[0079] Figure 3 A schematic diagram of a process for determining target resource billing data in one embodiment;

[0080] Figure 4 A schematic diagram of a flow chart of a method for periodically executing data analysis in one embodiment;

[0081] Figure 5 A schematic diagram of a flow chart of an exception handling method of a data analysis method in an embodiment;

[0082] Figure 6 A schematic diagram of a flow chart of abnormal processing of a data analysis method in another embodiment;

[0083] Figure 7 A schematic diagram of a process for determining a hierarchical grouping result in one embodiment;

[0084] Figure 8 A schematic diagram of a monthly unit price and monthly quantity calculation rule in one embodiment;

[0085] Fig. 9 A flowchart of an example of determining target resource billing data in one embodiment;

[0086] Fig.10 A flowchart of an example of abnormal processing of a data analysis method in an embodiment;

[0087] Fig.11 is a structural block diagram of a data analysis device in one embodiment;

[0088] Fig.12 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0089] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0090] The data analysis method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the data analysis system 102 communicates with the multi-cloud management system 104 through the network. The data storage system can store the data that the data analysis system 102 needs to process. The data storage system can be integrated on the data analysis system 102, or it can be placed on the cloud or other network servers. The data analysis system 102 obtains the target resource billing data reported by the multi-cloud management system; the resource billing data includes service items and attribute information corresponding to the service items; the data analysis system 102 hierarchically groups the service items according to the preset grouping rules and the attribute information corresponding to the service items, obtains the hierarchical grouping results of the service items, and determines the cost data corresponding to each service item in the service catalog; the data analysis system 102 calculates the data analysis results in each hierarchical grouping result based on the resource billing data and the cost data corresponding to the service items. Among them, the data analysis system 102 can be deployed on various personal computers or servers, and the server can be implemented with an independent server or a server cluster consisting of multiple servers.

[0091] In an exemplary embodiment, Figure 2 As shown, a data analysis method is provided, which is applied to Figure 1 The data analysis system 102 in FIG. 1 is used as an example to illustrate the method, which includes the following steps 202 to 206. Among them:

[0092] Step 202: Obtain target resource billing data reported by the multi-cloud management system.

[0093] The target resource billing data includes service items and attribute information corresponding to the service items;

[0094] In the embodiment of the present application, the data analysis method includes a multi-cloud management system and a data analysis system. The multi-cloud management system may be a heterogeneous multi-cloud management system, which is used to manage the cloud resource usage of users corresponding to the heterogeneous multi-cloud management system, including receiving the user's cloud resource usage application and obtaining the corresponding cloud resources from the cloud service provider according to the cloud resource usage application, and allocating the cloud resources to the user; the data analysis system may be a cost-profit analysis system, which is used to receive the target resource billing data reported by the multi-cloud management system and perform cost-profit analysis. Among them, heterogeneous cloud refers to the use of different cloud service providers and different cloud computing models by enterprises when managing and using cloud computing resources, so as to maximize the advantages of different cloud computing service providers.

[0095] The data analysis system includes the current standard service catalog and the historical standard service catalog based on the annual dimension, which are collectively referred to as the service catalog. Cloud service providers can configure and manage the current service catalog or historical services, for example, to create new service types and service items to increase the diversity of service types. When creating new service items, it is necessary to configure the service item name, service item number, time unit, and cost parameters, such as electricity cost coefficient, baseline price coefficient, extended price coefficient, standard price and quotation, so as to calculate cost data. For example, the electricity cost coefficient of a cloud service provider can be the cost of electricity consumed by the equipment that provides cloud services to the cloud service provider during operation; the baseline price coefficient and extended price coefficient are different calculation methods set for different types of cloud service items according to different specifications and usage. The electricity cost coefficient, baseline price coefficient and extended price coefficient are mainly used as key factors to evaluate the cost of cloud services. The standard price and quotation are the prices set by cloud service providers for multi-cloud management systems, which are used to provide customers with cloud service quotations. The standard price is used as a reference price for most customers. The standard price involves cost calculations in multiple aspects, including service equipment, maintenance costs, electricity costs, support and guarantees, etc.

[0096] The cloud resource usage application includes the unit price of service items, resource usage and resource usage duration independently set by the multi-cloud management system. The multi-cloud management system collects the user's cloud resource usage application, and calculates the target resource billing data in real time based on the unit price of service items, resource usage and resource usage duration in the cloud resource usage application, as the target resource billing data of the project corresponding to the cloud resource usage application, and reports the target resource billing data to the data analysis system. Optionally, the monitoring agent of the multi-cloud management system is encapsulated with the number of the multi-cloud management system. When reporting the target resource billing data, the number of the multi-cloud management system is bound to the target resource billing data and reported, so as to provide the multi-cloud management system corresponding to the target resource billing data, and then the target resource billing data corresponding to the customers of the cloud service provider can be obtained.

[0097] In an optional embodiment, the multi-cloud management system obtains the resource billing data manually filled in by the user in response to the user's manual reporting application, and reports the resource billing data manually filled in by the user to the data analysis system.

[0098] Step 204 , hierarchically grouping the service items according to the preset grouping rules and the attribute information corresponding to the service items, obtaining the hierarchical grouping results of the service items, and determining the cost data corresponding to each service item in the service catalog.

[0099] In an embodiment of the present application, the attribute information of the service item includes the year, contract number, month and the number of the multi-cloud management system. The data analysis system determines the cloud computing center based on the multi-cloud management system that reports the resource billing data, and groups the service items according to the year, contract number, month and cloud computing center according to preset grouping rules. For example, the grouping rule can be a default grouping rule, or, corresponding to the grouping dimension selected by the user, hierarchical grouping is performed according to the grouping dimension selected by the user, so that the resource billing data of each service item in the same year can be obtained, or the resource billing data corresponding to the service items in the same month but different years can be obtained.

[0100] The data analysis system includes a service catalog, which includes cost parameters corresponding to service items. The data analysis system can determine the cost data of the service items based on the cost parameters in the service catalog. The embodiment of the present application does not limit the order of steps for determining the cost data and hierarchically grouping the service items.

[0101] In an optional embodiment, the data analysis system determines whether the service catalog contains service items corresponding to the target resource billing data. If the service catalog does not contain service items corresponding to the target resource billing data, a prompt message is sent to the user or administrator role of the cloud service provider to prompt the update or modification of the service item content in the service catalog. The data analysis system can also determine whether to replace the manually input target resource billing data according to the time of receiving the target resource billing data imported by the multi-cloud management system.

[0102] Step 206, based on the target resource billing data and the cost data corresponding to the service item, obtain the data analysis result in each level grouping result.

[0103] In an embodiment of the present application, after the data analysis system obtains the target resource billing data and the cost data corresponding to the service items, it calculates the data analysis results of the service items included in each grouping result according to the hierarchical grouping of the service items, wherein the profit data of each hierarchical grouping can be obtained based on the target resource billing data and the cost data of the service items, and the profit data is used as the data analysis result of each hierarchical grouping.

[0104] Optionally, the target resource billing data may be revenue data, selling price, etc. The confirmed target resource billing data is displayed in the form of a report in the data analysis system so that the cloud service provider can perform cost-profit analysis. The report is also used to store the data analysis results obtained by the data analysis system, wherein the data analysis results may include gross profit margin, profit data, etc. Therefore, the target resource billing data and data analysis results are summarized in the report, and the report displays the results in two different time dimensions: annual comprehensive overview and annual details. The gross profit margin, cost, and revenue of one year in the annual comprehensive overview can be displayed, and the gross profit margin, cost, and revenue of each quarter and month in the annual details can also be displayed. Cost-profit analysis is performed through different time dimensions to make the cost-profit analysis more accurate.

[0105] In an optional embodiment, the data analysis system can also provide a financial data template to the multi-cloud management system. Users of the multi-cloud management system download the template to fill in and upload the financial data. The data analysis system can calculate the difference between business income and financial income based on the resource billing data of the income detail management, and assist the cloud service provider in cost-profit analysis. Optionally, the data analysis system can set discounts for the monthly resource billing of different multi-cloud management systems and confirm their implementation.

[0106] In the above data management method, by receiving the target resource billing data reported by the multi-cloud management system and taking the service item as the data analysis dimension, the service items in each target resource billing data are grouped according to the preset grouping rules. The cost of each service item under different grouping rules can be calculated, and the real cost source of cloud computing resources can be obtained, thereby improving the accuracy of cost analysis.

[0107] In an exemplary embodiment, Figure 3 As shown, step 202 includes steps 302 to 304. Among them:

[0108] Step 302: Obtain initial resource billing data reported by the multi-cloud management system.

[0109] In the embodiment of the present application, users who use the multi-cloud management system usually initiate cloud resource usage applications to cloud service providers through the multi-cloud management system based on projects. At the same time, the multi-cloud management system calculates the resource billing data of the current trial application based on the cloud resource usage application as the initial resource billing data, and reports the initial resource billing data to the data analysis system while sending the cloud resource usage application. Then, the data analysis system can receive the initial resource billing data reported by the multi-cloud management system in real time. Optionally, the multi-cloud management system can store the calculated initial resource billing data after obtaining the cloud resource usage application, and report the stored initial resource billing data to the data analysis system at regular intervals.

[0110] In an optional embodiment, the data analysis system stores the initial resource billing data reported by the multi-cloud management system, and when the data analysis system processes the data, it obtains the initial resource billing data according to a preset period.

[0111] Step 304: In each initial resource billing data, the invalid resource billing data without a contract number in the attribute information is eliminated to obtain the target resource billing data.

[0112] In an embodiment of the present application, after the data analysis system obtains the initial resource billing data, it is necessary to detect the initial resource billing data. Specifically, the attribute information of the initial resource billing data includes a contract number, which is used to identify a project, and a project may include multiple service items. Since the quotation or standard price in the multi-cloud management system is associated with the contract number, when the contract number is missing or an incorrect contract number exists in the attribute information of the initial resource billing data, the data analysis system will not be able to match the target resource billing data when performing data analysis. Therefore, the data analysis system determines the invalid resource billing data with an invalid contract number, eliminates the invalid resource billing data, and uses the initial resource billing data after eliminating the invalid resource billing data as the target resource billing data. Optionally, after eliminating the invalid resource billing data, the data analysis system sends a prompt message to the administrator of the cloud service provider or the administrator of the multi-cloud management system to re-check the invalid resource billing data to prevent the omission of service items with costs during data analysis calculations.

[0113] In this embodiment, invalid resource billing data will interfere with the statistics and analysis of actual resource usage. By eliminating invalid resource billing data, invalid information can be eliminated, thereby improving the accuracy of data analysis by the data analysis system.

[0114] In an exemplary embodiment, Figure 4 As shown, step 302 includes steps 402 to 404. Among them:

[0115] Step 402: Receive initial resource billing data regularly reported by each multi-cloud management system, and store the initial resource billing data in a service item list.

[0116] In the embodiment of the present application, the cloud service provider can perform cross-year calculations based on the user's use of cloud resources. Specifically, after the service item unit price set by the multi-cloud management system takes effect and the resource billing of the user's cloud resource use application takes effect, the cloud resource usage is charged. After receiving the initial resource billing data periodically reported by the multi-cloud management system, the data analysis system stores the resource billing data in the service item list.

[0117] Step 404: Obtain initial resource billing data in the service item list according to a preset period.

[0118] In the embodiment of the present application, the data analysis system can obtain the initial resource billing data stored in the service item list according to the preset period when there is a need for data analysis. The preset period can be data analysis according to an annual period or a quarterly period. Optionally, the data analysis system can respond to the data analysis request of the cloud service provider, obtain the initial resource billing data stored in the service item list in real time, and verify the initial resource billing data to obtain the target resource billing data, perform data analysis based on the target resource billing data, and obtain the data analysis result, that is, the cost-profit analysis result.

[0119] In this embodiment, by storing the initial resource billing data and obtaining the initial resource billing data from the service item list according to a preset period, cross-year billing of cloud resource usage of customers of the cloud service provider can be achieved.

[0120] In an exemplary embodiment, Figure 5 As shown, after step 202, the method further includes steps 502 to 504. Among them:

[0121] Step 502: Match the service item number corresponding to the standard service item in the service catalog with the service item number in each target resource billing data to obtain a matching result.

[0122] In the embodiment of the present application, the data analysis system needs to detect whether the service items have corresponding cost data before hierarchically grouping the service items. In the service catalog, the data analysis system can match the service item number corresponding to the standard service item with the service item number of the target resource billing data. According to the matching result between the standard service item and the service item reported by the multi-cloud management system, it can be determined whether the service catalog contains the standard service item corresponding to the reported service item, so as to determine the cost data of each service item in each target resource billing data reported by the multi-cloud management system.

[0123] In an exemplary embodiment, the data analysis system obtains a list of standard service item numbers through the service directory provided by the cloud service provider, and determines the service item number of each service item included in the target resource billing data. For each service item number in the target resource billing data, the service item number is matched and compared with each standard service item number in the list of standard service item numbers to determine whether the matching result is that the service item number can correspond to the standard service item number. Optionally, the service item number can be the same as the standard service item number, or it can have a corresponding relationship with the standard service item, that is, each service item number has a corresponding standard service item in the service directory. The corresponding relationship can be provided by the cloud service provider, or the corresponding relationship between the service item number and the standard service item number set by the cloud service provider can be called in real time by calling the API (Application Programming Interface) provided by the cloud service provider.

[0124] Step 504, when the matching result is a match, the step of hierarchically grouping the service items according to the preset grouping rules and the attribute information corresponding to the service items is executed to obtain the hierarchical grouping result of the service items.

[0125] In an embodiment of the present application, when the matching result between the service item number and the standard service item number is a match, it means that the service catalog contains standard service items corresponding to the service items in the target resource billing data. The data analysis system can determine the cost data of the service items through the service catalog and subsequently perform data analysis on the service items. The data analysis system does not need to operate on the service items and meets the conditions for executing subsequent steps. Therefore, when the matching result is a match, the data analysis system executes step 204 to hierarchically group the service items according to the preset grouping rules and the attribute information corresponding to the service items to obtain the hierarchical grouping results of the service items. This process has been described in step 204 and will not be repeated here.

[0126] In this embodiment, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, the correctness of the service items that incur costs can be ensured, the omission of the service items that incur costs can be prevented, and the accuracy of data analysis can be improved.

[0127] In an exemplary embodiment, when the matching result is a mismatch, other determination methods are provided for the cost data of the service item. Specifically, the method further includes step 506. Among them:

[0128] Step 506: When the matching result is a mismatch, the service item corresponding to the service item number in the target resource billing data is classified according to a preset processing rule to obtain cost data corresponding to the service item.

[0129] In an embodiment of the present application, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, it is possible to ensure that all service items that incur costs can be recorded, prevent service items from being omitted, and improve the accuracy of data analysis. The data analysis system can define preset processing rules based on business needs and the characteristics of the target resource billing data. For example, the types of service items are divided based on pattern matching, keyword matching, or rule sets of service item numbers. In the case where the matching result is a mismatch, there may be no standard service item corresponding to the service item in the target resource billing data in the service catalog. It may be that the service catalog has not been updated or the target resource billing data contains special service items, which may also incur costs. Therefore, it is necessary to further confirm the service item with a mismatch as the matching result.

[0130] The data analysis system can judge and classify the unmatched service item numbers one by one through preset processing rules. The data analysis system matches the service item numbers according to specific patterns, keywords or other rules, and classifies them into corresponding service item types. For example, regular expressions, string functions or other appropriate methods can be used to implement the classification of service item number types.

[0131] After completing the classification of service item types, the data analysis system can calculate and record the cost data corresponding to the service item according to the cost calculation rules corresponding to the service item types. The calculation rules can be pre-defined formulas, configuration files or conditional statements, and the processing occupied resources, memory occupied resources or storage occupied resources corresponding to the service item types are matched with the standard service items in the service catalog to directly perform cost calculation based on the resource occupation situation and obtain the cost data corresponding to the service item.

[0132] In this embodiment, by detecting the service items in the target resource billing data and determining the matching relationship between the service items and the standard service items, it can be ensured that all service items that incur costs can be recorded, preventing service items from being missed and improving the accuracy of data analysis.

[0133] In an exemplary embodiment, Figure 6 As shown, step 506 includes steps 602 to 604. Among them:

[0134] Step 602: When the matching result is no match, a preset field is searched for the service item corresponding to the service item number to obtain a search result.

[0135] In an embodiment of the present application, the preset field is a "virtual" field. When the matching result of the service item number in the target resource billing data and the standard service item number in the service catalog is a mismatch, the data analysis system searches for the service item whose service item number does not match, determines whether the service item name of the service item contains the "virtual" field, and obtains the search result.

[0136] Step 604, when the search result contains preset fields, or when the service item corresponding to the service item number is target type data and the resource occupancy is not empty, the service item corresponding to the service item number is determined as a virtual machine type service item, and the cost data of the virtual machine type service item is obtained.

[0137] Among them, the target type data is manually imported type data.

[0138] In an embodiment of the present application, when the name of a service item contains a "virtual" field, or when the service item is manually imported type data, and when the resource occupancy such as CPU or memory is not empty, it means that the service item has incurred costs, then the data analysis system will treat the service item as a special virtual machine, and determine the type corresponding to the service item as a virtual machine type service item. Among them, the virtual machine type can also be a secondary virtual machine type, which is a special type in the service catalog. Optionally, when both the manually imported type data and the target resource billing data reported by the multi-cloud management system cannot be matched to the corresponding standard service item in the service catalog, the cost data is calculated based on the uploaded data.

[0139] In this embodiment, by detecting the service items in the resource billing data and determining the matching relationship between the service items and the standard service items, it can be ensured that all service items that incur costs can be recorded, preventing service items from being missed and improving the accuracy of data analysis.

[0140] In an exemplary embodiment, Figure 7 As shown, step 204 includes steps 702 to 706. Among them:

[0141] Step 702: Obtain attribute information corresponding to each service item in the service item list.

[0142] In an embodiment of the present application, the service item list is used to store resource billing data reported by each multi-cloud management system, and the data analysis system obtains the target resource billing data reported by each multi-cloud management system through the service item list.

[0143] Step 704, in response to the screening operation on each attribute information of the service item, determining target attribute information in each attribute information.

[0144] In the embodiment of the present application, the administrator of the cloud service provider can filter the attribute information to be analyzed based on the analysis requirements and determine the target attribute information from the multiple attribute information. For example, the administrator can use the year and the multi-cloud management system as the target attribute information, and the data analysis system can display the data analysis results corresponding to each service item of a multi-cloud management system in a certain year.

[0145] Step 706: construct an attribute combination based on the target attribute information, and determine the service items with the same attribute combination as the hierarchical grouping result of the service items.

[0146] In an embodiment of the present application, the data analysis system combines the target attribute information obtained in response to the user's screening operation, and hierarchically groups the service items according to the attribute combination, and divides the service items with the same attribute combination into the same hierarchical grouping result. For example, based on the two attributes of service type and billing method, pay-as-you-go virtual machines, annual and monthly package virtual machines, and pay-as-you-go object storage can be grouped into one group, and annual and monthly package object storage can be grouped into another group. Alternatively, the hierarchical grouping result can be a month and a contract number. Under this hierarchical grouping result, the data analysis system can display the cost-profit analysis results of each service item included in the same contract number in the same month of different years.

[0147] In an optional embodiment, the data analysis system can optimize the hierarchical grouping according to the business requirements and the attribute information contained in the service item list. For example, the data analysis system can preliminarily group the service items according to the service item name, description information, association relationship, etc. in the attribute heart, so that the grouping result is more accurate.

[0148] In this embodiment, by constructing a hierarchical grouping result of the service items through target attribute information, data analysis can be performed on the target resource billing data based on business needs, and the attribute information is grouped according to the service item dimension, and the data analysis results are displayed according to the hierarchical grouping result of the service item dimension, which can improve the accuracy of the cost source in the data analysis, and thereby improve the accuracy of the data analysis.

[0149] In an exemplary embodiment, Figure 8 As shown, Figure 8 The multi-cloud management system performs calculation logic for monthly unit price and monthly quantity according to preset calculation rules, including monthly unit price of service item configuration in years, monthly unit price of service item configuration in days, and monthly unit price of service item configuration in hours. Then, the monthly quantity is obtained by using the billing data and monthly unit price calculated by resources according to the service item price and billing duration.

[0150] In an exemplary embodiment, Fig. 9 As shown, Fig. 9The verification process of the data reported by the multi-cloud management system or manually imported data for the data analysis system includes filtering the data with empty contract number, summarizing according to the cloud computing center (multi-cloud management system), contract number and month, and determining whether to update the current data based on the correspondence between the standard service items and service items included in the service catalog.

[0151] In an exemplary embodiment, Fig.10 As shown, Fig.10 It is the process of the data analysis system verifying the service item according to the standard service item number. When the standard service item number does not match the service item number, the service item type is judged on the imported data of the multi-cloud management system and the manually imported data respectively to determine whether the current service item has incurred costs, and then the target resource billing data corresponding to the current service item is uploaded.

[0152] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0153] Based on the same inventive concept, the embodiment of the present application also provides a data analysis device for implementing the data analysis method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more data analysis device embodiments provided below can refer to the limitations on the data analysis method above, and will not be repeated here.

[0154] In an exemplary embodiment, Fig.11 As shown, a data analysis device 1100 is provided, comprising: a first acquisition module 1101, a first grouping module 1102 and a calculation module 1103, wherein:

[0155] The first acquisition module 1101 is used to acquire target resource billing data reported by the multi-cloud management system; the target resource billing data includes service items and attribute information corresponding to the service items;

[0156] The first grouping module 1102 is used to hierarchically group the service items according to the preset grouping rules and the attribute information corresponding to the service items, obtain the hierarchical grouping results of the service items, and determine the cost data corresponding to each service item in the service catalog;

[0157] The calculation module 1103 is used to obtain the data analysis results in each level grouping result based on the resource billing data and the cost data corresponding to the service items.

[0158] In one of the embodiments, the first acquisition module 1101 is specifically used to acquire initial resource billing data reported by the multi-cloud management system;

[0159] In each initial resource billing data, invalid resource billing data without a contract number in the attribute information is eliminated to obtain the target resource billing data.

[0160] In one embodiment, the first acquisition module 1101 is specifically used to receive initial resource billing data regularly reported by each multi-cloud management system, and store the initial resource billing data in the service item list;

[0161] Obtain the initial resource billing data in the service item list according to the preset period.

[0162] In one embodiment, the apparatus 1100 further includes:

[0163] A matching module, used to match the service item number corresponding to the standard service item in the service catalog with the service item number in each target resource billing data to obtain a matching result;

[0164] The second grouping module is used to execute the step of hierarchically grouping the service items according to the preset grouping rules and the attribute information corresponding to the service items to obtain the hierarchical grouping results of the service items when the matching result is a match.

[0165] In one embodiment, the apparatus 1100 further includes:

[0166] The classification module is used to classify the service items corresponding to the service item numbers in the target resource billing data according to preset processing rules when the matching result is a mismatch, so as to obtain cost data corresponding to the service items.

[0167] In one embodiment, the partitioning module is specifically used to retrieve the service item corresponding to the service item number by a preset field when the matching result is a mismatch, to obtain a search result;

[0168] When the search result contains preset fields, or the service item corresponding to the service item number is target type data and the resource occupancy is not empty, the service item corresponding to the service item number is determined as a virtual machine type service item, and the cost data of the virtual machine type service item is obtained.

[0169] In one embodiment, the first grouping module 1102 is specifically used to obtain attribute information corresponding to each service item in the service item list;

[0170] In response to a screening operation on each attribute information of a service item, determining target attribute information in each attribute information;

[0171] An attribute combination is constructed based on the target attribute information, and service items with the same attribute combination are determined as the hierarchical grouping result of the service items.

[0172] Each module in the above data analysis device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0173] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.12 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store initial resource billing data and target resource billing data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data analysis method is implemented.

[0174] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0175] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0176] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0177] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0178] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0179] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0180] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0181] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A data analysis method, characterized in that: The method comprises: Obtain target resource billing data reported by the multi-cloud management system; the target resource billing data includes a service item and attribute information corresponding to the service item, and the service item includes a configuration cost parameter; the target resource billing data is calculated based on the service item unit price, resource usage, and resource usage duration in the cloud resource usage application; The service items are hierarchically grouped according to preset grouping rules and attribute information corresponding to the service items to obtain hierarchical grouping results, and cost data corresponding to each service item is determined in the service catalog; the hierarchical grouping results include the service items within the same year or the service items in the same month but different years; Based on the target resource billing data and the cost data corresponding to the service item, a data analysis result of each hierarchical grouping result is obtained; the data analysis result is profit data of each hierarchical grouping; The step of hierarchically grouping the service items according to a preset grouping rule and the attribute information corresponding to the service items to obtain the hierarchical grouping results of the service items includes: In the service item list, obtain the attribute information corresponding to each service item respectively; In response to a screening operation on each attribute information of the service item, determining target attribute information in each attribute information; An attribute combination is constructed based on the target attribute information, and service items with the same attribute combination are determined as a hierarchical grouping result of the service items.

2. The method according to claim 1, characterized in that The obtaining of target resource billing data reported by the multi-cloud management system includes: Obtain the initial resource billing data reported by the multi-cloud management system; In each of the initial resource billing data, invalid resource billing data without a contract number in the attribute information is eliminated to obtain target resource billing data.

3. The method according to claim 2, characterized in that The obtaining of initial resource billing data reported by the multi-cloud management system includes: Receive initial resource billing data regularly reported by each multi-cloud management system, and store the initial resource billing data in a service item list; According to a preset period, the initial resource billing data in the service item list is obtained.

4. The method according to claim 1, characterized in that After obtaining the target resource billing data reported by the multi-cloud management system, the method further includes: Matching the service item number corresponding to the standard service item in the service catalog with the service item number in each of the target resource billing data to obtain a matching result; In the case that the matching result is a match, the step of hierarchically grouping the service items according to the preset grouping rule and the attribute information corresponding to the service items is performed to obtain the hierarchical grouping result of the service items.

5. The method according to claim 4, characterized in that: The method further comprises: In the case that the matching result is a mismatch, the service item corresponding to the service item number in the target resource billing data is classified into types according to a preset processing rule to obtain cost data corresponding to the service item.

6. The method according to claim 5, characterized in that When the matching result is a mismatch, the service item corresponding to the service item number in the target resource billing data is classified according to a preset processing rule to obtain cost data corresponding to the service item, including: If the matching result is no match, searching the service item corresponding to the service item number by a preset field to obtain a search result; When the retrieval result contains the preset field, or when the service item corresponding to the service item number is target type data and the resource occupancy is not empty, the service item corresponding to the service item number is determined as a virtual machine type service item, and the cost data of the virtual machine type service item is obtained.

7. A data analysis device, characterized in that: The device comprises: A first acquisition module is used to acquire target resource billing data reported by the multi-cloud management system; the target resource billing data includes a service item and attribute information corresponding to the service item, and the service item includes a configuration cost parameter; the target resource billing data is calculated by the service item unit price, resource usage and resource usage duration in the cloud resource usage application; A first grouping module is used to hierarchically group the service items according to a preset grouping rule and attribute information corresponding to the service items, obtain hierarchical grouping results of the service items, and determine cost data corresponding to each of the service items in the service catalog; the hierarchical grouping results include the service items in the same year or the service items in the same month but different years; A calculation module, used to obtain a data analysis result in each of the hierarchical grouping results based on the resource billing data and the cost data corresponding to the service item; the data analysis result is profit data for each hierarchical grouping; The first grouping module is specifically used to obtain the attribute information corresponding to each service item in the service item list; In response to a screening operation on each attribute information of the service item, determining target attribute information in each attribute information; An attribute combination is constructed based on the target attribute information, and service items with the same attribute combination are determined as a hierarchical grouping result of the service items.

8. The device according to claim 7, characterized in that The first acquisition module is specifically used to obtain initial resource billing data reported by the multi-cloud management system; In each of the initial resource billing data, invalid resource billing data without a contract number in the attribute information is eliminated to obtain target resource billing data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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