Intelligent retrieval and visual display platform for data assets

Abstract

The invention relates to the technical field of data asset management, and discloses a data asset intelligent retrieval and visualization display platform, which comprises a data asset intelligent retrieval and visualization system, and the data asset intelligent retrieval and visualization system comprises a central processing unit. The input end of the central processing unit is electrically connected with the output end of a data analysis and mining module; according to the intelligent retrieval and visual display platform for the data assets, a user can quickly position required data resources in manners of keyword search, label screening and the like, the data retrieval efficiency is greatly improved, meanwhile, an intelligent retrieval algorithm can provide personalized search results according to the search history and preference of the user, and the user experience is improved. According to the method and the system, the retrieval accuracy is further improved, the platform performs classified management on the data assets, and a corresponding label is marked on each data set, so that a user is helped to better understand the meaning and the purpose of the data, and a more accurate matching result can be provided during retrieval.

Description

Technical Field

[0001] The present invention relates to the technical field of data asset management, and in particular to a data asset intelligent retrieval and visualization display platform. Background Art

[0002] As digital construction and development gradually penetrate into all stages of corporate strategic deployment, digital asset management has become an indispensable part of maintaining the healthy life cycle of an enterprise. The value energy contained in the huge, complex and growing data in the life cycle of an enterprise can be fully activated through proper data governance and other means to feed back into every link in the blood of the business process, inject fresh sources of vitality into the enterprise, assist in business management decisions, and achieve macro and micro cost reduction and efficiency improvement.

[0003] In order to efficiently and accurately mine the value of data, data asset intelligent retrieval and visualization display platforms have emerged. However, existing platforms of this type find it difficult to help users quickly locate the data resources they need, and the quality of the data obtained is poor, making it difficult to ensure the accuracy and reliability of the data. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent retrieval and visualization display platform for data assets, which has the advantages of rapid positioning, in-depth analysis and intuitive presentation of data assets. It solves the problem raised in the above background technology that existing platforms of this type are difficult to help users quickly locate the required data resources, and the quality of the obtained data is poor, making it difficult to ensure the accuracy and reliability of the data.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a data asset intelligent retrieval and visualization display platform, including a data asset intelligent retrieval and visualization system, the data asset intelligent retrieval and visualization system including a central processing unit, the input end of the central processing unit is electrically connected to the output end of the data analysis and mining module, the input end of the data analysis and mining module is electrically connected to the output end of the data acquisition and preprocessing module, the output end of the central processing unit is electrically connected to the input end of the data asset management module, the output end of the data asset management module is electrically connected to the input end of the central processing unit, the input end of the central processing unit is electrically connected to the output end of the data quality monitoring and governance module, the input end of the data quality monitoring and governance module is electrically connected to the output end of the central processing unit, and the output end of the central processing unit is electrically connected to the system monitoring module. The input end of the control and maintenance module is electrically connected, the output end of the central processing unit is electrically connected to the input end of the intelligent retrieval engine module, the output end of the intelligent engine retrieval module is electrically connected to the input end of the data sharing and collaboration module, the output end of the data sharing and collaboration module is electrically connected to the input of the intelligent retrieval engine module, the output end of the intelligent engine retrieval module is electrically connected to the input end of the security and privacy protection module, the output end of the security and privacy protection module is electrically connected to the input end of the intelligent retrieval engine module, the output end of the security and privacy protection module is electrically connected to the input end of the central processing unit, the output end of the central processing unit is electrically connected to the input end of the system expansion and integration module, the output end of the central processing unit is electrically connected to the input end of the visualization display module, and the output end of the visualization display module is connected to the user end signal.

[0008] Preferably, the data acquisition and preprocessing module includes a data source diversity acquisition unit, a data cleaning unit, a data conversion unit and a data integration unit.

[0009] Preferably, the data analysis and mining unit includes a statistical analysis unit, a data mining unit and a machine learning model training unit.

[0010] Preferably, the data asset management module includes a data classification and labeling unit, a permission management unit and a data lifecycle management unit.

[0011] Preferably, the data quality monitoring and governance module includes a data quality assessment unit, a data quality strategy unit and a data cleaning and repair unit.

[0012] Preferably, the system extension and integration module includes an API interface unit, a third-party integration unit and a plug-in and extension unit.

[0013] Preferably, the visualization display module includes a diversified visualization unit, an interaction and analysis unit, and a dynamic update unit.

[0014] Preferably, the system monitoring and maintenance module includes a real-time monitoring unit, a log recording unit, an error tracking unit and a version management unit.

[0015] Preferably, the data sharing and collaboration module includes a data sharing unit, a collaborative editing unit and a comment and feedback unit.

[0016] Preferably, the intelligent search engine module includes a natural language processing unit, a semantic understanding unit, an intelligent recommendation unit and a search optimization unit;

[0017] The security and privacy protection module includes a data encryption unit, an access control unit and a privacy protection unit.

[0018] (III) Beneficial effects

[0019] Compared with the prior art, the present invention provides a data asset intelligent retrieval and visual display platform, which has the following beneficial effects:

[0020] The data asset intelligent retrieval and visualization display platform allows users to quickly locate the required data resources through keyword search, tag screening, etc., greatly improving the efficiency of data retrieval. At the same time, the intelligent retrieval algorithm can also provide personalized search results based on the user's search history and preferences, further improving the accuracy of retrieval. The platform classifies and manages data assets and labels each data set accordingly, which not only helps users better understand the meaning and purpose of the data, but also provides more accurate matching results when searching;

[0021] The platform can automatically evaluate the quality of data, including data integrity, accuracy, consistency, etc., and promptly discover and resolve problems in the data, which helps ensure the reliability and accuracy of the data and provides a solid foundation for subsequent data analysis and decision-making. The platform provides data governance and cleaning tools to support users in cleaning, deduplicating, converting and other operations on data to improve data quality and availability. At the same time, the platform can also formulate personalized data governance strategies based on user needs to ensure data compliance and security. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 Schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] See also Figure 1 The present invention provides a technical solution: a data asset intelligent retrieval and visualization display platform, including a data asset intelligent retrieval and visualization system, the data asset intelligent retrieval and visualization system includes a central processing unit, the input end of the central processing unit is electrically connected to the output end of the data analysis and mining module, the input end of the data analysis and mining module is electrically connected to the output end of the data acquisition and preprocessing module, the output end of the central processing unit is electrically connected to the input end of the data asset management module, the output end of the data asset management module is electrically connected to the input end of the central processing unit, the input end of the central processing unit is electrically connected to the output end of the data quality monitoring and governance module, the input end of the data quality monitoring and governance module is electrically connected to the output end of the central processing unit, and the output end of the central processing unit is electrically connected to the system monitoring and maintenance The input end of the module is electrically connected, the output end of the central processing unit is electrically connected to the input end of the intelligent retrieval engine module, the output end of the intelligent engine retrieval module is electrically connected to the input end of the data sharing and collaboration module, the output end of the data sharing and collaboration module is electrically connected to the input of the intelligent retrieval engine module, the output end of the intelligent engine retrieval module is electrically connected to the input end of the security and privacy protection module, the output end of the security and privacy protection module is electrically connected to the input end of the intelligent retrieval engine module, the output end of the security and privacy protection module is electrically connected to the input end of the central processing unit, the output end of the central processing unit is electrically connected to the input end of the system expansion and integration module, the output end of the central processing unit is electrically connected to the input end of the visualization display module, and the output end of the visualization display module is connected to the user-end signal.

[0025] The data collection and preprocessing module includes a data source diverse collection unit, a data cleaning unit, a data conversion unit and a data integration unit. The data source diverse collection unit supports data collection from multiple data sources, including but not limited to relational databases, non-relational databases, file systems, API interfaces and web crawlers; the data cleaning unit automatically detects and corrects errors, missing values, outliers and other problems in the data through preset rules and algorithms to ensure data quality; the data conversion unit converts data of different formats and structures into a unified format to facilitate subsequent processing and analysis; the data integration unit integrates data from multiple data sources to form a complete data view and supports cross-source data query and analysis.

[0026] The data analysis and mining unit includes the statistical analysis unit, the data mining unit and the machine learning model training unit. The statistical analysis unit provides basic statistical analysis functions, such as calculations of mean, variance, standard deviation, correlation coefficient, etc., as well as advanced statistical analysis methods such as hypothesis testing and variance analysis; the data mining unit supports data mining algorithms, such as classification, clustering, association rule mining, prediction, etc., to help users discover hidden patterns and trends from data; the machine learning model training unit provides machine learning model training functions and supports a variety of machine learning algorithms. Users can use their own data sets for model training and apply them to tasks such as prediction and classification.

[0027] The data asset management module includes a data classification and labeling unit, a permission management unit and a data lifecycle management unit. The data classification and labeling unit provides flexible data classification and labeling functions, supports user-defined classification and labels, and facilitates data organization and search; the permission management unit adopts a role-based access control model to achieve fine-grained permission management to ensure data security and compliance; the data lifecycle management unit supports the full life cycle management of data creation, storage, use, archiving and destruction to ensure data compliance and validity.

[0028] The data quality monitoring and governance module includes a data quality assessment unit, a data quality strategy unit, and a data cleaning and repair unit. The data quality assessment unit regularly assesses the quality of data, including completeness, accuracy, consistency, timeliness, etc., and generates data quality reports; the data quality strategy unit formulates and implements data governance strategies, such as data standard setting, data lifecycle management, data quality improvement plans, etc.; the data cleaning and repair unit provides automated data cleaning and repair tools to automatically detect and repair quality problems in data based on preset rules and algorithms.

[0029] The system extension and integration module includes API interface unit, third-party integration unit and plug-in and extension unit. The API interface unit provides rich API interfaces, allowing users to integrate the platform's functions into their own application systems; the third-party integration unit supports integration with third-party systems (such as CRM, ERP, BI tools, etc.) to achieve seamless docking and sharing of data; the plug-in and extension unit provides plug-in and extension functions, allowing users to customize and expand the platform's functions according to their own needs.

[0030] The visualization display module includes diversified visualization units, interaction and analysis units, and dynamic update units. The diversified visualization units provide rich visualization types, including line charts, bar charts, pie charts, scatter plots, maps, dashboards, etc., to meet the needs of different scenarios; the interaction and analysis unit supports users to interact with visualization charts through operations such as dragging, zooming, and clicking, and to explore data in depth; the dynamic update unit supports real-time updating and dynamic display of data to ensure that users always see the latest data.

[0031] The system monitoring and maintenance module includes a real-time monitoring unit, a log recording unit, an error tracking unit and a version management unit. The real-time monitoring unit promptly discovers and handles potential problems by monitoring the system's operating status, resource consumption, performance indicators and other key information in real time; the log recording unit records the system's operating log in detail, including user operations, system anomalies, error information, etc., to facilitate subsequent analysis and troubleshooting; the error tracking unit provides an error tracking function that automatically captures and records system errors, making it easier for developers to quickly locate and solve problems; the version management unit supports system version management, including version release, rollback, upgrade and other functions to ensure system stability and reliability.

[0032] The data sharing and collaboration module includes a data sharing unit, a collaborative editing unit, and a comment and feedback unit. The data sharing unit provides data sharing functions, allowing users to share data resources with other users or teams, thereby promoting the flow and sharing of data; the collaborative editing unit supports multiple people to edit and modify data at the same time, and provides version control functions to ensure the consistency and integrity of the data; the comment and feedback unit provides comment and feedback functions, allowing users to comment and discuss data resources or analysis results, thereby promoting team collaboration and knowledge sharing.

[0033] The intelligent retrieval engine module includes a natural language processing unit, a semantic understanding unit, an intelligent recommendation unit, and a search optimization unit. The natural language processing unit uses NLP technology to understand the user's query intent and supports complex natural language queries; the semantic understanding unit uses semantic analysis to understand the association and context between data to improve the accuracy of retrieval; the intelligent recommendation unit intelligently recommends relevant data resources based on the user's query history and preferences to improve the user experience; the search optimization unit uses indexing technology, caching mechanism, etc. to optimize the search speed and achieve millisecond-level response

[0034] The security and privacy protection module includes a data encryption unit, an access control unit and a privacy protection unit. The data encryption unit encrypts the storage and transmission of sensitive data to ensure the security of the data; the access control unit adopts stricter access control strategies, such as multi-factor authentication and attribute-based access control (ABAC), to ensure data access rights; the privacy protection unit provides privacy protection mechanisms, such as data desensitization and anonymization, to ensure that user privacy is not leaked.

[0035] In summary, the data asset intelligent retrieval and visualization display platform allows users to quickly locate the required data resources through keyword search, tag screening and other methods, greatly improving the efficiency of data retrieval. At the same time, the intelligent retrieval algorithm can also provide personalized search results based on the user's search history and preferences, further improving the accuracy of retrieval. The platform classifies and manages data assets and labels each data set accordingly, which not only helps users better understand the meaning and purpose of the data, but also provides more accurate matching results during retrieval. The platform can automatically evaluate the quality of the data, including the integrity, accuracy, and consistency of the data, and promptly discover and solve problems in the data, which helps to ensure the reliability and accuracy of the data and provide a solid foundation for subsequent data analysis and decision-making. The platform provides data governance and cleaning tools to support users to clean, deduplicate, and convert data to improve the quality and availability of data. At the same time, the platform can also formulate personalized data governance strategies according to user needs to ensure data compliance and security.

[0036] The relevant modules involved in this system are all hardware system modules or functional modules that combine computer software programs or protocols with hardware in the prior art. The computer software programs or protocols involved in the functional modules are themselves technologies that are well known to those skilled in the art and are not improvements of this system. The improvements of this system are the interaction or connection relationships between the modules, that is, improvements to the overall structure of the system to solve the corresponding technical problems to be solved by this system.

[0037] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Data asset intelligent retrieval and visualization display platform, including data asset intelligent retrieval and visualization system, characterized by: The data asset intelligent retrieval and visualization system includes a central processing unit, an input end of the central processing unit is electrically connected to an output end of a data analysis and mining module, an input end of the data analysis and mining module is electrically connected to an output end of a data acquisition and preprocessing module, an output end of the central processing unit is electrically connected to an input end of a data asset management module, an output end of the data asset management module is electrically connected to an input end of the central processing unit, an input end of the central processing unit is electrically connected to an output end of a data quality monitoring and governance module, an input end of the data quality monitoring and governance module is electrically connected to an output end of the central processing unit, an output end of the central processing unit is electrically connected to an input end of a system monitoring and maintenance module, and an output end of the central processing unit is electrically connected to an input end of an intelligent The input end of the intelligent search engine module is electrically connected, the output end of the intelligent engine search module is electrically connected to the input end of the data sharing and collaboration module, the output end of the data sharing and collaboration module is electrically connected to the input of the intelligent search engine module, the output end of the intelligent engine search module is electrically connected to the input end of the security and privacy protection module, the output end of the security and privacy protection module is electrically connected to the input end of the intelligent search engine module, the output end of the security and privacy protection module is electrically connected to the input end of the central processing unit, the output end of the central processing unit is electrically connected to the input end of the system expansion and integration module, the output end of the central processing unit is electrically connected to the input end of the visualization display module, and the output end of the visualization display module is connected to the user end signal.

2. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The data collection and preprocessing module includes a data source diverse collection unit, a data cleaning unit, a data conversion unit and a data integration unit.

3. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The data analysis and mining unit includes a statistical analysis unit, a data mining unit and a machine learning model training unit.

4. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The data asset management module includes a data classification and labeling unit, a permission management unit and a data lifecycle management unit.

5. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The data quality monitoring and governance module includes a data quality assessment unit, a data quality strategy unit and a data cleaning and repair unit.

6. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The system expansion and integration module includes an API interface unit, a third-party integration unit and a plug-in and expansion unit.

7. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The visualization display module includes a diversified visualization unit, an interaction and analysis unit, and a dynamic update unit.

8. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The system monitoring and maintenance module includes a real-time monitoring unit, a log recording unit, an error tracking unit and a version management unit.

9. The data asset intelligent retrieval and visual display platform according to claim 1 is characterized by: The data sharing and collaboration module includes a data sharing unit, a collaborative editing unit and a comment and feedback unit.

10. The data asset intelligent retrieval and visual display platform according to claim 1, characterized in that: The intelligent search engine module includes a natural language processing unit, a semantic understanding unit, an intelligent recommendation unit and a search optimization unit; The security and privacy protection module includes a data encryption unit, an access control unit and a privacy protection unit.

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