Cross-platform data intelligent sharing and automatic pushing method based on data-in-platform
By using a cross-platform data intelligence sharing and automated push method based on a data middle platform, the problems of data silos, poor push timeliness, and untraceable data in the financial industry have been solved, realizing timely and accurate data push and full-link traceability, thereby improving the efficiency and effectiveness of digital marketing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA CONSTRUCTION BANK
- Filing Date
- 2025-12-15
- Publication Date
- 2026-04-28
AI Technical Summary
The financial industry suffers from data silos, with insufficient timeliness and flexibility in data delivery, failing to meet the needs of precise marketing decisions. Furthermore, the data is untraceable, posing a risk of loss and failing to meet security and traceability requirements.
By using a cross-platform data intelligent sharing and automated push method based on a data middle platform, we can achieve standardized integration of customer data in multiple environments and systems, establish a full-link data traceability and backup system, improve the timeliness and flexibility of data push by adopting an automated push mechanism, and build a dual backup mechanism to support flexible configuration of multiple frequencies and cycles.
It enables timely and accurate data delivery, meets the timeliness requirements of different marketing scenarios, reduces the risk of data loss, supports data extraction and standardized processing in multiple environments, improves the timeliness and flexibility of data delivery, ensures data accuracy and security, provides data support for precision marketing, and significantly improves the efficiency of digital marketing decision-making.
Smart Images
Figure CN121935429A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computer technology, specifically to a cross-platform data intelligent sharing and automated push method based on a data middleware platform, which is particularly suitable for the integration, push and analysis of customer data in digital marketing scenarios in the financial industry. Background Technology
[0002] With the deepening of digital transformation in the financial industry, banks and other financial institutions have an increasingly urgent need for digital marketing, requiring the establishment of efficient digital marketing platforms to improve their digital operating systems. Currently, internal bank data sources are scattered and difficult to integrate. While various business systems have accumulated a large amount of data mining results, serious "data silos" still exist between systems. The lack of standardized, automated data push channels makes it difficult to quickly deploy and verify data mining results, and the combined power of data is not fully utilized. Existing data push mechanisms are inefficient and lack flexibility, relying heavily on manual triggering of push operations. They cannot flexibly set the push frequency and effective time according to the actual needs of marketing tasks, resulting in insufficient timeliness of pushed data and difficulty in supporting the formulation of precise marketing decisions. Furthermore, pushed customer data lacks a systematic historical retention and backup mechanism, leaving no basis for subsequent data verification, problem tracing, and post-mortem analysis, posing a risk of data loss and failing to meet the stringent requirements of the financial industry for data security and traceability. Therefore, existing technical solutions cannot effectively solve the three problems of data silos, poor push timeliness, and data untraceability, exhibiting significant shortcomings. Summary of the Invention
[0003] The purpose of this invention is to overcome the above-mentioned defects in the prior art and provide a cross-platform data intelligent sharing and automated push method based on a data middle platform. This method enables standardized integration of customer data in multiple environments and systems, improves the timeliness and flexibility of data push through an automated push mechanism, and establishes a full-link data traceability and backup system to solve the pain points of data application in digital marketing in the financial industry.
[0004] To achieve the above objectives, the present invention is implemented through the following technical solution:
[0005] This invention discloses a cross-platform intelligent data sharing and automated push method based on a data middle platform, which includes the following steps:
[0006] Step S1: Apply for a model number: The banking business department submits the customer group name, customer group description, affiliated institution, and model validity period information to the model number application module. After the system initiates the application and it is approved, a unique model number is automatically generated.
[0007] Step S2: Extract customer group information and insert it into the automatic batch processing module: The bank's financial technology department extracts target customer group data containing customer IDs. The automatic batch processing module cleans the data and removes invalid fields. The data is then concatenated into a single field in the format of "data date|@|model number|@|customer number" and inserted into the model push information table. The data of the day in the model push information table is then synchronized to the local push table. At the same time, the synchronization operation is performed according to the customized multi-frequency push frequency.
[0008] Step S3 involves cross-platform push based on configured push task information and customer content information: Cross-platform data push is executed. The banking business department configures the execution information task for the customer group execution information module, including the institution number, model number, upload node, target directory, upload cycle, file type, and effective deadline. The system updates the activation status according to the application status and effective deadline. The automatic task module periodically scans for tasks that meet the conditions, encapsulates the corresponding data in the local push table into a specified format file, and performs content verification. After verification, the file is pushed to the specified server target path, while a backup is stored locally. The file transfer status, the last upload date, and the activation status are updated according to the push results.
[0009] Step S4: The marketing platform extracts and loads file data and associates it with specified tags: The marketing platform's tag association module retrieves the pushed files and extracts and loads the data, associates the data with multi-dimensional tags, and conducts secondary customer group analysis.
[0010] Step S5: Historical Data Backup and Retention: Back up historical data. The historical data backup module stores push files, task information, and data details, and supports querying data by model number and push date.
[0011] Preferably, in step S2, when the automatic batch processing module inserts the processed standardized data into the model push information table, it can simultaneously insert data with different model numbers; the automatic batch processing module supports push frequencies of every 3 hours, every 6 hours, every 9 hours, and every 12 hours.
[0012] Preferably, in step S3, the execution information task configured by the banking business department also includes the application status, the model number is automatically generated by the customer group execution information module and is unique, the upload node is a fixed value G1SZ, the target directory is / home / file / data / system date / , the file type includes single file type and multiple file type, and the application status includes approval passed and approval failed; if the application status is approval passed and the system time is ≤ the valid deadline, the activation status is automatically changed to activation; if the application status is approval failed, the push task is not executed.
[0013] Preferably, in step S3, the tasks scanned by the automatic task module at regular intervals must simultaneously meet the following conditions: the application status is approved, the status is enabled, the effective deadline is greater than or equal to the system date, and the corresponding model number exists in the local push table on that day.
[0014] The file is packaged in .dat format and named LIST_model_number.dat. File content validation includes: checking whether the field "data date|@|model_number|@|customer_number" has a null value. If it does, the corresponding entire row of data is deleted. At the same time, it checks whether the custom separator |@| exists and is unique. When the file is pushed, data containing the organization number, model number, file name, and file transfer status is inserted into the customer content information module. The file transfer status is initially empty.
[0015] Preferably, in step S3, for tasks with a single upload cycle, the enabled status automatically changes to disabled after the file is successfully pushed; for tasks with a daily upload cycle, the enabled status automatically changes to disabled after the system date exceeds the valid deadline; when the file is successfully pushed, the file transfer status in the customer group content information module changes to successful, and the most recent upload date in the customer group execution information module changes to the system date of this push; when the file push fails, the file transfer status in the customer group content information module changes to failed, and the data processing, task configuration, and file verification steps need to be checked, corrected, and the push process re-executed.
[0016] Preferably, the historical data stored in step S5 includes .dat format files, task information, and data details, supporting data verification, problem tracing, and retrospective analysis.
[0017] The present invention discloses a cross-platform data intelligent sharing and automated push system based on a data middle platform, characterized in that it includes a model number application module, an automatic batch processing module, a customer group execution information module, a customer group content information module, an automatic task module, a marketing platform tag association module, and a historical data backup module.
[0018] The model number application module is used to receive customer group name, customer group description, affiliated institution, and model validity period information submitted by the banking business department, initiate an application, and automatically generate a unique model number after approval.
[0019] The automatic batch processing module and the model number application module communicate with each other. The module is used to receive target customer data extracted by the bank's financial technology department, clean the data and remove invalid fields, and insert the standardized data into the model push information table after splicing it in a specified format. At the same time, the data of the day in the model push information table is synchronized to the local push table, and the module supports customized multiple push frequencies.
[0020] The customer group execution information module communicates with the automatic batch processing module and is used to store the execution information tasks configured by the banking business department. The execution information tasks include the institution number, model number, upload node, target directory, upload cycle, file type, activation status, effective deadline, most recent upload date, and application status. At the same time, the activation status is automatically updated according to the application status and effective deadline.
[0021] The customer group content information module and the customer group execution information module communicate with each other to store the organization number, model number, file name, and file transmission status information, and update the file transmission status according to the file push result;
[0022] The automatic task module communicates with the automatic batch processing module, the customer group execution information module, and the customer group content information module respectively. It is used to periodically scan the tasks that meet the conditions in the customer group execution information module, encapsulate the corresponding data in the local push table into a specified format file and perform content verification. After the verification is passed, the file is pushed to the specified server target path, and the local backup process is triggered at the same time.
[0023] The marketing platform tag association module communicates with the automatic task module to retrieve pushed files and extract loaded data, and associates the data with multi-dimensional tags for business departments to conduct secondary customer group analysis and precise marketing decisions.
[0024] The historical data backup module communicates with the automatic task module, customer group execution information module, and customer group content information module to store push files, task information, and data details. It supports data querying by model number and push date, enabling full-link data traceability and retrospective analysis.
[0025] Preferably, the upload node in the customer group execution information module is a fixed value G1SZ, the target directory is / home / file / data / system date / , the upload cycle includes daily and single upload, and the file type includes single file type and multiple file type.
[0026] Preferably, the file name generated by the automatic task module when performing the file encapsulation operation is LIST_model number.dat.
[0027] Preferably, the marketing platform tag association module uses multi-dimensional tags including consumer preference tags, product ownership tags, and customer activity tags.
[0028] Beneficial effects: It supports data breakpoint linking, ensuring timely and accurate data delivery to meet the timeliness needs of different marketing scenarios; by retaining push files locally and backing up push history, it achieves full-link data traceability and reduces the risk of data loss; it supports multi-environment data extraction and standardized processing, enabling parallel processing of multi-model numbered data and fully leveraging the synergy of data; it achieves automated push, supporting flexible configuration of multiple frequencies and cycles without manual intervention, significantly improving the timeliness of data push; it constructs a dual backup and verification mechanism to achieve full-link data traceability, ensuring data accuracy and security and resolving the risk of data loss; and it provides support for precision marketing by associating data with multi-dimensional tags, significantly improving the efficiency and effectiveness of digital marketing decision-making in the financial industry. Attached Figure Description
[0029] Figure 1 This is an overall flowchart of the method of the present invention.
[0030] Figure 2 This is a preliminary data processing diagram of the present invention.
[0031] Figure 3 This is a flowchart of the platform data push process of the present invention.
[0032] Figure 4 This is a schematic diagram illustrating the association between documents and tags and the use of model tags in this invention.
[0033] Figure 5 This is a schematic diagram illustrating the historical data backup and retention of this invention. Detailed Implementation
[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0035] Technical solution / principle:
[0036] This invention provides a cross-platform intelligent data sharing and automated push method based on a data middle platform, specifically including the following steps:
[0037] The banking department, based on the target customer group needs of digital marketing, submits information such as customer group name, customer group description, affiliated institution, and model validity period to the model number application module. The model number application module initiates the application process. After approval, a unique model number is automatically generated, which serves as the unique identifier for subsequent customer group data pushes. The banking fintech department extracts target customer group data containing customer numbers. The data extraction environment covers both ACA and NGB environments, supporting multi-environment data fusion and mining. After receiving the target customer group data, the automatic batch processing module cleans the data and removes invalid fields. The processed data is then concatenated into a single field in the format "Data Date|@|Model Number|@|Customer Number" to form standardized data. The automatic batch processing module inserts standardized data into the model push information table, and supports inserting multiple sets of customer group data corresponding to different model numbers simultaneously. Subsequently, the automatic batch processing module synchronizes the target customer group data for the day from the model push information table to the local push table, and can perform synchronization operations according to customized multi-frequency push operations, including every 3 hours, every 6 hours, every 9 hours, and every 12 hours. Based on the configured push task information and customer group content information, cross-platform pushes are performed. Banking departments configure execution information tasks to the customer group execution information module. The task includes the institution number, model number, upload node, target directory, upload cycle, file type, effective deadline, and application status. The model number is automatically generated by the customer group execution information module and is unique; the upload node is a fixed value G1SZ; the target directory is / home / file / data / system date / ; the file type includes single file and multiple file types; and the application status includes approval approved and approval rejected. The customer group execution information module updates the task activation status based on the application status and the effective deadline: if the application status is approved and the system time is less than or equal to the effective deadline, the activation status is automatically changed to activated; if the application status is rejected, the push task is not executed. The automatic task module periodically scans the tasks in the customer group execution information module, filtering only those tasks that simultaneously meet the conditions of "application status approved, activation status activated, effective deadline greater than or equal to the system date, and corresponding model number data existing in the local push table for the current day". The automatic task module encapsulates the local push table data corresponding to the filtered tasks into a .dat format file named LIST_model_number.dat. During the file encapsulation process, content validation is performed, including two aspects: first, checking whether the "data date|@|model number|@|customer number" field has a null value; if it does, the corresponding entire row of data is deleted; second, checking whether the custom separator |@| exists and is unique. After the validation passes, the automatic task module inserts data containing the organization number, model number, file name, and file transfer status into the customer group content information module. The file transfer status is initially empty.The automated task module pushes verified .dat format files to the target path on the bank's designated server, while simultaneously storing a backup file on the local server at a designated path. Upon successful push, the task status is updated: In the customer content information module, the file transfer status changes to "successful," and the most recent upload date in the customer execution information module changes to the system date of this push. For tasks with a single upload cycle, the enabled status automatically changes to "disabled." For tasks with a daily upload cycle, the enabled status automatically changes to "disabled" after the system date exceeds the valid deadline. In the event of a push failure, the file transfer status in the customer content information module changes to "failed." Staff must check data processing, task configuration, and file verification, correct any errors, and re-execute the push process. The marketing platform extracts and loads file data and associates it with designated tags. The marketing platform's tag association module automatically retrieves file information from the target push directory daily, extracts and loads customer data from the files, and associates the data with preset multi-dimensional tags, including consumption preference tags, product ownership tags, and customer activity tags. The associated data can be used by business departments for secondary customer analysis, providing data support for precise marketing decisions. The historical data backup and retention module collects all data from completed pushes, including .dat format files, execution information task data, customer group data details, etc., and stores this data in the push history database for backup. Backup data supports querying by model number, push date, and other dimensions, meeting the needs of subsequent data verification, problem tracing, and post-mortem analysis. This invention also provides a system for implementing the above method, including a model number application module, an automatic batch processing module, a customer group execution information module, a customer group content information module, an automatic task module, a marketing platform tag association module, and a historical data backup module. These modules are interconnected and collaboratively complete cross-platform intelligent data sharing and automated push operations.
[0038] like Figure 1 The method for cross-platform intelligent data sharing and automated push based on a data middle platform, as shown, includes the following steps:
[0039] Step S1: Apply for a model number;
[0040] Based on the needs of the target customer group, the banking business department submits the customer group name, customer group description, affiliated institution, and model validity period information to the model number application module. After the system initiates the application and it is approved, a unique model number is automatically generated.
[0041] Step S2: Extract customer group information and insert it into the automatic batch processing module;
[0042] The bank's fintech department extracts target customer data containing customer IDs. The data extraction environment includes both ACA and NGB environments, supporting multi-environment and multi-channel integrated data mining and sharing.
[0043] Step S2.1 Extract target customer data according to marketing needs. The automatic batch processing module cleans the data and removes invalid fields. The specific processing steps are as follows: Figure 2 As shown, the data is concatenated into a single field in the format "Data Date|@|Model Number|@|Customer Number". The Data Date is the date the data was inserted, and the Model Number is the number requested in step S1. The processed standardized data is then inserted into the model push information table, supporting the simultaneous insertion of data with different model numbers. (Specifically:) Figure 2 This demonstrates the initial processing of target customer group data: Input data includes two categories: detailed consumption data (including bank card number, consumption time, and consumption amount) and user app registration information (including mobile phone number, registration time, and browsing duration). Through the "data processing (cleaning and removal) by associating user information" step, the two types of data are integrated and invalid information is cleaned. Finally, the data is converted to a specified format: "Data Date|@|Model Number|@|Customer Number," completing the data standardization process.
[0044] Step S2.2 The automatic batch processing module synchronizes the target customer group data of the day in the model push information table to the local push table, and supports customized push frequencies of every 3 hours, every 6 hours, every 9 hours, and every 12 hours.
[0045] Step S3: Cross-platform data push;
[0046] The specific process is as follows: Figure 3 As shown, in this invention, the automatic task module pushes files to the marketing platform periodically via NFT-SA. Specifically: Figure 3 The specific execution logic of cross-platform data push is demonstrated: it includes "Customer Group Execution Information Module - Task Information List" and "Customer Group Content Information Module - Content Information List", which record task parameters such as organization number, model number, upload node, target directory, and file status; the task automatically scans for model numbers that meet the conditions (such as model number 12341), generates the corresponding .dat format file and pushes it to the specified directory; after the push is completed, the file transfer status (success / failure) and the task upload date are updated, and the task activation status is adjusted (such as deactivation after a single task push).
[0047] Step S3.1 The banking business department configures the execution information task to the customer group execution information module. The task includes the institution number, model number, upload node, target directory, upload cycle, file type, activation status, effective deadline, most recent upload date, and application status. The model number is automatically generated by the customer group execution information module and is unique. The upload node is a fixed value G1SZ. The target directory is / home / file / data / system date / . The upload cycle is divided into daily and once. The file type is divided into single file type and multiple file type. The application status is divided into approval and rejection. If the application status is approval and the system time is less than or equal to the effective deadline, the activation status is automatically changed to activation. If the application status is rejection, the push task is not executed.
[0048] Step S3.2 The automatic task module periodically scans the customer group execution information module, filtering out tasks with an application status of "approved," an activation status of "activated," an effective deadline ≥ the system date, and corresponding model number data existing in the local push table for that day; the corresponding data is packaged into a .dat format file according to the model number, with the file name LIST_model number.dat; the content is verified during file packaging, deleting entire rows of data containing null values, and verifying the existence and uniqueness of the separator |@|; at the same time, data containing the organization number, model number, file name, and file transmission status is inserted into the customer group content information module, with the file transmission status initially being an empty value.
[0049] After the .dat format file is generated in step S3.3, the automatic task module pushes it to the designated server target path and simultaneously saves a backup locally. When the push is successful, the file transfer status in the customer group content information module changes to successful, and the most recent upload date in the customer group execution information module is updated to the system date of the push. For tasks with a single upload cycle, the enabled status automatically changes to disabled. For tasks with a daily upload cycle, the enabled status automatically changes to disabled after the system date exceeds the valid deadline. When the push fails, the file transfer status changes to failed, and the data processing, task configuration, and file verification processes need to be checked before pushing again.
[0050] After the marketing platform successfully pushes the file data and associates it with the specified tags in step S4, the tag association module of the marketing platform searches the target directory daily, extracts and loads the file data, and associates the data with multi-dimensional tags, specifically as follows: Figure 4 As shown, the tags include consumption preferences, product ownership, and activity levels, which are used by the business department to conduct secondary customer analysis and make precise marketing decisions. Figure 4The demonstration showcased the process of linking customer data with tags and conducting secondary analysis: linking "new customer information" with "model tags" (including new customer tags, gender, zodiac sign, total asset range, etc.); through the "secondary analysis" stage, combining multi-dimensional tags to further process customer information, ultimately forming a richer and more accurate customer profile, providing support for precision marketing.
[0051] Step S5: Historical Data Backup and Retention. The completed push data, including the .dat format file, task information, and data details, is stored in the historical data backup module and backed up in the historical database. (Specific details are as follows...) Figure 5 As shown; historical data supports querying by model number and push date, enabling data traceability and retrospective analysis. Figure 5 The backup logic for historical data was demonstrated: the data to be backed up includes the "Push Data Details Table", "Customer Group Execution Information Module - Execution Task Details", and "Customer Group Content Information Module - Content Details"; through the "Backup" operation, the above data is stored in the "Historical Push Data Details Table", "Customer Group Execution Information Module - Historical Execution Task Details Table", and "Customer Group Content Information Module - Historical Content Details Table" respectively, realizing full-link data retention and traceability.
[0052] Example 1: Taking customer data push in a bank's digital marketing scenario as an example, the method of the present invention will be described in detail.
[0053] Model Number Application: The bank's retail banking department plans to conduct a targeted credit card marketing campaign and needs to push target customer group data to the marketing platform. Business personnel submit the following information to the model number application module: the customer group name is "High-Potential Credit Card Customer Group," the customer group description is "Customers with spending exceeding 5,000 yuan in the past 3 months and no overdue payment records," the affiliated institution is the retail banking department, and the model validity period is from June 1, 2025 to June 30, 2025. The model number application module initiates the approval process. Upon approval, a unique model number XM202506001 is automatically generated.
[0054] Customer Information Extraction and Processing: The Financial Technology Department extracts target customer data from the ACA and NGB environments, retaining only the key field "Customer ID". The automatic batch processing module cleans the extracted data, removing invalid customer ID data, and then concatenates the data in the format "Data Date|@|Model ID|@|Customer ID" to generate standardized data, as shown in the example below: 2025-06-01|@|XM202506001|@|6226000012345678. The automatic batch processing module inserts the above standardized data into the model push information table, and simultaneously sets the push frequency to synchronize data to the local push table every 6 hours.
[0055] Push Task Configuration and Execution: The Retail Business Department configures push tasks for the Customer Group Execution Information Module with the following parameters: Institution ID is 001, Model ID is XM202506001, Upload Node is G1SZ, Target Directory is / home / file / data / 20250601 / , Upload Frequency is daily, File Type is single file, Valid Deadline is 2025-06-30, and Application Status is Approved. The Customer Group Execution Information Module detects that the application status is approved and the system time 2025-06-01 ≤ Valid Deadline 2025-06-30, automatically changing the task's activation status to Enabled. The Automatic Task Module scans tasks at 0:00, 6:00, 12:00, and 18:00 daily. After filtering out tasks that meet the criteria, it encapsulates the data of Model ID XM202506001 in the local push table into the file LIST_XM202506001.dat. During the encapsulation process, the automatic task module validates the file content, deletes rows containing null values, and confirms that the delimiter |@| is unique. After successful validation, the following data is inserted into the customer group content information module: Organization ID 001, Model ID XM202506001, Filename LIST_XM202506001.dat, and File Transfer Status is null. The automatic task module pushes the file to the specified server target path and simultaneously saves a backup file on the local server. Upon successful push, the File Transfer Status in the Customer Group Content Information module is updated to "Success," and the Last Upload Date in the Customer Group Execution Information module is updated to 2025-06-01.
[0056] Data Tagging and Marketing Applications: The marketing platform's tagging module retrieved the LIST_XM202506001.dat file from the target directory. After extracting and loading the data, it associated customer IDs with tags such as "Consumption Preferences - High-Frequency Dining Consumption," "Product Holding - Debit Card," and "Activity - More Than 10 Logins Per Month." Based on the associated data, the retail business department developed a credit card installment discount marketing plan, accurately reaching target customers, and improving marketing conversion rates by 30% compared to traditional manual push methods.
[0057] Historical Data Backup and Tracking: The historical data backup module stores the LIST_XM202506001.dat file, push task configuration information, and customer data details into the historical database. After the marketing campaign ended on June 30, staff could retrieve the full push data using model number XM202506001, complete the marketing effectiveness review and analysis, and provide data support for subsequent marketing campaigns.
[0058] In summary, this invention supports data extraction and standardized processing in multiple environments, including ACA and NGB environments, through an automatic batch processing module. It integrates customer data from different systems into a unified format and supports parallel processing of data from multiple model numbers, fully leveraging the combined power of data. Automated push notifications improve timeliness and flexibility. This invention configures parameters such as the cycle and effective time of push tasks through a customer group execution information module. Combined with the timed scanning and push functions of the automatic task module, it achieves full automation of the data push process without manual intervention. It also supports multiple push frequencies from every 3 to 12 hours, as well as flexible push cycle settings for single or daily pushes, meeting the timeliness requirements of different marketing tasks. This invention uses a dual backup mechanism of local backup and historical data backup modules to store the full amount of data, including push files, task information, and data details. It supports querying by model number and push date, achieving full-chain data traceability. Furthermore, the verification steps during file encapsulation eliminate invalid data, further ensuring data accuracy and security and solving the problems of data loss and lack of traceability. Empowering precision marketing and improving marketing efficiency, this invention links pushed data with multi-dimensional customer tags through the marketing platform's tag association module, providing business departments with accurate customer group analysis basis, helping banks to carry out personalized and precise digital marketing activities, and significantly improving marketing decision-making efficiency and marketing effectiveness.
[0059] Finally, it should be noted that the present invention is not limited to the above embodiments, and many variations are possible. All variations that can be directly derived or conceived by those skilled in the art from the disclosure of the present invention should be considered within the scope of protection of the present invention.
Claims
1. A cross-platform data intelligent sharing and automated push method based on a data middle platform, characterized in that... The method includes the following steps: Step S1: Apply for a model number: The banking business department submits the customer group name, customer group description, affiliated institution, and model validity period information to the model number application module. After the system initiates the application and it is approved, a unique model number is automatically generated. Step S2: Extract customer group information and insert it into the automatic batch processing module: The bank's financial technology department extracts target customer group data containing customer IDs. The automatic batch processing module cleans the data and removes invalid fields. The data is then concatenated into a single field in the format "data date|@|model number|@|customer number" and inserted into the model push information table. The data of the day in the model push information table is then synchronized to the local push table. At the same time, the synchronization operation is performed according to the customized multi-frequency push frequency. Step S3 pushes data across platforms based on the configured push task information and customer content information: The banking business department configures the execution information task, which includes the institution number, model number, upload node, target directory, upload cycle, file type, and effective deadline, to the customer execution information module. The system updates the activation status according to the application status and the effective deadline. The automatic task module periodically scans for tasks that meet the criteria, encapsulates the corresponding data in the local push table into a file of a specified format and performs content verification. Once the verification is successful, the file is pushed to the target path on the specified server, while a backup is stored locally. The module also updates the file transfer status, the last upload date, and the enabled status based on the push results. Step S4: The marketing platform extracts and loads file data and associates it with specified tags: The marketing platform's tag association module retrieves the pushed files and extracts and loads the data, associates the data with multi-dimensional tags, and conducts secondary customer group analysis. Step S5: Historical Data Backup and Retention: Back up historical data. The historical data backup module stores push files, task information, and data details, and supports querying data by model number and push date.
2. The method for cross-platform intelligent data sharing and automated push based on a data middle platform according to claim 1, characterized in that, In step S2, when the automatic batch processing module inserts the processed standardized data into the model push information table, it can insert data with different model numbers at the same time. The automatic batch processing module supports push frequencies of every 3 hours, every 6 hours, every 9 hours, and every 12 hours.
3. A cross-platform data intelligent sharing and automated push method based on a data middle platform according to claim 1 or 2, characterized in that, In step S3, the execution information task configured by the banking business department also includes the application status. The model number is automatically generated by the customer group execution information module and is unique. The upload node is a fixed value G1SZ. The target directory is / home / file / data / system date / . The file type includes single file type and multiple file type. The application status includes approval passed and approval failed. If the application status is approval passed and the system time is less than or equal to the valid deadline, the activation status will be automatically changed to activation. If the application status is approval failed, the push task will not be executed.
4. The cross-platform intelligent data sharing and automated push method based on a data middle platform according to claim 3, characterized in that, In step S3, the tasks scanned by the automatic task module at regular intervals must simultaneously meet the following conditions: the application status is approved, the status is enabled, the effective deadline is greater than or equal to the system date, and the corresponding model number exists in the local push table on that day. The file is packaged in .dat format and named LIST_model_number.dat. File content validation includes: checking if the "data date|@|model number|@|customer number" field has a null value. If it does, the corresponding entire row of data is deleted. At the same time, it checks if the custom separator |@| exists and is unique. When a file is pushed, data including organization number, model number, file name, and file transfer status is inserted into the customer content information module. The file transfer status is initially empty.
5. The cross-platform intelligent data sharing and automated push method based on a data middle platform according to claim 4, characterized in that, In step S3, for tasks with a single upload cycle, the enabled status will automatically change to disabled after the file is successfully pushed; for tasks with a daily upload cycle, the enabled status will automatically change to disabled after the system date exceeds the valid deadline. When a file is successfully pushed, the file transfer status in the customer content information module changes to "successful," and the most recent upload date in the customer execution information module changes to the system date of this push. When a file is pushed unsuccessfully, the file transfer status in the customer content information module changes to "failed." It is necessary to check the data processing, task configuration, and file verification processes, correct them, and then re-execute the push process.
6. The cross-platform intelligent data sharing and automated push method based on a data middle platform according to claim 1, characterized in that, The historical data stored in step S5 includes .dat format files, task information, and data details, supporting data verification, problem tracing, and post-mortem analysis.
7. A cross-platform data intelligent sharing and automated push system based on a data middleware as described in any one of claims 1-6, characterized in that, It includes a model number application module, an automatic batch processing module, a customer group execution information module, a customer group content information module, an automatic task module, a marketing platform tag association module, and a historical data backup module; The model number application module is used to receive customer group name, customer group description, affiliated institution, and model validity period information submitted by the banking business department, initiate an application, and automatically generate a unique model number after approval. The automatic batch processing module and the model number application module communicate with each other. The module is used to receive target customer data extracted by the bank's financial technology department, clean the data and remove invalid fields, and insert the standardized data into the model push information table after splicing it in a specified format. At the same time, the data of the day in the model push information table is synchronized to the local push table, and the module supports customized multiple push frequencies. The customer group execution information module communicates with the automatic batch processing module and is used to store the execution information tasks configured by the banking business department. The execution information tasks include the institution number, model number, upload node, target directory, upload cycle, file type, activation status, effective deadline, most recent upload date, and application status. At the same time, the activation status is automatically updated according to the application status and effective deadline. The customer group content information module and the customer group execution information module communicate with each other to store the organization number, model number, file name, and file transmission status information, and update the file transmission status according to the file push result; The automatic task module communicates with the automatic batch processing module, the customer group execution information module, and the customer group content information module respectively. It is used to periodically scan the tasks that meet the conditions in the customer group execution information module, encapsulate the corresponding data in the local push table into a specified format file and perform content verification. After the verification is passed, the file is pushed to the specified server target path, and the local backup process is triggered at the same time. The marketing platform tag association module communicates with the automatic task module to retrieve pushed files and extract loaded data, and associates the data with multi-dimensional tags for business departments to conduct secondary customer group analysis and precise marketing decisions. The historical data backup module communicates with the automatic task module, customer group execution information module, and customer group content information module to store push files, task information, and data details. It supports data querying by model number and push date, enabling full-link data traceability and retrospective analysis.
8. A cross-platform data intelligent sharing and automated push system based on a data middle platform according to claim 7, characterized in that, In the customer group execution information module, the upload node is a fixed value G1SZ, the target directory is / home / file / data / system date / , the upload cycle includes daily and single upload, and the file type includes single file type and multiple file type.
9. A cross-platform data intelligent sharing and automated push system based on a data middle platform according to claim 7, characterized in that, The file name generated by the automatic task module when performing the file encapsulation operation is LIST_model number.dat.
10. A cross-platform data intelligent sharing and automated push system based on a data middle platform according to claim 7, characterized in that, The marketing platform's tag association module uses multi-dimensional tags, including consumer preference tags, product ownership tags, and customer activity tags.