CN117349124A - Data quality monitoring and early warning device and method based on data blood-edge technology - Google Patents
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Abstract
The invention discloses a data quality monitoring and early warning device and a method based on a data blood-margin technology, which belong to the technical field of data quality management, the device carries out loading of original data and transmission of management information through a data quality standard protocol, management butt joint between platforms and between components in the platforms is realized through a data quality management standard adaptation framework supporting the data quality standard protocol, blood-margin management in a data circulation process is realized through a self-defined data standard quality protocol, and an association relation between data quality indexes is established, so that the warning capacity, the service application early warning risk capacity and the problem level determining capacity of a data circulation whole flow are improved, the existing data quality problem tracing difficulty is overcome, the workload of manual configuration is reduced based on an automatic establishment mechanism of the data blood-margin, and the accuracy of the data quality management is improved.
Description
Technical Field
The invention belongs to the technical field of data quality management, and particularly relates to a data quality monitoring and early warning device and method based on a data blood-edge technology.
Background
In the digital economic age, data becomes an important asset and competitive advantage of organizations and enterprises, and is widely applied to business decision making, innovation, insight and value creation, and the data quality directly determines and influences the data value, so that the data is a foundation for realizing the data economic age. The current data quality management scheme is mostly bound with a specific data quality management tool, and management is mostly carried out aiming at a specific target (such as a table, a field, a database and the like) of data to realize a specific index such as an item number, a null value rate, a value error rate and the like.
The current method has the advantages that for different data quality management scenes, firstly, the whole flow management defect exists, the whole flow of data flow often needs to span a plurality of platforms, each platform manages the respective blood edge relationship and data quality problem, because the cross-platform blood edge relationship and index aggregation analysis and quality management capability have the defects, the existing cross-platform data quality traceability mostly needs to be customized and analyzed in each data flow, the quick adaptation problem exists due to the lack of unified standards in the cross-system data quality management, the universality defect exists, and the point-to-point upgrading optimization is needed for each maintenance of a quality management system; secondly, current data quality management is focused on analyzing the cause of the problem, and has little concern for assessing downstream data risk and influence through data blood-edge management.
The method is characterized in that a general technical scheme capable of cross-platform management of data blood edges and data quality aggregation association matching is lacked in most of the current schemes, and further risk assessment and early warning are carried out, so that data quality management staff cannot establish unified data blood edge standards for cross-system data, analyze the cross-platform data blood edges, upgrade and optimize quality management tools of the cross-system rapidly through the unified standards, and effectively assess influences caused by data quality problems.
Most of the current data blood-edge is based on an independent big data platform, a blood-edge relation is built in the big data platform through sql statement analysis, and the scheme cannot support a current fast-developed data flow scene which does not pass through the sql statement scene (called as a no sql environment for short) and a data-cross-platform data flow scene, and cannot build the data-flow blood-edge relation in the whole flow of data-cross-platform flow; in the same scheme supporting cross-platform data quality management, link analysis is mostly carried out through analyzing point-to-point data configuration information among systems, and the existing scheme does not support building of global data blood relationship and lacks general expansibility. The cross-platform risk early warning capability generated by the lack of quality problems in the aspect of data quality management.
Disclosure of Invention
In order to achieve the above purpose, the technical scheme of the invention is as follows: the device carries out loading of original data and transmission of management information through a data quality standard protocol, and realizes management butt joint between platforms and between components in the platforms through a data quality management standard adaptation framework supporting the data quality standard protocol.
As an improvement of the invention, the assembly comprises a data quality early warning management assembly which is responsible for evaluating the upstream and downstream relation of quality warning source data and the upstream and downstream relation of a system according to the global data blood-edge relation, generating data flow full-flow warning information and generating a service application early warning risk prompt; and the data quality monitoring management component is responsible for generating alarm information according to the quality monitoring index result and the alarm configuration information.
As an improvement of the invention, the component also comprises a data quality index management component which is responsible for obtaining the configuration information of the quality monitoring index and generating the quality monitoring index value by statistical calculation; a data blood relationship management component; the data blood-edge relationship management component is responsible for generating data blood-edge relationships among data storage objects on the upstream and downstream sides among different modules in a cross-platform and inside the platform according to blood-edge marks in the cross-platform circulation process of detail data.
As an improvement of the invention, the component also comprises a data flow management component which is responsible for marking data storage object information in the data cross-platform and platform internal flow process; the detail data loading component is responsible for loading detail data in the data circulation process.
As an improvement of the invention, an alarm method realized by the data quality monitoring and early warning device based on the data blood edge technology comprises the following steps:
step 1) constructing a data quality management network, which comprises standard adaptation framework initialization, data flow link initialization and data quality monitoring initialization;
step 2) establishing a data blood-edge relationship, including recording upstream data source information, recording the data source information and establishing a complete blood-edge relationship;
and 3) realizing data quality management through the device, and tracing the data quality problem and early warning the risk of the whole flow of the data flow link, wherein the data quality problem and the risk early warning comprise data quality index statistical calculation, data quality index warning and data blood margin tracing and data quality risk early warning.
As an improvement of the present invention, the step 1) includes the steps of:
step 1.1) the standard adaptation frame initializing step comprises initializing a standard adaptation frame in a data stream network environment;
step 1.2), initializing each link of data stream, including initializing each data quality management external tool and service application system loaded with data quality standard protocol in the data stream network environment;
step 1.3), the step of initializing the data quality monitoring comprises the step that a data quality management external tool initializes the data monitoring index through a data quality index management component, and the data quality monitoring management component initializes the index to alarm the triggering condition.
As an improvement of the present invention, the step 2) includes the steps of:
step 2.1) when the step of recording the upstream data source information comprises reading data, recording source node information, wherein the partial capacity is defined by a data flow management component and a detail data loading component in a standard quality protocol, after the data is read, a tool supporting the standard quality protocol loads the detail data into the detail data loading component, the source node information is placed in the data flow management component, and after the information is packaged in the standard quality protocol, transmission flow is carried out to the next node;
step 2.2) when the record data source information comprises the data written in by the target node, the data flow management component synchronizes the target node information to the standard adaptation component, the record persistence of the point-to-point record of the data flow is completed, the step 2.1) and the step 2.2) are repeatedly executed in the subsequent flow process of the data, and the point-to-point record of the whole flow of the data flow is completed;
step 2.3) establishing a complete blood-lineage relationship includes the data blood-lineage relationship management component establishing a data blood-lineage relationship according to the data point-to-point circulation process recorded in step 2.1) and step 2.2).
As an improvement of the invention, the step of calculating the data quality index statistics in the step 3) comprises the step of carrying out real-time statistics on the index according to defined data quality requirements in the data circulation process by a data quality index management component in a standard quality protocol, and transmitting the statistical result to a data quality monitoring management component in real time for alarm monitoring.
As an improvement of the present invention, the step of alarming the data quality index in step 3) includes sending the alarm information to the data quality early warning management component when the data quality monitoring management component monitors that the statistic value reaches the threshold value and the alarm triggering condition is satisfied.
As an improvement of the invention, the step of data blood edge tracing and data quality risk early warning in the step 3) comprises the steps that the data quality early warning management component obtains complete data blood edge information from the data blood edge relation management component according to warning object information to form a complete warning link, meanwhile, a module analyzes a corresponding business application system at the upstream and downstream of data through warning information and blood edge management to generate business risk early warning information, and the whole process of problem tracing and risk early warning automatic reporting is completed through an external display notification tool.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the blood margin management in the data circulation process is realized through the self-defined data standard quality protocol, and the association relation between the data quality indexes is established, so that the warning capacity of the whole flow of the data circulation is improved, the early warning risk capacity and the problem standard locating capacity of the service application are improved, and the existing tracing difficulty of the data quality problem is overcome;
2. and by means of automatic flow management, manual intervention is reduced, and accuracy of data quality management is improved. The invention reduces the manual configuration process in the existing aggregation quality management process, reduces the workload of manual configuration based on an automatic establishment mechanism of data blood edges, and improves the accuracy of data quality management;
3. the invention is realized by the standardized quality management protocol, and has the characteristics of multiple applicable scenes and strong universality. The protocol defined by the invention is used for data quality management, is a general method suitable for data quality management of various service scenes, shields the differentiation of the external component technology butt joint by the standard protocol, and has universal applicability.
Drawings
Fig. 1 is a data quality management network initialization flow in the present embodiment;
FIG. 2 is a diagram illustrating a process of establishing a data blood relationship by the universal standard quality protocol in the present embodiment;
fig. 3 is a full-flow tracing process of the data quality problem in the circulation link in the present embodiment;
fig. 4 is a full flow of data quality in this embodiment.
Description of the embodiments
The invention will be further elucidated with reference to fig. 1 to 4 and the embodiments, it being understood that the following embodiments are only illustrative of the invention and are not intended to limit the scope of the invention.
Examples: according to the embodiment, through the self-defined application layer data management protocol, the flow process of detail data is subjected to data flow marking, so that field level, table level and database level business data processing flow process tracking and marking in the data treatment and data fusion process are realized, marking and management of data blood edges in the whole flow of data flow are realized, and the method is a general scheme capable of simultaneously meeting sql data processing scenes and no sql data processing scenes in the cross-platform data flow process, and the applicability and the universality of the data blood edges can be obviously improved. According to the embodiment, the data quality tracking of the whole flow of the data flow is realized by combining the data blood-source management capability and the data quality management technology, and the management capability of data quality situation awareness, quality problem tracing and risk early warning is realized. The method specifically comprises a data quality cross-platform risk early warning technology, a data quality management technology and a data blood-source cross-platform management technology. On the basis of the existing monitoring management tools (such as zabbix, grafana, promethues and the like), the problem of unified data blood-edge standard management under a cross-platform sql environment and a no sql system environment is solved firstly through a custom general data quality standard protocol, automatic exploration and automatic generation of blood-edge relations are supported, and further rapid positioning of the data quality problems is realized when the data quality problems (alarms) occur, and risk early warning of a data downstream service system is realized through the blood-edge relations; secondly, the system docking variability is shielded through a custom general data quality standard protocol, docking adaptation is realized through unified standards by cross-system data quality management docking, unified management is realized for data quality capacity upgrading and system upgrading, and the problem that system adaptation is required to be performed point-to-point when data quality upgrading is performed every time is solved.
In this embodiment, the loading of the original data and the transmission of the management information are performed by a standard data quality standard protocol (hereinafter referred to as standard quality protocol), and the management and the docking of data blood edges, quality alarms and the like between the platforms and between the components in the platform are implemented by a standard data quality management adaptation frame (hereinafter referred to as standard adaptation frame) supporting the protocol, and the architecture is shown in fig. 4.
The tool for data transmission using the present embodiment needs to load a common data quality standard protocol (hereinafter referred to as standard quality protocol) defined in the present embodiment for data transmission. Meanwhile, an external tool for performing data quality monitoring management by using the embodiment needs to load the standard quality protocol defined in the embodiment in an application protocol stack, acquire the data blood-edge association relationship by docking with a standard adaptation framework, and perform data flow full-flow quality monitoring. The basic structure of the standard quality protocol proposed in this embodiment is shown in the following table:
the standard quality protocol proposed in this embodiment defines: data flow management capability standard; data blood-margin management capability criteria; data quality index management standard; data quality monitoring management standard, data quality alarm management standard, etc. The standard framework is consistent with the corresponding functions of all the components in the standard quality protocol, and the service capability provided by all the functional components is as follows:
(1) data_quality_alarm_message: and the data quality early warning management component is responsible for evaluating the upstream and downstream relation of the quality warning source data and the upstream and downstream relation of the system according to the global data blood-edge relation, generating the whole flow warning information of the data flow and generating the service application early warning risk prompt.
(2) data_quality_monitor_message: and the data quality monitoring management component is responsible for generating alarm information according to the quality monitoring index result and the alarm configuration information.
(3) data_quality_indicators_message: and the data quality index management component is in charge of acquiring quality monitoring index configuration information and generating a quality monitoring index value through statistical calculation.
(4) data_linear_message: and the data blood-edge relationship management component is responsible for generating data blood-edge relationships between upstream and downstream data objects (such as databases, tables and fields) among the cross-platforms and among different modules in the platform according to blood-edge marks in the cross-platform circulation process of detail data.
(5) data_flow_message: and the data flow management component is responsible for marking data storage object information such as databases, tables, fields and the like in the data cross-platform and platform internal flow process.
(6) data: and loading the detail data in the data circulation process.
Further, the schematic diagram of the data quality management network is shown in fig. 1, and the procedure is as follows:
step 1, initializing a standard adaptation framework: initializing a standard adaptation frame in a data flow network environment, enabling each transmission node in the standard adaptation frame and the data flow process to have network connectivity, and enabling a standard adaptation component to have management information persistence capability.
Step 2, initializing each link of the data stream: data quality management external tools (e.g., zabbix, grafana, promethues, etc.) and business application systems each loaded with the protocol of the present embodiment are initialized in a data flow network environment. And the standard quality protocol is normally transferred among the standard adapting component, the service application system and the data quality management external tool.
Step 3, data quality monitoring and initializing: the data quality management external tool initializes the data monitoring index through the data quality indicator management component; and initializing an index alarm triggering condition through a data_quality_monitor_message data quality monitoring management component.
Further, the flow of establishing the data blood relationship through this embodiment is shown in fig. 2, and the procedure is as follows:
step 1: upstream data source information is recorded. When reading data, source node information (such as database, table, field information, etc.) is recorded. The partial capability is defined by a data_flow_message data flow management component and a data detail data loading component in a standard quality protocol, after data is read, a tool supporting the standard quality protocol loads detail data into the data component, source node information is placed in the data_flow_message component, and the information is packaged in the standard quality protocol and then transmitted to the next node.
And step 2, recording the data source information. When the target node writes data, the data_flow_message component synchronizes the target node information to the standard adaptation component, and record persistence of the data flow point-to-point is completed. And (3) repeatedly executing the step 1 and the step 2 in the subsequent circulation process of the data, and completing the point-to-point record of the whole flow of the data circulation.
And 3, establishing a complete blood relationship. And the data_linear_message data blood-edge relation management component is used for carrying out a data point-to-point circulation process recorded in the step 1 and the step 2. And establishing a data blood-edge relationship.
Further, through the implementation of data quality management in this embodiment, the flow of data quality problem tracing and risk early warning in the whole flow of the data flow link is shown in fig. 3, and the process is as follows:
and step 1, data quality index statistics calculation. In the data flow process, a data_quality_indicators_message data quality index management component in the standard quality protocol carries out real-time statistics on indexes according to defined data quality requirements, and a statistical result is transmitted to a data_quality_monitor_message data quality monitoring management component in real time for alarm monitoring.
And 2, alarming the data quality index. When the data_quality_monitor_message data quality monitoring management group monitors that the statistical value reaches a threshold value and meets an alarm triggering condition, alarm information is sent to the data_quality_alarm_message data quality alarm management group.
And 3, tracing the data blood edges and early warning the data quality risks. The data_quality_alarm_message data quality early warning management component obtains complete data blood-edge information from the data_linear_message data blood-edge relation management component according to the warning object information to form a complete warning link, meanwhile, the module analyzes a corresponding business application system at the upstream and downstream of data through warning information and blood-edge management to generate business risk early warning information, and the whole process of problem tracing and risk early warning automatic reporting is completed through an external display notification tool (such as zabbix, nails, mails and the like).
It should be noted that the foregoing merely illustrates the technical idea of the present invention and is not intended to limit the scope of the present invention, and that a person skilled in the art may make several improvements and modifications without departing from the principles of the present invention, which fall within the scope of the claims of the present invention.
Claims (10)
1. The data quality monitoring and early warning device based on the data blood-source technology is characterized in that the device carries out loading of original data and transmission of management information through a data quality standard protocol, and management butt joint among platforms and among components in the platforms is realized through a data quality management standard adaptation framework supporting the data quality standard protocol.
2. The data quality monitoring and early warning device based on the data blood-edge technology according to claim 1, wherein the component comprises a data quality early warning management component, and the data quality early warning management component is responsible for evaluating the upstream and downstream relation of quality warning source data and the upstream and downstream relation of a system according to the global data blood-edge relation, generating data flow full-flow warning information and generating a business application early warning risk prompt; and the data quality monitoring management component is responsible for generating alarm information according to the quality monitoring index result and the alarm configuration information.
3. The data quality monitoring and early warning device based on the data blood-edge technology according to claim 2, wherein the component further comprises a data quality index management component, the data quality index management component is responsible for obtaining quality monitoring index configuration information, and generating a quality monitoring index value through statistical calculation; a data blood relationship management component; the data blood-edge relationship management component is responsible for generating data blood-edge relationships among data storage objects on the upstream and downstream sides among different modules in a cross-platform and inside the platform according to blood-edge marks in the cross-platform circulation process of detail data.
4. The data quality monitoring and early warning device based on the data blood-edge technology according to claim 3, wherein the component further comprises a data flow management component, and the data flow management component is responsible for marking data storage object information in the process of data cross-platform and platform internal flow; the detail data loading component is responsible for loading detail data in the data circulation process.
5. An alarm method realized by the data quality monitoring and early warning device based on the data blood edge technology as claimed in any one of claims 1 to 4, characterized in that the method comprises the following steps:
step 1) constructing a data quality management network, which comprises standard adaptation framework initialization, data flow link initialization and data quality monitoring initialization;
step 2) establishing a data blood-edge relationship, including recording upstream data source information, recording the data source information and establishing a complete blood-edge relationship;
and 3) realizing data quality management through the device, and tracing the data quality problem and early warning the risk of the whole flow of the data flow link, wherein the data quality problem and the risk early warning comprise data quality index statistical calculation, data quality index warning and data blood margin tracing and data quality risk early warning.
6. The data quality monitoring and alarming method based on the data blood-edge technique as claimed in claim 5, wherein the step 1) comprises the steps of:
step 1.1) the standard adaptation frame initializing step comprises initializing a standard adaptation frame in a data stream network environment;
step 1.2), initializing each link of data stream, including initializing each data quality management external tool and service application system loaded with data quality standard protocol in the data stream network environment;
step 1.3), the step of initializing the data quality monitoring comprises the step that a data quality management external tool initializes the data monitoring index through a data quality index management component, and the data quality monitoring management component initializes the index to alarm the triggering condition.
7. The data quality monitoring and alarming method based on the data blood-edge technique as claimed in claim 6, wherein the step 2) comprises the steps of:
step 2.1) when the step of recording the upstream data source information comprises reading data, recording source node information, wherein the partial capacity is defined by a data flow management component and a detail data loading component in a standard quality protocol, after the data is read, a tool supporting the standard quality protocol loads the detail data into the detail data loading component, the source node information is placed in the data flow management component, and after the information is packaged in the standard quality protocol, transmission flow is carried out to the next node;
step 2.2) when the record data source information comprises the data written in by the target node, the data flow management component synchronizes the target node information to the standard adaptation component, the record persistence of the point-to-point record of the data flow is completed, the step 2.1) and the step 2.2) are repeatedly executed in the subsequent flow process of the data, and the point-to-point record of the whole flow of the data flow is completed;
step 2.3) establishing a complete blood-lineage relationship includes the data blood-lineage relationship management component establishing a data blood-lineage relationship according to the data point-to-point circulation process recorded in step 2.1) and step 2.2).
8. The method for monitoring and alarming data quality based on data blood-edge technology as claimed in claim 7, wherein the step of calculating statistics of data quality index in step 3) includes that the data quality index management component in the standard quality protocol performs real-time statistics on the index according to defined data quality requirement in the process of data circulation, and the statistical result is transmitted to the data quality monitoring management component in real time for alarming and monitoring.
9. The data quality monitoring and alarming method based on the data blood-edge technology according to claim 8, wherein the data quality index alarming step in the step 3) includes sending alarming information to the data quality early-warning management component when the data quality monitoring management component monitors that the statistics reach a threshold value, and the alarming triggering condition is satisfied.
10. The data quality monitoring and alarming method based on the data blood-edge technology according to claim 9, wherein the step of data blood-edge tracing and data quality risk early warning in the step 3) includes that the data quality early warning management component obtains complete data blood-edge information from the data blood-edge relation management component according to the alarm object information to form a complete alarm link, meanwhile, the module analyzes the corresponding business application systems at the upstream and downstream of the data through the alarm information and blood-edge management to generate business risk early warning information, and the whole process of problem tracing and risk early warning automatic reporting is completed through an external display notification tool.
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