Intelligent data storage service method, system, medium and equipment

Abstract

The invention provides an intelligent data storage service method and system, a medium and equipment, and the method comprises the steps: obtaining a target data set, carrying out the desensitization of the obtained target data set, and obtaining a desensitized target data set; constructing a table dictionary, and performing intelligent classified storage on the desensitized target data set according to the constructed table dictionary; and based on the stored desensitized target data, performing data query based on the query statement to obtain result data.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and specifically, to intelligent data storage service methods, systems, media and devices, and more specifically, to intelligent data storage and service methods for multiple users in the life insurance industry. Background Art

[0002] The life insurance industry faces challenges in managing large amounts of customer data, such as data security, storage efficiency, and data management. Traditional data storage methods are difficult to meet the needs of multiple users, large scale, and high efficiency.

[0003] Patent document CN117390169B discloses a method, device, equipment and storage medium for question and answering tabular data. The method includes: obtaining historical tabular data and extracting historical name information therein to fine-tune a pre-built large language model; obtaining table data to be processed and extracting name information to be processed therein, inputting the name information to be processed into the fine-tuned large language model to obtain a ternary relationship prediction result; constructing an undirected graph based on the ternary relationship prediction result to obtain a meta-concept; constructing a knowledge graph based on the table data to be processed, the ternary relationship prediction result and the meta-concept; obtaining real-time feedback questions and pre-processing them to obtain pre-processing information, matching and searching the constructed knowledge graph based on the pre-processing information, and obtaining the answer to the question fed back by the preset question and answer large language model according to the matching result.

[0004] The present invention aims to utilize artificial intelligence technology to propose an intelligent data storage and service method to solve the bottleneck problem in data management in the life insurance industry. Summary of the invention

[0005] The main purpose of the present invention is to solve the technical problem that the data storage method in the prior art is difficult to meet the needs of multiple users, large scale and high efficiency.

[0006] A first aspect of the present invention provides an intelligent data storage service method, comprising:

[0007] Acquire a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set;

[0008] Build a table dictionary, and intelligently classify and store the desensitized target data set according to the built table dictionary;

[0009] Based on the stored anesthetized target data, data query is performed based on query statements to obtain result data.

[0010] Optionally, in a first implementation of the first aspect of the present invention, the acquiring the target data set and performing desensitization processing on the acquired target data set to obtain desensitized target data includes:

[0011] Acquire target data, and classify the acquired target data into sensitive data and non-sensitive data according to preset standards;

[0012] After generating a unique identifier for sensitive data, perform data cleaning to obtain the cleaned sensitive data;

[0013] Encrypting the sensitive data after data cleaning to obtain encrypted sensitive data;

[0014] Based on the encrypted sensitive data and non-sensitive data, a desensitized target dataset is constructed.

[0015] Optionally, in a second implementation of the first aspect of the present invention, constructing a table dictionary, and intelligently classifying the desensitized target data set according to the constructed table dictionary, includes:

[0016] Build a table dictionary based on the defined data topics and the sub-topic tables corresponding to each data topic;

[0017] Preprocess the desensitized target data set so that the field format of the preprocessed target data is consistent with the fields defined in the table dictionary;

[0018] Traverse the masked target data set, and match and map each field in the masked target data set according to the fields defined in the table dictionary;

[0019] According to the mapping relationship, the anonymized target data set is classified and stored in the corresponding topic table and sub-topic table.

[0020] Optionally, in a third implementation of the first aspect of the present invention, the step of performing a data query based on a query statement based on the stored desensitized target data to obtain result data includes:

[0021] The large language model uses natural language processing technology to analyze free input sentences and obtain the corresponding topics, field names, and query conditions;

[0022] When the acquired subject, field name, and query condition are all in the table dictionary, the corresponding result data is acquired based on the desensitized target data set stored in the table dictionary.

[0023] Optionally, in a fourth implementation of the first aspect of the present invention, the step of performing a data query based on a query statement based on the stored desensitized target data to obtain result data includes:

[0024] The large language model uses natural language processing technology to analyze the structured input and obtain the corresponding topics, field names, and query conditions.

[0025] When the acquired subject, field name, and query condition are all in the table dictionary, the corresponding result data is acquired based on the desensitized target data set stored in the table dictionary;

[0026] The structured input includes: input in a predetermined format, including: subject, field name, and query condition.

[0027] Optionally, in a fifth implementation of the first aspect of the present invention, the method further includes:

[0028] Get the report template, identify the placeholders in the report template, and map the placeholders in the report template to the fields in the target data set stored in the table dictionary by using column binding to achieve data filling.

[0029] Optionally, in a sixth implementation of the first aspect of the present invention, the method further includes:

[0030] The fields and analysis dimensions selected by the user are obtained, and an analysis statement is generated based on the obtained fields and analysis dimensions selected by the user using a large language model. An analysis report is generated based on the analysis statement according to the target data set stored in the table dictionary.

[0031] A second aspect of the present invention provides an intelligent data storage service system, comprising:

[0032] A data acquisition module is used to acquire a target data set, perform desensitization processing on the acquired target data set, and obtain a desensitized target data set;

[0033] The data classification storage module is used to construct a table dictionary. The desensitized target data set is intelligently classified and stored according to the constructed table dictionary.

[0034] The data query module is used to perform data query based on the stored anonymized target data and query statements to obtain result data.

[0035] Optionally, in a first implementation of the second aspect of the present invention, the data acquisition module includes:

[0036] A data division submodule is used to obtain target data and divide the obtained target data into sensitive data and non-sensitive data according to preset standards;

[0037] The data cleaning submodule is used to generate a unique identifier for sensitive data and then perform data cleaning to obtain the sensitive data after data cleaning;

[0038] The encryption processing submodule is used to encrypt the sensitive data after data cleaning to obtain encrypted sensitive data;

[0039] The dataset building module is used to build a desensitized target dataset based on the encrypted sensitive data and non-sensitive data.

[0040] Optionally, in a second implementation of the second aspect of the present invention, the data classification storage module includes:

[0041] A table dictionary building submodule is used to build a table dictionary based on defined data themes and sub-theme tables corresponding to each data theme;

[0042] The preprocessing submodule is used to preprocess the desensitized target data set so that the field format of the preprocessed target data is consistent with the fields defined in the table dictionary;

[0043] The mapping submodule is used to traverse the masked target data set and match and map each field in the masked target data set according to the fields defined in the table dictionary;

[0044] The storage submodule is used to classify and store the desensitized target data set into corresponding topic tables and sub-topic tables according to the mapping relationship.

[0045] Optionally, in a third implementation of the second aspect of the present invention, the data query module includes:

[0046] The sentence analysis submodule is used by the large language model to analyze the free input through natural language processing technology to obtain the corresponding topic, field name and query condition;

[0047] The result data acquisition submodule is used to obtain the corresponding result data based on the desensitized target data set stored in the table dictionary when the acquired subject, field name and query condition are all in the table dictionary.

[0048] Optionally, in a fourth implementation of the second aspect of the present invention, the data query module includes:

[0049] The sentence analysis submodule is used by the large language model to analyze the structured input through natural language processing technology to obtain the corresponding topics, field names and query conditions;

[0050] The result data acquisition submodule is used to acquire the corresponding result data based on the desensitized target data set stored in the table dictionary when the acquired subject, field name and query condition are all in the table dictionary;

[0051] The structured input includes: input in a predetermined format, including: subject, field name, and query condition.

[0052] Optionally, in a fifth implementation of the second aspect of the present invention, the system further includes:

[0053] The report generation module is used to obtain the report template, identify the placeholders in the report template, and map the placeholders in the report template with the fields in the target data set stored in the table dictionary using column binding to achieve data filling.

[0054] Optionally, in a sixth implementation of the second aspect of the present invention, the system further includes:

[0055] The report generation module is used to obtain the fields and analysis dimensions selected by the user, generate analysis statements based on the obtained fields and analysis dimensions selected by the user using the large language model, and generate an analysis report based on the analysis statements according to the target data set stored in the table dictionary.

[0056] A third aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-mentioned intelligent data storage service method.

[0057] A fourth aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the above-described intelligent data storage service method when executed by the processor.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. The present invention establishes a data warehouse by using data classification standards, and can intelligently perform storage management according to data characteristics, thereby improving storage efficiency and utilization;

[0060] 2. The present invention ensures the security and integrity of data and prevents data leakage and loss through measures such as data backup and encryption;

[0061] 3. The present invention reads table fields according to artificial intelligence and can directly generate corresponding SQL scripts, effectively alleviating the pressure of data extraction work. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0063] Figure 1 A first flow chart of the intelligent data storage service method provided by an embodiment of the present invention.

[0064] Figure 2 A second flow chart of the intelligent data storage service method provided by an embodiment of the present invention.

[0065] Figure 3A third flow chart of the intelligent data storage service method provided by an embodiment of the present invention.

[0066] Figure 4 A fourth flow chart of the intelligent data storage service method provided by an embodiment of the present invention.

[0067] Figure 5 A fifth flow chart of the intelligent data storage service method provided by an embodiment of the present invention.

[0068] Figure 6 A schematic diagram of the structure of an intelligent data storage service system provided in an embodiment of the present invention.

[0069] Figure 7 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0071] The embodiments of the present invention provide an intelligent data storage service method, system, medium and device, which acquire a target data set, perform desensitization processing on the acquired target data set to obtain a desensitized target data set; construct a table dictionary, and intelligently classify and store the desensitized target data set according to the constructed table dictionary; perform data query based on a query statement based on the stored desensitized target data to obtain result data; and generate an analysis report based on the stored desensitized target data according to preset requirements.

[0072] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0073] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1The first embodiment of the intelligent data storage service method in the embodiment of the present invention includes:

[0074] 101. Acquire a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set;

[0075] In this embodiment, target data is obtained, and the obtained target data is divided into sensitive data and non-sensitive data according to a preset standard;

[0076] After generating a unique identifier for sensitive data, perform data cleaning to obtain the cleaned sensitive data;

[0077] Encrypting the sensitive data after data cleaning to obtain encrypted sensitive data;

[0078] Based on the encrypted sensitive data and non-sensitive data, a desensitized target dataset is constructed.

[0079] 102. Build a table dictionary, and intelligently classify and store the desensitized target data set according to the built table dictionary;

[0080] In this embodiment, a table dictionary is constructed based on the defined data topics and the sub-topic table corresponding to each data topic;

[0081] Preprocess the desensitized target data set so that the field format of the preprocessed target data is consistent with the fields defined in the table dictionary;

[0082] Traverse the masked target data set, and match and map each field in the masked target data set according to the fields defined in the table dictionary;

[0083] According to the mapping relationship, the anonymized target data set is classified and stored in the corresponding topic table and sub-topic table.

[0084] 103. Based on the stored anonymized target data, data query is performed based on the query statement to obtain result data.

[0085] In this embodiment, the large language model uses natural language processing technology to analyze the free input and obtain the corresponding subject, field name and query condition;

[0086] When the acquired subject, field name, and query condition are all in the table dictionary, the corresponding result data is acquired based on the desensitized target data set stored in the table dictionary.

[0087] See also Figure 2 Another embodiment of the intelligent data storage service method in the embodiment of the present invention includes:

[0088] 201. Acquire a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set;

[0089] 202. Construct a table dictionary, and intelligently classify and store the desensitized target data set according to the constructed table dictionary;

[0090] 203. Based on the stored anonymized target data, data query is performed based on the query statement to obtain result data.

[0091] In this embodiment, the large language model uses natural language processing technology to perform sentence analysis on the structured input to obtain the corresponding subject, field name and query condition;

[0092] When the acquired subject, field name, and query condition are all in the table dictionary, the corresponding result data is acquired based on the desensitized target data set stored in the table dictionary;

[0093] The structured input includes: input in a predetermined format, including: subject, field name, and query condition.

[0094] See also Figure 3 Another embodiment of the intelligent data storage service method in the embodiment of the present invention includes:

[0095] 301. Acquire a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set;

[0096] 302. Construct a table dictionary, and intelligently classify and store the desensitized target data set according to the constructed table dictionary;

[0097] 303. Based on the stored anonymized target data, data query is performed based on the query statement to obtain result data.

[0098] 304. Obtain a report template, identify a placeholder in the report template, and map the placeholder in the report template to a field in a target data set stored in a table dictionary by using a column binding method to implement data filling and obtain an analysis report.

[0099] See also Figure 4 Another embodiment of the intelligent data storage service method in the embodiment of the present invention includes:

[0100] 401. Obtain a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set;

[0101] 402. Build a table dictionary, and intelligently classify and store the desensitized target data set according to the built table dictionary;

[0102] 403. Based on the stored anonymized target data, data query is performed based on the query statement to obtain result data.

[0103] 404. Obtain the fields and analysis dimensions selected by the user, generate analysis statements based on the obtained fields and analysis dimensions selected by the user using the large language model, and generate an analysis report based on the analysis statements according to the target data set stored in the table dictionary.

[0104] See also Figure 5 Another embodiment of the intelligent data storage service method in the embodiment of the present invention includes:

[0105] 501. Sensitive data processing;

[0106] In this embodiment, the life insurance industry has already issued a specific data classification standard, based on which data is divided into two categories: sensitive and non-sensitive. For sensitive information data sets, data cleaning is performed after a unique identifier is generated, and a set of desensitized non-sensitive data sets is constructed through encryption methods such as MD5. Sensitive or non-sensitive data sets can be read according to the requirements.

[0107] 502. Intelligent classification of data sets;

[0108] In this embodiment, according to the characteristics of the life insurance industry, the data is divided into multiple topics, and topic tables and sub-topic tables are constructed respectively, such as policy, claim, preservation, contract, actual collection, etc., and detailed table dictionaries are constructed for these topic tables. In the table dictionary, detailed descriptions of fields and fields that can be used as query conditions are further defined, which are divided into modes such as drop-down boxes, text boxes, check boxes, and time periods.

[0109] 503. Intelligently generate query statements;

[0110] In this embodiment, the query page refers to the current artificial intelligence AI method to identify user needs in the form of questions and answers. Two methods, free question and answer and rich text question and answer, can be provided.

[0111] In free questions and answers, if the topic name, field name, and query conditions mentioned are all in the built knowledge base, then based on the built table dictionary, PHP automatic page generation technology is used to automatically generate the result data required by the user.

[0112] Rich text Q&A establishes a fixed set of data extraction standards. The order of Q&A is: subject, field name, query condition, collection column, and sorting. After the Q&A is completed, the query statements and pages can be automatically organized to generate result data.

[0113] 504. Automatically generate analysis reports;

[0114] In this embodiment, the analysis report provides two solutions, one is that the user imports the report template, and the second is the intelligent analysis report.

[0115] When users import templates, they need to organize the text and pictures in the analysis report in advance and then import them into the system. The required data in the report template can be mapped from the query result set using column binding and other methods to automatically fill in data.

[0116] Smart analysis report: users select the fields to be used for the report in the foreground and describe the required report dimensions, such as synchronization, growth rate, etc. The corresponding analysis statements can be generated according to the detailed description of the fields in the table dictionary, and finally the overall analysis report is formed.

[0117] The above describes the intelligent data storage service method in the embodiment of the present invention. The following describes the intelligent data storage service system in the embodiment of the present invention. Figure 6 In one embodiment of the present invention, an intelligent data storage service system includes:

[0118] The data acquisition module 601 is used to acquire a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set;

[0119] The data classification storage module 602 is used to construct a table dictionary, and the desensitized target data set is intelligently classified and stored according to the constructed table dictionary;

[0120] The data query module 603 is used to perform data query based on the stored anesthetized target data and query statements to obtain result data.

[0121] In this embodiment, the large language model uses natural language processing technology to perform sentence analysis on free input to obtain corresponding topics, field names and query conditions; when the obtained topics, field names and query conditions are all in the table dictionary, the corresponding result data is obtained based on the desensitized target data set stored in the table dictionary; or, the large language model uses natural language processing technology to perform sentence analysis on structured input to obtain corresponding topics, field names and query conditions; when the obtained topics, field names and query conditions are all in the table dictionary, the corresponding result data is obtained based on the desensitized target data set stored in the table dictionary; wherein the structured input includes: input in a predetermined format, including: topic, field name, query condition.

[0122] A report generation module 604 is used to generate an analysis report according to preset requirements based on the stored desensitized target data;

[0123] In this embodiment, a report template is obtained, and placeholders in the report template are identified. The placeholders in the report template are mapped to the fields in the target data set stored in the table dictionary by using a column binding method to implement data filling and generate an analysis report; or the fields and analysis dimensions selected by the user are obtained, and an analysis statement is generated based on the obtained fields and analysis dimensions selected by the user using a large language model, and an analysis report is generated based on the analysis statement and the target data set stored in the table dictionary.

[0124] above Figure 6 The intelligent data storage service system in the embodiment of the present invention is described in detail from the perspective of modular functional entities, and the electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0125] Figure 7 7 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 700 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing unit, CPU) 710 (for example, one or more processors) and a memory 720, and one or more storage media 730 (for example, one or more mass storage devices) storing application programs 733 or data 732. Among them, the memory 720 and the storage medium 730 can be temporary storage or permanent storage. The program stored in the storage medium 730 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the electronic device 700. Furthermore, the processor 710 may be configured to communicate with the storage medium 730 to execute a series of instruction operations in the storage medium 730 on the electronic device 700.

[0126] The electronic device 700 may also include one or more power supplies 740, one or more wired or wireless network interfaces 750, one or more input and output interfaces 750, and / or one or more operating systems 731, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 7 The structure of the electronic device shown does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0127] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the intelligent data storage service method.

[0128] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0129] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0130] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent data storage service method, characterized in that: include: Acquire a target data set, and perform desensitization processing on the acquired target data set to obtain a desensitized target data set; Build a table dictionary, and intelligently classify and store the desensitized target data set according to the built table dictionary; Based on the stored anesthetized target data, data query is performed based on the query statement to obtain the result data.

2. The intelligent data storage service method according to claim 1, characterized in that: The step of acquiring a target data set and performing desensitization processing on the acquired target data set to obtain desensitized target data includes: Acquire target data, and classify the acquired target data into sensitive data and non-sensitive data according to preset standards; After generating a unique identifier for sensitive data, perform data cleaning to obtain the cleaned sensitive data; Encrypting the sensitive data after data cleaning to obtain encrypted sensitive data; Based on the encrypted sensitive data and non-sensitive data, a desensitized target dataset is constructed.

3. The intelligent data storage service method according to claim 1, characterized in that: The table dictionary is constructed, and the desensitized target data set is intelligently classified according to the constructed table dictionary, including: Build a table dictionary based on the defined data topics and the sub-topic tables corresponding to each data topic; Preprocess the desensitized target data set so that the field format of the preprocessed target data is consistent with the fields defined in the table dictionary; Traverse the masked target data set, and match and map each field in the masked target data set according to the fields defined in the table dictionary; According to the mapping relationship, the anonymized target data set is classified and stored in the corresponding topic table and sub-topic table.

4. The intelligent data storage service method according to claim 1, characterized in that: The stored desensitized target data is queried based on a query statement to obtain result data, including: The large language model uses natural language processing technology to analyze free input sentences and obtain the corresponding topics, field names, and query conditions; When the acquired subject, field name, and query condition are all in the table dictionary, the corresponding result data is acquired based on the desensitized target data set stored in the table dictionary.

5. The intelligent data storage service method according to claim 1, characterized in that: The stored desensitized target data is queried based on a query statement to obtain result data, including: The large language model uses natural language processing technology to analyze the structured input and obtain the corresponding topics, field names, and query conditions. When the acquired subject, field name, and query condition are all in the table dictionary, the corresponding result data is acquired based on the desensitized target data set stored in the table dictionary; The structured input includes: input in a predetermined format, including: subject, field name, and query condition.

6. The intelligent data storage service method according to claim 1, characterized in that: The method further comprises: Get the report template, identify the placeholders in the report template, and map the placeholders in the report template to the fields in the target data set stored in the table dictionary by using column binding to achieve data filling.

7. The intelligent data storage service method according to claim 1, characterized in that: The method further comprises: The fields and analysis dimensions selected by the user are obtained, and an analysis statement is generated based on the obtained fields and analysis dimensions selected by the user using a large language model. An analysis report is generated based on the analysis statement according to the target data set stored in the table dictionary.

8. An intelligent data storage service system, characterized in that: include: A data acquisition module is used to acquire a target data set, perform desensitization processing on the acquired target data set, and obtain a desensitized target data set; The data classification storage module is used to construct a table dictionary. The desensitized target data set is intelligently classified and stored according to the constructed table dictionary. The data query module is used to perform data query based on the stored anonymized target data and query statements to obtain result data.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the intelligent data storage service method described in any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the intelligent data storage service method described in any one of claims 1 to 7 are implemented.

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