Monitoring and early warning system based on business data

Abstract

The invention provides a monitoring and early warning system based on business data, and the system comprises a data collection module which is used for collecting business data from various data sources; a data splitting module, the data splitting module is electrically connected with the data splitting module, and the data splitting module is used for splitting the collected business data; a data storage module, the data splitting module is electrically connected with the data storage module, and the data splitting module is used for storing the processed data; the early warning analysis module is electrically connected with the data storage module, and the early warning analysis module is used for data analysis and early warning; and the message pushing module is electrically connected with the early warning analysis module, and the message pushing module is used for pushing data. The monitoring dimension and the threshold value are flexibly adjusted in a configuration mode, a user can carry out dynamic adjustment according to actual requirements, and the flexibility and the adaptability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of business data monitoring and early warning, and is a business data monitoring and early warning system based thereon. Background Art

[0002] Currently, most monitoring systems on the market mainly focus on monitoring the infrastructure level, such as CPU usage, hardware status, and network traffic. These monitoring systems can effectively help administrators track the running status of the system and ensure the stability of hardware devices and the network. However, when it comes to the business system level, the coverage and response speed of such monitoring systems are significantly insufficient. Especially when there are business failures, performance bottlenecks, or abnormal data fluctuations, traditional monitoring methods often fail to provide timely feedback and early warning.

[0003] Traditional monitoring systems usually lack in-depth monitoring of business processes and key business indicators (KPIs) and cannot identify abnormal fluctuations or potential failures in business data in real time. For example, when there are transaction delays, payment failures, or inventory data errors on an e-commerce platform, traditional monitoring systems may not be able to capture these specific business-level problems, resulting in enterprises being unable to discover and solve problems in a timely manner. In severe cases, it may even affect the customer experience and enterprise revenue.

[0004] In addition, traditional monitoring systems often rely on static threshold settings. Once the data fluctuations exceed a certain preset range, the system will trigger an alarm. However, this method is difficult to adapt to the dynamic changes in the business environment. Especially in the operation of complex business systems, there are interactions of various factors, and simple threshold early warning is difficult to meet the requirements of accurate monitoring and timely feedback.

[0005] Furthermore, it can be seen that the current systems on the market have the following disadvantages:

[0006] 1. Limited to infrastructure monitoring: Most systems only monitor the status of CPU, hardware, and network infrastructure, lacking in-depth monitoring of the business level and unable to capture business anomalies in a timely manner;

[0007] 2. Unable to provide real-time feedback on business failures: When a business system fails or has a performance bottleneck, traditional monitoring systems are difficult to provide timely feedback, resulting in problems being unable to be quickly located and processed;

[0008] 3. Lack of intelligence and flexibility: Many traditional systems rely on static threshold early warning and are unable to cope with complex and changeable business scenarios, with poor monitoring and early warning effects;

[0009] 4. Poor data correlation: Traditional monitoring systems usually fail to correlate key business data, making it difficult to provide a global perspective and accurate analysis;

[0010] 5. Inaccurate alarm information: Most alarm mechanisms are based on simple rules, which may lead to false alarms or missed alarms. Moreover, the configuration of notification methods and recipients is relatively single, and the response is not timely or flexible enough. Summary of the Invention

[0011] The present invention aims to solve the technical problems of being limited to infrastructure monitoring: Most systems only monitor the status of CPU, hardware, and network infrastructure, lacking in-depth monitoring of the business level and being unable to capture business anomalies in a timely manner; being unable to provide real-time feedback on business failures: When a business system fails or experiences performance bottlenecks, traditional monitoring systems are difficult to provide timely feedback, resulting in problems that cannot be quickly located and resolved; lacking intelligence and flexibility: Many traditional systems rely on static threshold warnings and are unable to cope with complex and ever-changing business scenarios, with poor monitoring and warning effects; poor data correlation: Traditional monitoring systems usually fail to correlate key business data, making it difficult to provide a global perspective and accurate analysis; inaccurate alarm information: Most alarm mechanisms are based on simple rules, which may lead to false alarms or missed alarms, and the configuration of notification methods and recipients is relatively single, and the response is not timely or flexible enough. Therefore, a business data-based monitoring and warning system is provided.

[0012] The present invention solves the above technical problems through the following technical solutions:

[0013] The present invention provides a business data-based monitoring and warning system, which includes:

[0014] A data collection module, which is used to collect business data from various data sources;

[0015] A data splitting module, which is electrically connected to the data collection module and is used to split the collected business data;

[0016] A data storage module, which is electrically connected to the data splitting module and is used to store the processed data;

[0017] An early warning analysis module, which is electrically connected to the data storage module and is used for data analysis and early warning;

[0018] A message push module, which is electrically connected to the early warning analysis module and is used for data push.

[0019] Furthermore, the data collection module is responsible for collecting business data from various data sources, including but not limited to traffic data, business logs, and user behavior data. The collected data is transmitted to subsequent modules after preprocessing.

[0020] Furthermore, the data splitting module splits the collected business data and classifies it according to different dimensions such as data type, business process, and device source, facilitating subsequent monitoring and analysis. The data splitting can be adjusted as needed and supports flexible configuration.

[0021] Furthermore, the data storage module uses a database or distributed storage to store the processed data, ensuring efficient data storage and real-time querying. It attaches source tags and digital signatures to each piece of data to guarantee data traceability and immutability.

[0022] Furthermore, the warning analysis module performs real-time analysis on the split data based on the configured rules, monitors key metrics such as traffic and repetition rate, and performs corresponding processing when necessary. It supports flexible rule configuration, such as threshold settings for different dimensions, data splitting degree, and alarm conditions.

[0023] Furthermore, the message push module notifies relevant personnel when warning conditions are triggered. The notification methods include but are not limited to text messages, emails, and instant messaging tools. It supports automatically selecting the notification method according to the warning type and severity and also supports user-customized notification strategies.

[0024] Furthermore, the data collection module is unidirectionally connected to the data splitting module, and the data splitting module is unidirectionally connected to the data storage module.

[0025] Furthermore, the message push module is electrically connected to the security and compliance module, and the security and compliance module is electrically connected to the user interaction module.

[0026] Furthermore, the security and compliance module is an important part for ensuring the safe and stable operation of the business data monitoring and warning system. The security and compliance module is responsible for the design of data encryption, permission management, and compliance supervision to ensure the security, integrity, and reliability of the system data.

[0027] Furthermore, the user interaction module serves as the interface between the business data monitoring and warning system and the user, responsible for providing a friendly user interface and interaction experience. Users can view real-time data, historical data, analysis results, and warning information through the user interaction module. Users can also configure warning rules, adjust warning conditions, and manage notification methods through this module to meet their own business needs.

[0028] Based on common knowledge in the art, the above preferred conditions can be combined arbitrarily to obtain various preferred embodiments of the present invention.

[0029] The positive and progressive effects of the present invention are as follows:

[0030] The above-mentioned business data monitoring and early warning system realizes multi-dimensional monitoring of business data through a flexible configuration data splitting mechanism. The monitoring dimensions are not limited to traffic, but also include data duplication rate and data quality. It can perform customized monitoring according to different types of business requirements, realizing the expansion of business data from a single monitoring dimension to multi-dimensions. It can dynamically monitor data traffic, processing status, and abnormal behaviors in different business scenarios, protecting the real-time monitoring capabilities of the monitoring system for multiple dimensions of business data traffic, duplication rate, and quality, including the specific implementation methods of data splitting, classification, and monitoring, as well as how to generate early warnings according to different monitoring dimensions;

[0031] By tagging each piece of data with a source label and signature, the system can ensure the uniqueness and traceability of the data, facilitating problem troubleshooting and increasing the security and transparency of the system;

[0032] The system supports flexible adjustment of monitoring dimensions and thresholds in a configured manner. Users can dynamically adjust according to actual needs, improving the flexibility and adaptability of the system. Brief Description of the Drawings

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application.

[0034] Figure 1 It is a flowchart of the business data monitoring and early warning system based on the present invention.

[0035] Figure 2 It is a schematic diagram of the system execution process of the business data monitoring and early warning system based on the present invention. Detailed Embodiments

[0036] In order to enable those skilled in the art to better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present application.

[0037] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0038] Embodiment:

[0039] As Figure 1-2 shown, the business data monitoring and early warning system includes:

[0040] Data collection module 1, which is used to collect business data from various data sources;

[0041] Data splitting module 2, which is electrically connected to the data splitting module 2, and is used to split the collected business data;

[0042] Data storage module 3, which is electrically connected to the data splitting module 2, and is used to store the processed data;

[0043] Early warning analysis module 4, which is electrically connected to the data storage module 3, and is used for data analysis and early warning;

[0044] Message push module 5, which is electrically connected to the early warning analysis module 4, and is used for data push.

[0045] Through a flexible configuration data splitting mechanism, multi-dimensional monitoring of business data is realized. The monitoring dimensions are not limited to traffic, but also include data duplication rate and data quality. It can perform customized monitoring for different types of business requirements, realizing the expansion of business data from a single monitoring dimension to multi-dimensions. It can dynamically monitor data traffic, processing status, and abnormal behaviors in different business scenarios, protecting the real-time monitoring ability of the monitoring system for multiple dimensions of business data traffic, duplication rate, and quality, including the specific implementation methods of data splitting, classification, and monitoring, as well as how to generate early warnings according to different monitoring dimensions; by attaching source tags and signatures to each piece of data, the system can ensure the uniqueness and traceability of the data, facilitating problem troubleshooting and increasing the security and transparency of the system; the system supports flexible adjustment of monitoring dimensions and thresholds in the form of configuration, and users can make dynamic adjustments according to actual needs, improving the flexibility and adaptability of the system.

[0046] The data collection module 1 is responsible for collecting business data from various data sources, including but not limited to traffic data, business logs, and user behavior data. The collected data is transmitted to the subsequent module after preprocessing.

[0047] The data splitting module 2 splits the collected business data and classifies it according to different dimensions such as data type, business process, and device source, facilitating subsequent monitoring and analysis. The data splitting can be adjusted as needed and supports flexible configuration.

[0048] The data storage module 3 uses a database or distributed storage to store the processed data, ensuring the efficient storage and real-time query of the data, and attaching a source tag and digital signature to each piece of data to ensure the traceability and immutability of the data.

[0049] The early warning analysis module 4 performs real-time analysis on the split data based on the configured rules, monitors key indicators such as traffic and repetition rate, and performs corresponding processing when the early warning analysis module 4 does so, supporting flexible rule configuration, such as threshold settings in different dimensions, data splitting degree, and alarm conditions.

[0050] When the early warning condition is triggered, the message push module 5 notifies relevant personnel. The notification methods include but are not limited to text messages, emails, and instant messaging tools. It supports automatically selecting the notification method according to the early warning type and severity, and also supports user-customized notification strategies.

[0051] The data collection module 1 is unidirectionally connected to the data splitting module 2, and the data splitting module 2 is unidirectionally connected to the data storage module 3.

[0052] The message push module 5 is electrically connected to the security and compliance module 6, and the security and compliance module 6 is electrically connected to the user interaction module 7.

[0053] The security and compliance module 6 is an important part for ensuring the safe and stable operation of the business data monitoring and early warning system. The security and compliance module 6 is responsible for the design in aspects of data encryption, permission management, and compliance supervision to ensure the security, integrity, and reliability of the system data.

[0054] The user interaction module 7 serves as the interface between the business data monitoring and early warning system and users, responsible for providing a friendly user interface and interaction experience. Users can view real-time data, historical data, analysis results, and early warning information through the user interaction module 7. Users can also configure early warning rules, adjust early warning conditions, and manage notification methods through this module to meet their own business needs.

[0055] Circuits, electronic components, and modules involved are all prior arts and can be fully realized by those skilled in the art without further elaboration. The content protected by this application does not involve improvements to software and methods either.

[0056] The present invention is not limited to the above embodiments. No matter what changes are made in its shape or structure, they all fall within the protection scope of the present invention. The protection scope of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A business data monitoring and early warning system, characterized in that: The business data-based monitoring and early warning system includes: A data collection module (1), wherein the data collection module (1) is used to collect business data from various data sources; A data splitting module (2), the data splitting module (2) being electrically connected to the data splitting module (2), the data splitting module (2) being used to split the collected business data; A data storage module (3), the data splitting module (2) being electrically connected to the data storage module (3), the data splitting module (2) being used to store processed data; An early warning analysis module (4), the early warning analysis module (4) being electrically connected to the data storage module (3), and the early warning analysis module (4) being used for data analysis and early warning; A message push module (5), the message push module (5) is electrically connected to the early warning analysis module (4), and the message push module (5) is used for data push.

2. The business data monitoring and early warning system according to claim 1, characterized in that: The data collection module (1) is responsible for collecting business data from various data sources, including but not limited to flow data, business logs, and user behavior data. The collected data is transmitted to subsequent modules after pre-processing.

3. The business data monitoring and early warning system according to claim 1, characterized in that: The data splitting module (2) splits the collected business data and classifies them according to different dimensions such as data type, business process and device source, so as to facilitate subsequent monitoring and analysis. The data splitting can be adjusted as needed and supports flexible configuration.

4. The business data monitoring and early warning system according to claim 1, characterized in that: The data storage module (3) uses a database or distributed storage to store processed data, ensuring efficient data storage and real-time query capabilities, and attaching a source tag and a digital signature to each piece of data to ensure data traceability and non-tamperability.

5. The business data monitoring and early warning system according to claim 1, characterized in that: The early warning analysis module (4) performs real-time analysis on the split data based on the configured rules, monitors key indicators such as flow rate and repetition rate, and performs corresponding processing, supporting flexible rule configuration, such as threshold settings of different dimensions, data splitting degree, and alarm conditions.

6. The business data monitoring and early warning system according to claim 1, characterized in that: The message push module (5) notifies relevant personnel when the warning condition is triggered. The notification methods include but are not limited to text messages, emails, and instant messaging tools. It supports automatic selection of notification methods based on the warning type and severity, and supports user customization of notification strategies.

7. The business data monitoring and early warning system according to claim 1, characterized in that: The data collection module (1) is unidirectionally connected to the data splitting module (2), and the data splitting module (2) is unidirectionally connected to the data storage module (3).

8. The business data monitoring and early warning system according to claim 1, characterized in that: The message push module (5) is electrically connected to the security and compliance module (6), and the security and compliance module (6) is electrically connected to the user interaction module (7).

9. The business data monitoring and early warning system according to claim 8, characterized in that: The security and compliance module (6) is an important component for ensuring the safe and stable operation of the business data monitoring and early warning system. The security and compliance module (6) is responsible for the design of data encryption, authority management, and compliance supervision to ensure the security, integrity, and reliability of system data.

10. The business data monitoring and early warning system according to claim 8, characterized in that: The user interaction module (7) is used as the interface between the business data monitoring and early warning system and the user, and is responsible for providing a friendly user interface and interactive experience. The user can view real-time data, historical data, analysis results and early warning information through the user interaction module (7). The user can also configure early warning rules, adjust early warning conditions, and manage notification methods through this module to meet their own business needs.

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