Enterprise digital service method, device and medium based on data analysis

Abstract

The application relates to the technical field of data processing, in particular to an enterprise digitization service method, device and equipment based on data analysis and a medium, the method comprising the following steps: receiving user request information, wherein the user request information at least comprises a target data type; matching the target data type with a plurality of preset data categories to determine a target data category corresponding to the target data type, wherein the target category comprises the target data type and a plurality of other data types, the plurality of preset data categories are obtained by classifying a plurality of data types, the plurality of data types are determined based on respective data labels of the plurality of data, and the plurality of data are obtained from different data sources; obtaining target data corresponding to all data types in the target data category, and pushing all the target data to a client by using a preset data security sandbox. The application has the technical effect of improving data search efficiency.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, device, and medium for enterprise digital services based on data analysis. Background Technology

[0002] In the development of government and enterprise units, the utilization rate of data can be improved through reasonable data processing. The improvement of data utilization rate has a significant impact on the correctness of various decisions made by government and enterprise units. Furthermore, the various business decisions of government and enterprise units and the correctness of these decisions are closely related to the digital transformation of government and enterprise units.

[0003] In related technologies, when users need decision support, the system obtains the user's key fields and recommends a single data point that perfectly matches those fields. However, when users need to refer to multiple data points from any category for decision support, simply recommending a single data point cannot meet their needs. Users would need to perform multiple searches to obtain the data. Therefore, recommending only a single data point in related technologies results in low data search efficiency.

[0004] Therefore, how to solve the above-mentioned technical problems is an urgent issue that needs to be addressed by those skilled in the art. Summary of the Invention

[0005] To improve search efficiency, this application provides a method, apparatus, device, and medium for enterprise digital services based on data analysis.

[0006] Firstly, this application provides a data analysis-based enterprise digital service method, employing the following technical solution: A data analytics-based approach to enterprise digital services includes: Receive user request information, wherein the user request information includes at least the target data type; The target data type is matched with several preset data categories to determine the target data category corresponding to the target data type. The target category includes the target data type and several other data types. The several preset data categories are obtained by classifying several data types. The several data types are determined based on the data tags corresponding to each of the several data types. The several data types are obtained from different data sources. Obtain the target data corresponding to each data type in the target data category, and push all target data to the client using a preset data security sandbox.

[0007] By adopting the above technical solution, user request information with target data type is obtained, and the target data type is matched with several preset data categories. By determining the target data category and determining multiple other data types based on the target data category, a large amount of relevant data can be quickly obtained. Then, the target data corresponding to each data type in the target data category can be obtained quickly to improve search efficiency. Finally, the target data is pushed to the client through a preset data security sandbox, which further enhances data protection while improving search efficiency.

[0008] In one possible implementation, after matching the target data type with several preset data categories to determine the target data category corresponding to the target data type, the method further includes: Obtain the user's identity information; Based on the user's identity information and preset data viewing permission information, the data viewing permission information corresponding to the user's identity information is determined, wherein the data viewing permission represents the data range corresponding to each data type in the target data category that the user can view; Accordingly, obtaining the target data corresponding to each data type in the target data category includes: Based on the data viewing permission information, retrieve the target data corresponding to each data type in the target data category from the database.

[0009] By adopting the above technical solution, user identity information is obtained. Different users correspond to different identity identifiers, and different identity identifiers correspond to different user data viewing permissions. Based on the user's identity identifier, the corresponding data viewing permissions are determined. Based on the data viewing permission information, the data that the user can view is filtered from the database, which can effectively reduce the probability of data leakage and improve the security of data protection.

[0010] In one possible implementation, pushing all target data to the client using a preset data security sandbox includes: Obtain the data label corresponding to each target data; Based on the data tags corresponding to each of the target data and several preset privacy data tags, it is determined whether privacy data exists; If so, all target data identified as private data will be anonymized, and the anonymized target data will be pushed to the client.

[0011] By adopting the above technical solution, it is possible to determine whether privacy data exists based on data tags and several preset privacy data tags. If privacy data exists, it can be desensitized. Through desensitization, data security can be improved and privacy data leakage can be prevented.

[0012] In one possible implementation, after pushing all target data to the client using a pre-defined data security sandbox, the following is also included: Get the current space information within the preset data security sandbox space after all target data pushes are completed. The current space information describes the contents of the preset data security sandbox space after all target data pushes are completed. Determine whether the current spatial information differs from the preset initial spatial information; If so, the preset data security sandbox will be restored based on the current spatial information.

[0013] By adopting the above technical solution, the current spatial information of the preset data security sandbox is obtained, and it is determined whether the current spatial information is different from the preset initial spatial information. If they are different, it indicates that the current spatial information is the same as the preset initial spatial information and there is additional spatial information. Therefore, restoration processing is required to ensure the normal use of the preset data security sandbox and reduce the impact on the user's next use.

[0014] In one possible implementation, the current spatial information includes webpage loading information and process information. If so, then the preset data security sandbox is restored based on the current spatial information, including: If so, when the current spatial information is webpage loading information, close the webpage loaded in the preset data security sandbox; When the current spatial information is process information, clear the processes in the preset data security sandbox.

[0015] By adopting the above technical solution, when the current spatial information is distinguishable webpage loading information, the webpage loaded in the preset data security sandbox is closed; if the current spatial information is process information, the processes in the preset data security sandbox are cleared to realize the restoration process of the preset data security sandbox. By restoring the preset data security sandbox, the impact on the next preset data security sandbox can be effectively reduced, so as to ensure the normal use of the preset data security sandbox.

[0016] In one possible implementation, before pushing all target data to the client using a preset data security sandbox, the method further includes: Based on all target data, determine the required space of the preset data security sandbox needed to recommend all target data, where the required space represents the size of the preset data security sandbox needed to recommend all target data. Get the current space volume of the preset data security sandbox; Determine whether the required space amount is less than the current space amount; If so, then all target data will be pushed to the client using the preset data security sandbox; Otherwise, the push priority corresponding to each target data is obtained, and several target data are pushed to the client in sequence based on the push priority corresponding to each target data.

[0017] By adopting the above technical solution, the required space of the preset data security sandbox for recommending all target data is determined. By judging the current space and the required space, it can be determined whether the preset data security sandbox can push all target data. If the preset data security sandbox cannot push all target data, the target data is pushed sequentially based on the push priority corresponding to each target data. Recommending target data based on priority can avoid the probability of the preset data security sandbox crashing when pushing all data, and further improve the stability of the preset data security sandbox operation.

[0018] In one possible implementation, obtaining the priority corresponding to each target data and pushing all target data to the client based on the priority of the target data at each moment includes: Obtain the historical push information corresponding to each of the target data, where the push information represents the number of historical pushes within a preset time period; The priority of each target data is determined based on each target data and its corresponding historical push count; The target data is pushed to the client in sequence according to the push priority of each target data.

[0019] By adopting the above technical solution, the push priority of each target data can be accurately determined based on the historical push count of each target data within a preset time period. Furthermore, based on the push priority of each target data, high-priority target data can be recommended first, and all target data can be pushed in batches according to priority, thereby improving the user experience without affecting the preset data security sandbox space.

[0020] Secondly, this application provides an enterprise digital service device based on data analysis, which adopts the following technical solution: A data analytics-based enterprise digital service device includes: The receiving module is used to receive user request information, wherein the user request information includes at least the target data type; The target data category determination module is used to match the target data type with several preset data categories to determine the target data category corresponding to the target data type. The target category includes the target data type and several other data types. The several preset data categories are obtained by classifying the multiple data types. The multiple data types are determined based on the data tags corresponding to each of the multiple data types. The multiple data types are obtained from different data sources. The data push module is used to obtain target data corresponding to each data type in the target data category, and push all target data to the client using a preset data security sandbox.

[0021] Thirdly, this application provides an electronic device that adopts the following technical solution: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute a data analytics-based enterprise digital service approach as described in any of the first aspects.

[0022] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform a data analysis-based enterprise digital service method as described in any of the first aspects.

[0023] In summary, this application includes at least one of the following beneficial technical effects: 1. Obtain user request information with the target data type, match the target data type with several preset data categories to determine the target data category corresponding to the target data type, and effectively expand the data range by determining the target data category; then obtain the target data corresponding to each data type in the target data category, so that only the target data type is needed to quickly obtain a large amount of relevant data, and then push the target data to the client through a preset data security sandbox, thereby improving search efficiency and enhancing data protection.

[0024] 2. Based on data tags and several preset privacy data tags, it can be determined whether privacy data exists. If privacy data exists, it can be de-identified. Through de-identification, the security of enterprise data can be improved and the leakage of privacy data can be prevented.

[0025] 3. Determine the required space of the preset data security sandbox for recommending all target data. By judging the current space and the required space, it can be determined whether the preset data security sandbox can push all target data. If the preset data security sandbox cannot push all target data, target data is pushed sequentially based on the push priority of each target data. Recommending target data based on priority can avoid the probability of the preset data security sandbox crashing when pushing all data, effectively improving the stability of the preset data security sandbox operation. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating a data analysis-based enterprise digital service method provided in an embodiment of this application.

[0027] Figure 2 This is a schematic diagram of the structure of an enterprise digital service device based on data analysis, provided in an embodiment of this application.

[0028] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0029] The following is in conjunction with the appendix Figure 1 To be continued Figure 3 This application will be described in further detail.

[0030] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they are within the scope of this application.

[0031] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0033] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0034] This application provides a data analysis-based enterprise digital service method executed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this connection.

[0035] Combination Figure 1 , Figure 1 This application provides a flowchart illustrating an enterprise-level digital service method based on data analysis, wherein the method includes steps S101, S102, and S103, wherein: Step S101: Receive user request information, wherein the user request information includes at least the target data type.

[0036] Specifically, users can log in to their accounts through the client portal, access the service platform, and send request information carrying the target data type. This user request information can be a string, such as "query financial data" or "search personnel data." Users can be different types of government or enterprise entities, or any employee within those entities. In this embodiment, government or enterprise entities can include: government agencies, private enterprises, state-owned enterprises, and public institutions.

[0037] Step S102: Match the target data type with several preset data categories to determine the target data category corresponding to the target data type. The target category includes the target data type and several other data types. The several preset data categories are obtained by classifying the multiple data types. The multiple data types are determined based on the data labels corresponding to the multiple data types. The multiple data types are obtained from different data sources.

[0038] Specifically, a target data type can be matched with several preset data categories using data tags. This can include: obtaining the data tags for the target data type; matching the data tags for the target data type with the corresponding data tags for each of the preset data categories; and determining the data category corresponding to the target data type through matching. In this embodiment, preferably, the preset data categories include: personnel data, financial data, transaction data, and material data. These preset data categories are pre-input and stored in the electronic device. Each preset data category includes several data types. For example, personnel data may include attendance data, job data, and employee personal information data; financial data may include: equipment purchase cost data, fixed asset data, salary data, and government / enterprise revenue data; transaction data may include: data corresponding to various government / enterprise activities; and material data may include: equipment purchase data, equipment maintenance data, and equipment usage data. In this embodiment, each data type is determined based on multiple data sets and their corresponding data tags. The data tag for each data set can be determined based on the data source and its operational nature. For example, when the data source is a facial recognition device, the data tag can be determined as attendance; however, when the data source is a financial statement, the data tag can be determined as government / enterprise revenue data. In this embodiment, the multiple data sources can be hardware devices, such as facial recognition devices, smart meter devices, and smart street light devices; they can also be data collected from software, such as financial statements and table data manually entered by employees.

[0039] Step S103: Obtain the target data corresponding to each data type in the target data category, and push all target data to the client using the preset data security sandbox.

[0040] Specifically, a pre-defined data security sandbox, also known as a data sandbox, is a virtual system program deployed within the agent's network. It can connect to both the external data source server and the agent's internal server via the network. Deploying a bastion host within the agent's network allows for the configuration of the pre-defined data security sandbox. Furthermore, the data within the pre-defined data security sandbox is completely closed; users can only access the data but cannot download it, thus effectively ensuring data security.

[0041] Furthermore, after determining the target data category corresponding to the user's target data type, all data types within the target data category and their corresponding target data can be retrieved from the data repository corresponding to that category. The electronic device then places all data corresponding to the target data type into a preset data security sandbox, where the user can view all target data. This preset data security sandbox is pre-built and hosted on a server. By using the preset data security sandbox, a secure program execution environment can be created for the user, thereby effectively improving the security of various user operations.

[0042] Based on the above embodiments, user request information with a target data type is obtained, and the target data type is matched with several preset data categories to determine the target data category corresponding to the target data type. By determining the target data category, the data range can be effectively expanded. Then, the target data corresponding to each data type in the target data category is obtained. Thus, only the target data type is needed to quickly obtain a large amount of relevant data. Then, the target data is pushed to the client through a preset data security sandbox. Furthermore, while improving search efficiency, the protection of data is also enhanced.

[0043] Furthermore, in this embodiment of the application, after matching the target data type with several preset data categories to determine the target data category corresponding to the target data type, steps SA1-SA2 (not shown in the accompanying drawings) are further included, wherein: Step SA1: Obtain the user's identity information.

[0044] Specifically, users can log in using an account and password, or via mobile phone number and SMS verification. Each user's account or mobile phone number serves as their unique identifier. Upon login, the user's identifier information is automatically uploaded to their electronic device.

[0045] Step SA2: Based on the user's identity information and preset data viewing permission information, determine the data viewing permission information corresponding to the user's identity information. The data viewing permission represents the data range corresponding to each data type in the target data category that the user can view.

[0046] Retrieve the target data corresponding to each data type within the target data category, including: Based on data viewing permission information, retrieve the target data corresponding to each data type in the target data category from the database.

[0047] Specifically, preset data viewing permission information represents the data viewing permissions corresponding to a user's identity information. That is, preset data viewing permission information can include each user's identity and corresponding data viewing scope. Different users may have the same or different data viewing permission information. However, when a user views another user's data, due to the preset data viewing permissions, the user cannot view all of that user's data. It can be understood that the preset data viewing permission information is pre-set by other users in their electronic devices; that is, the preset data viewing permission information set by other users can limit the user's data viewing scope, and different data viewing permissions can be set for different users.

[0048] Based on the above embodiments, user identity information is obtained. Different users correspond to different identity identifiers, and different identity identifiers correspond to different user data viewing permissions. Based on the user's identity identifier, the corresponding data viewing permissions are determined. Based on the data viewing permission information, the data that the user can view is filtered from the database, which can effectively reduce the probability of data leakage and improve the security of data protection.

[0049] Furthermore, in this embodiment of the application, a preset data security sandbox is used to push all target data to the client, including steps SB1-SB3 (not shown in the figures), wherein: Step SB1: Obtain the data label corresponding to each target data.

[0050] Specifically, the data tag corresponding to each target data can be determined based on the key fields of the data or based on the source of the target data. For example, when the source of the target data is a facial recognition device, the data tag corresponding to the target data can be determined as attendance. The data tag corresponding to each target data is pre-stored in the electronic device.

[0051] Step SB2: Based on the data tags corresponding to all target data and several preset privacy data tags, determine whether privacy data exists.

[0052] Specifically, several preset privacy data tags are pre-stored in electronic devices. The preset privacy data tags set by different government and enterprise units can be the same or different; this application embodiment does not impose any restrictions, and users can set them themselves. For example, the home addresses and bank card numbers of employees in a government or enterprise unit are considered privacy data for that unit, therefore, the preset privacy data tags for that unit can be home addresses and bank card numbers. All target data are matched one by one with each preset privacy data tag. If any target data has a data tag that matches a preset privacy data tag, then privacy data is determined to exist. Further, step SB3 is executed to de-identify the target data determined to be privacy data, thereby effectively improving the security of government and enterprise data and preventing privacy data leakage. Otherwise, it indicates that no privacy data exists, and all target data can be directly pushed to the client through the preset data security sandbox.

[0053] Step SB3: If yes, then all target data identified as privacy data will be anonymized, and all anonymized target data will be pushed to the client.

[0054] Specifically, data anonymization can be performed based on data tags, which may include steps SB31-SB32 (not shown in the attached diagram), wherein: Step SB31: Based on the data tags corresponding to all target data identified as privacy data and several desensitization methods, select the target desensitization method corresponding to the data tags.

[0055] Step SB32: Based on the target desensitization processing method, desensitize the target data corresponding to the data label.

[0056] Specifically, different de-identification methods are used when the data tags of privacy data are different. The data tags corresponding to the privacy data are determined, and each data tag is matched with several de-identification methods to determine the target de-identification method corresponding to each data tag. For example, when the data tag is a bank card number or a home address, a data replacement method can be used to replace the bank card number or home address. Special characters, random characters, or fixed-value characters can be used for replacement; this application embodiment does not limit the specific methods. When the data tag is a mandatory display tag, such as a name, a simulation method can be used for de-identification. The real name is generated into new data that conforms to the original data encoding and verification rules, and then replaced with data of the same meaning. The replaced name remains meaningful, and the simulation algorithm ensures the business attributes and relationships of the de-identified data, resulting in high data usability. Finally, all the de-identified target data is pushed to the client for display to the user.

[0057] Based on the above embodiments, the existence of privacy data can be determined based on data tags and several preset privacy data tags. If privacy data exists, it can be desensitized. Through desensitization, the security of enterprise data can be improved and the leakage of privacy data can be prevented.

[0058] Furthermore, in the real-time example of this application, after pushing all target data to the client using a preset data security sandbox, steps SC1-SC3 (not shown in the attached figures) are also included, wherein: Step SC1: Obtain the current space information within the preset data security sandbox space after all target data has been pushed. The current space information describes the contents of the current preset data security sandbox space.

[0059] Specifically, once the preset data security sandbox completes its operation, it will automatically generate the content of the preset data security sandbox after the operation, and the electronic device will obtain the generated content.

[0060] Step SC2: Determine whether the current spatial information is different from the preset initial spatial information.

[0061] Specifically, before pushing target data into the preset data security sandbox, the preset initial spatial information remains fixed. This preset initial spatial information describes the contents of the preset data security sandbox before the target data is pushed. The system determines whether there is any additional spatial information compared to the preset initial spatial information. If so, it indicates that the current spatial information differs from the preset initial spatial information, and step SC3 is executed to restore the preset data security sandbox. Otherwise, it indicates that the current spatial information is the same as the preset initial spatial information, and no restoration is required; the sandbox can be used directly.

[0062] Step SC3: If yes, then restore the preset data security sandbox based on the current spatial information.

[0063] Current spatial information includes webpage loading information and process information.

[0064] The implementation method for restoring based on current spatial information may include: steps SC41-SC42 (not shown in the attached figures), wherein: Step SC41: If yes, when the current space information is webpage loading information, close the webpage loaded in the preset data security sandbox.

[0065] Step SC42: When the current space information is process information, clear the processes in the preset data security sandbox.

[0066] Specifically, the webpage can be any webpage corresponding to the user's target data. Webpage loading information can include the webpage loading progress, the time required for loading, and multiple components of the loaded webpage. These components can include text, audio, and tables. Therefore, if the current spatial information is webpage loading information, the webpage loaded in the preset data security sandbox is closed to restore the preset data security sandbox. Process information can be: processes of programs currently running in the preset security data sandbox, system process information, or user process information. Specifically, running program processes represent the activities of programs running in the preset data security sandbox; system process information represents the activities of the system running in the preset data security sandbox; and user process information represents the activities of user applications in the preset data security sandbox. Therefore, if the current spatial information is process information, the processes in the preset data security sandbox are cleared. By clearing the preset data security sandbox, its restoration is achieved, further ensuring the normal use of the preset data security sandbox in the next iteration.

[0067] Based on the above embodiments, the current spatial information of the preset data security sandbox is obtained, and it is determined whether the current spatial information is different from the preset initial spatial information. If they are different, it indicates that the current spatial information is the same as the preset initial spatial information, and there is additional spatial information. Therefore, restoration processing is required to ensure the normal use of the preset data security sandbox and reduce the impact on the user's next use.

[0068] Furthermore, in this embodiment of the application, before pushing all target data to the client using the preset data security sandbar, steps SD1-SD5 (not shown in the accompanying drawings) are also included, wherein: Step SD1: Based on all target data, determine the required space of the preset data security sandbox needed to recommend all target data. The required space represents the size of the preset data security sandbox needed to recommend all target data.

[0069] Specifically, the required space of the preset data security sandbox for pushing all target data can be determined by calculating either the byte method or the block method. The byte calculation method is: required space = word length * number of bits; the block calculation method is: required space = block length * number of bits, thus yielding the required space.

[0070] Step SD2: Obtain the current space amount of the preset data security sandbox.

[0071] Specifically, before the target data is pushed into the preset data security sandbox, there is no information or content within the sandbox; therefore, the current space size is the actual space size of the preset data security sandbox. The current space size of the preset data security sandbox is pre-input into the electronic device.

[0072] Step SD3: Determine whether the required space is less than the current space.

[0073] Step SD4: If yes, then push all target data to the client using the preset data security sandbox.

[0074] Specifically, the required space and the current space are compared. If the required space is less than the current space, it means that the current preset data security sandbox space can push all target data, and step S103 is executed. If the required space is not less than the current space, step S5 is executed, indicating that the current preset data security sandbox space cannot push all target data at the same time. In order to ensure the stable operation of the preset data security sandbox and without affecting the push of all target data, the target data needs to be pushed in sequence according to the push priority of each target data.

[0075] Step SD5: Otherwise, obtain the push priority corresponding to each target data, and push several target data to the client in sequence based on the push priority corresponding to each target data.

[0076] The push priority can be determined based on the number of historical pushes, specifically including steps SD51-SD53 (not shown in the attached diagram), wherein: Step SD51: Obtain the historical push information corresponding to each of the target data, wherein the push information represents the number of historical pushes within a preset time period.

[0077] Step SD52: Determine the priority of each target data based on each target data and its corresponding historical push count.

[0078] Step SD53: Push the target data to the client sequentially based on the push priority of each target data.

[0079] Specifically, this application embodiment does not limit the preset duration; users can set it themselves, such as for a week, a month, or a quarter. After obtaining the user's identity information, the historical push counts for each target data within the preset duration can be retrieved from the data repository corresponding to the user's identity information. It is understood that the more times a target data is pushed within the preset duration, the higher its priority. Therefore, when pushing target data within the preset data security sandbox, high-priority target data is pushed first. This priority push not only reduces the space occupied by the preset data security sandbox but also avoids low user search efficiency due to disordered pushes, thus improving the user experience.

[0080] Based on the above embodiments, the required space of the preset data security sandbox for recommending all target data is determined. By judging the current space and the required space, it can be determined whether the preset data security sandbox can push all target data. If the preset data security sandbox cannot push all target data, the target data is pushed sequentially based on the push priority corresponding to each target data. Recommending target data based on priority can avoid the probability of the preset data security sandbox crashing when pushing all data, and further improve the stability of the preset data security sandbox operation.

[0081] The above embodiments describe a data analysis-based enterprise digital service method from the perspective of process flow. The following embodiments describe a data analysis-based enterprise digital service device from the perspective of virtual modules or virtual units. For details, please refer to the following embodiments.

[0082] This application provides an enterprise digital service device based on data analysis, such as... Figure 3 As shown, this data-driven enterprise digital service device may specifically include: The receiving module 210 is used to receive user request information, wherein the user request information includes at least the target data type; The target data category determination module 220 is used to match the target data type with several preset data categories to determine the target data category corresponding to the target data type. The target category includes the target data type and several other data types. The several preset data categories are obtained by classifying the multiple data types. The multiple data types are determined based on the data labels corresponding to the multiple data types. The multiple data types are obtained from different data sources. The data push module 230 is used to obtain the target data corresponding to each data type in the target data category, and push all the target data to the client using a preset data security sandbox.

[0083] In this embodiment of the application, user request information with a target data type is obtained, and the target data type is matched with several preset data categories. By determining the target data category and determining multiple other data types based on the target data category, a large amount of relevant data can be quickly obtained. Then, the target data corresponding to each data type in the target data category is obtained, which can also quickly obtain a large amount of data to improve search efficiency. Finally, the target data is pushed to the client through a preset data security sandbox, which further enhances the protection of data while improving search efficiency.

[0084] One possible implementation of this application embodiment, the enterprise digital service device based on data analysis, further includes: The user permission determination module is used for: Obtain the user's identity information; Based on the user's identity information and preset data viewing permission information, the data viewing permission information corresponding to the user's identity information is determined. The data viewing permission represents the data range corresponding to each data type in the target data category that the user can view. Accordingly, when the data push module 230 retrieves the target data corresponding to each data type in the target data category, it is used to: Based on data viewing permission information, retrieve the target data corresponding to each data type in the target data category from the database.

[0085] In one possible implementation of this application embodiment, when the data push module 230 performs the operation of pushing all target data to the client using a preset data security sandbox, it is used to: Obtain the data label corresponding to each target data; Based on the data tags corresponding to each of the target data and several preset privacy data tags, it is determined whether privacy data exists; If so, all target data identified as private data will be anonymized, and the anonymized target data will be pushed to the client.

[0086] One possible implementation of this application embodiment, the enterprise digital service device based on data analysis, further includes: The default data security sandbox restoration module is used for: Get the current space information within the preset data security sandbox space after all target data pushes are completed. The current space information describes the contents of the preset data security sandbox space after all target data pushes are completed. Determine whether the current spatial information differs from the preset initial spatial information; If so, the preset data sandbox will be restored based on the current spatial information.

[0087] In one possible implementation of this application embodiment, when the preset data security sandbox restoration module executes "If yes, then restore the preset data security sandbox based on the current spatial information", it is used to: If so, when the current spatial information is webpage loading information, close the webpage loaded in the preset data security sandbox; When the current spatial information is process information, clear the processes in the preset data security sandbox.

[0088] One possible implementation of this application embodiment, the enterprise digital service device based on data analysis, further includes: The target data push priority determination module is used for: Based on all target data, determine the required space of the preset data security sandbox needed to recommend all target data. The required space represents the size of the preset data security sandbox needed to recommend all target data. Get the current space volume of the preset data security sandbox; Determine if the required space is less than the current space. If so, then all target data will be pushed to the client using the preset data security sandbox; Otherwise, the push priority corresponding to each target data is obtained, and several target data are pushed to the client in sequence based on the push priority corresponding to each target data.

[0089] In one possible implementation of this application embodiment, when the data-based enterprise digital service device performs an action other than, obtains the priority corresponding to each target data to be pushed, and pushes all target data to the client based on the priority corresponding to each target data, it is used for: Obtain the historical push information corresponding to each of the target data, where the push information represents the number of historical pushes within a preset time period; The priority of each target data is determined based on each target data and its corresponding historical push count; The target data is pushed to the client in sequence according to the push priority of each target data.

[0090] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the data analysis-based enterprise digital service device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0091] The following describes an electronic device provided in an embodiment of this application. The electronic device described below can be referred to in correspondence with the enterprise digital service method based on data analysis described above.

[0092] This application provides an electronic device, such as... Figure 3 Show, Figure 3 This application provides a schematic diagram of the structure of an electronic device. Figure 3 The illustrated electronic device 300 includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this electronic device 300 does not constitute a limitation on the embodiments of this application.

[0093] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in connection with the embodiments of this application. Processor 301 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0094] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0095] The memory 303 may be a ROM (Read-Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or it may be an EEPROM (Electrically Erasable Programmable Read-Only Memory), a CD-ROM (Compact Disc Read-Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0096] The memory 303 is used to store application code that executes the scheme of the embodiments of this application, and its execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0097] Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 3 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0098] The following describes a computer-readable storage medium provided in an embodiment of this application. This computer-readable storage medium stores a computer program, which, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments. Compared with related technologies, obtaining user request information with a target data type, matching the target data type with several preset data categories, can determine the target data category corresponding to the target data type. By determining the target data category, the data range can be effectively expanded. Then, the target data corresponding to each data type in the target data category is obtained. Therefore, only the target data type is needed to quickly obtain a large amount of relevant data. Finally, the target data is pushed to the client through a preset data security sandbox. Furthermore, while improving search efficiency, the protection of data is also enhanced.

[0099] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0100] The above are only some embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A data analysis-based enterprise digital service method, characterized in that, include: Receive user request information, wherein the user request information includes at least the target data type; The target data type is matched with several preset data categories to determine the target data category corresponding to the target data type. The target data category includes the target data type and several other data types. The several preset data categories are obtained by classifying several data types. The several data types are determined based on the data tags corresponding to each of the several data types. The several data types are obtained from different data sources. Obtain the target data corresponding to each data type in the target data category, and push all target data to the client using a preset data security sandbox, including: Obtain the data label corresponding to each target data; Based on the data tags corresponding to each of the target data and several preset privacy data tags, it is determined whether privacy data exists; If so, all target data identified as private data will be anonymized, and all anonymized target data will be pushed to the client using a preset data security sandbox; The step of pushing all target data to the client using a preset data security sandbox further includes: Get the current space information within the preset data security sandbox space after all target data pushes are completed. The current space information describes the contents of the preset data security sandbox space after all target data pushes are completed. Determine whether the current spatial information differs from the preset initial spatial information; If so, the preset data security sandbox is restored based on the current spatial information, including: If the current spatial information is different from the preset initial spatial information, and the current spatial information is webpage loading information, then close the webpage loaded in the preset data security sandbox to restore the preset data security sandbox; If the current spatial information is different from the preset initial spatial information, and the current spatial information is process information, then the processes in the preset data security sandbox will be cleared in order to restore the preset data security sandbox. Before pushing all target data to the client using a preset data security sandbox, the process also includes: Based on all target data, determine the required space of the preset data security sandbox needed to recommend all target data, where the required space represents the size of the preset data security sandbox needed to recommend all target data. Get the current space volume of the preset data security sandbox; Determine whether the required space amount is less than the current space amount; If so, then all target data will be pushed to the client using the preset data security sandbox; Otherwise, the push priority corresponding to each target data is obtained, and several target data are pushed to the client sequentially based on the push priority corresponding to each target data, including: Obtain the historical push information corresponding to each of the target data, where the push information represents the number of historical pushes within a preset time period; The priority of each target data is determined based on each target data and its corresponding historical push count; The target data is pushed to the client in sequence according to the push priority of each target data.

2. The enterprise-level digital service method based on data analysis according to claim 1, characterized in that, After matching the target data type with several preset data categories to determine the target data category corresponding to the target data type, the method further includes: Obtain the user's identity information; Based on the user's identity information and preset data viewing permission information, the data viewing permission information corresponding to the user's identity information is determined, wherein the data viewing permission represents the data range corresponding to each data type in the target data category that the user can view; Accordingly, obtaining the target data corresponding to each data type in the target data category includes: Based on the data viewing permission information, retrieve the target data corresponding to each data type in the target data category from the database.

3. A data analysis-based enterprise digital service device, characterized in that, include: The receiving module is used to receive user request information, wherein the user request information includes at least the target data type; The target data category determination module is used to match the target data type with several preset data categories to determine the target data category corresponding to the target data type. The target data category includes the target data type and several other data types. The several preset data categories are obtained by classifying the several data types. The several data types are determined based on the data tags corresponding to the several data types. The several data types are obtained from different data sources. The data push module is used to obtain target data corresponding to each of the data types in the target data category, and push all target data to the client using a preset data security sandbox; When the data push module executes the function of pushing all target data to the client using a preset data security sandbox, it is used for: Obtain the data label corresponding to each target data; Based on the data tags corresponding to each of the target data and several preset privacy data tags, it is determined whether privacy data exists; If so, all target data identified as private data will be anonymized, and all anonymized target data will be pushed to the client using a preset data security sandbox; The preset data security sandbox restoration module is used to: obtain the current space information within the preset data security sandbox space after all target data has been pushed; where the current space information describes the contents of the preset data security sandbox space after all target data has been pushed. Determine whether the current spatial information differs from the preset initial spatial information; If so, the preset data security sandbox will be restored based on the current spatial information; When the preset data security sandbox restoration module performs restoration processing on the preset data security sandbox based on the current spatial information, it is used to: If the current spatial information is different from the preset initial spatial information, and the current spatial information is webpage loading information, then close the webpage loaded in the preset data security sandbox to restore the preset data security sandbox; If the current spatial information is different from the preset initial spatial information, and the current spatial information is process information, then the processes in the preset data security sandbox will be cleared in order to restore the preset data security sandbox. The target data push priority determination module is used for: Based on all target data, determine the required space of the preset data security sandbox needed to recommend all target data, where the required space represents the size of the preset data security sandbox needed to recommend all target data. Get the current space volume of the preset data security sandbox; Determine whether the required space amount is less than the current space amount; If so, then all target data will be pushed to the client using the preset data security sandbox; Otherwise, the push priority corresponding to each target data is obtained, and several target data are pushed to the client in sequence based on the push priority corresponding to each target data. When a data-driven enterprise digital service device performs an operation that otherwise obtains the push priority corresponding to each target data point and pushes several target data points to the client sequentially based on their respective push priorities, it is used for: Obtain the historical push information corresponding to each of the target data, where the push information represents the number of historical pushes within a preset time period; The priority of each target data is determined based on each target data and its corresponding historical push count; The target data is pushed to the client in sequence according to the push priority of each target data.

4. An electronic device, characterized in that, include: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, said at least one application being configured to: perform an enterprise digital service method based on data analysis as described in any one of claims 1 to 2.

5. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed in a computer, causes the computer to perform an enterprise-based digital service method based on data analysis as described in any one of claims 1 to 2.

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