CN112835957A - Data quality monitoring method and system for data middling station based on block chain technology - Google Patents
Data quality monitoring method and system for data middling station based on block chain technology Download PDFInfo
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Abstract
The invention relates to a data quality monitoring method and a data quality monitoring system of a data center station based on a block chain technology. The method comprises the following steps: the service system automatically completes data consistency index statistics on the user data according to a preset time period to generate a first data consistency result; the block chain system sends a data statistics instruction to the data center station through an intelligent contract; the data center station counts data consistency indexes of the user data to generate a second data consistency result; the block chain system receives the second data consistency result, processes the first data consistency result and the second data consistency result through an intelligent contract, intelligently analyzes the data consistency and generates a consistency analysis result; judging whether the consistency analysis results all accord with consistency rules, if so, determining that the user data has consistency in the service system and the data center; if not, determining that the user data does not have consistency in the service system and the data center station. The invention ensures the consistency of data in different systems.
Description
Technical Field
The invention relates to the field of data quality monitoring, in particular to a data quality monitoring method and system of a data center station based on a block chain technology.
Background
With the continuous research and development of block chains, data quality monitoring technology is more and more concerned, whether the total amount and index value of the same data in a service system and a data center station are consistent or not is monitored to evaluate the quality of the data, which is the premise that the data can be used for supporting service decision, and the data quality is always a difficult problem which puzzles data developers and data users, wherein the data consistency is particularly common.
The inconsistency of the same piece of data among different systems can lead to a number of problems, such as: due to frequent data quality problems, data development and data users have to spend a great deal of energy on processing the data quality problems, so that the time for the business itself is reduced, the project schedule is influenced, and the working efficiency is low; the data provided for the service does not accord with the actual condition of the service, and the data is distrusted by the service and a trust crisis occurs in the past; the value of the data depends on the decision of the support service, and when the quality of the data cannot be guaranteed, the value of the data cannot be reflected. Therefore, it is important to monitor the data quality, but the existing monitoring method can only monitor the data in the same system, and cannot monitor the same data in different systems in real time, and cannot ensure the consistency of the data in different systems.
Disclosure of Invention
The invention aims to provide a data quality monitoring method and a data quality monitoring system for a data relay station based on a block chain technology, which aim to solve the problems that the existing monitoring method can only monitor data in the same system, cannot monitor the same data in different systems in real time and cannot ensure the consistency of the data in different systems.
In order to achieve the purpose, the invention provides the following scheme:
a data quality monitoring method of a data center station based on a block chain technology comprises the following steps: a service system, a block chain system and a data center;
the service system automatically completes data consistency index statistics on user data according to a preset time period to generate a first data consistency result;
the block chain system receives the first data consistency result and sends a data statistics instruction to the data middlebox through an intelligent contract;
on the basis of the first data consistency result, the data center station counts data consistency indexes of the user data according to the data statistics instruction to generate a second data consistency result;
the block chain system receives the second data consistency result, processes the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyzes data consistency, generates a consistency analysis result, and writes the consistency analysis result into the block chain system;
respectively judging whether the consistency analysis results meet consistency rules set by the service system and the data center station to obtain first judgment results;
if the first judgment result indicates that the consistency analysis results in the service system and the data center station both accord with the consistency rule set by the service system and the data center station, determining that the user data has consistency in the service system and the data center station;
and if the first judgment result indicates that the consistency analysis results in the service system and the data center station do not accord with the consistency rule set by the service system and the data center station together, determining that the user data does not have consistency in the service system and the data center station.
Optionally, the service system automatically completes data consistency index statistics on the user data according to a preset time period to generate a first data consistency result, and then further includes:
a data uplink request is sent to the blockchain system.
Optionally, the blockchain system receives the second data consistency result, processes the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyzes data consistency, generates a consistency analysis result, and writes the consistency analysis result into the blockchain system, and then further includes:
and simultaneously sending the consistency analysis result to the service system and the data center station through the intelligent contract.
Optionally, the determining that the user data has consistency in the service system and the data center station further includes:
and sending the detection result of the user data to the user client.
Optionally, the determining that the user data does not have consistency in the service system and the data center, and then further comprising:
and processing the user data to generate processed user data, taking the processed user data as the user data, and returning to the step of enabling the service system to automatically complete data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
A data quality monitoring system of a data center station based on a block chain technology comprises: a service system, a block chain system and a data center;
the first data consistency result generation module is used for automatically completing data consistency index statistics on the user data according to a preset time period by utilizing the service system to generate a first data consistency result;
the data statistics instruction sending module is used for receiving the first data consistency result by using the block chain system and sending a data statistics instruction to the data center station through an intelligent contract;
a second data consistency result generation module, configured to calculate, based on the first data consistency result, a data consistency index for the user data according to the data statistics instruction by the data center, and generate a second data consistency result;
the consistency analysis result generation module is used for receiving the second data consistency result by using the block chain system, processing the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyzing the data consistency, generating a consistency analysis result and writing the consistency analysis result into the block chain system;
the first judgment module is used for judging whether the consistency analysis results meet the consistency rules set by the service system and the data center station together respectively in the service system and the data center station to obtain a first judgment result;
a consistency determining module, configured to determine that the user data has consistency in the service system and the data center if the first determination result indicates that the consistency analysis results in the service system and the data center both conform to a consistency rule set by the service system and the data center;
and the inconsistency confirming module is used for determining that the user data does not have consistency in the service system and the data center if the first judgment result shows that the consistency analysis results in the service system and the data center do not accord with the consistency rule set by the service system and the data center together.
Optionally, the method further includes:
a data uplink request sending module, configured to send a data uplink request to the block chain system.
Optionally, the method further includes:
and the consistency analysis result sending module is used for sending the consistency analysis result to the service system and the data center station simultaneously through the intelligent contract.
Optionally, the method further includes:
and the detection result sending module is used for sending the detection result of the user data to the user client.
Optionally, the method further includes:
and the processing module is used for processing the user data to generate processed user data, taking the processed user data as the user data, and returning to the step that the business system automatically completes data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention provides a data quality monitoring method and a data quality monitoring system of a data center station based on a block chain technology, which utilize an intelligent contract in a block chain system to realize data consistency monitoring of the same part of data in different systems, for example, judge whether the total amount and index value of the same part of client data in a service system and the data center station are consistent or not, realize data consistency monitoring in the data quality monitoring process of the data center station, ensure that the user data in the service system and the data center station keep data consistency, improve the availability of the data, reduce the maintenance cost of the data consistency in the data center station construction process, and improve the trust degree of data users on the data center station data.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flow chart of a data quality monitoring method for a data center station based on a block chain technique according to the present invention;
fig. 2 is a block chain technology-based data quality monitoring system structure diagram of a data center station according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a data quality monitoring method and a data quality monitoring system for a data center station based on a block chain technology, which are used for monitoring the same data in different systems in real time and ensuring the consistency of the data in different systems.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of a data quality monitoring method for a data center station based on a block chain technique according to the present invention, and as shown in fig. 1, a data quality monitoring method for a data center station based on a block chain technique includes: a service system, a block chain system and a data center.
Step 101: and the service system automatically completes data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
The step 101 further includes: sending a data uplink request to a block chain system, and writing a first data consistency result of data consistency index statistics of uplink requested by a service system into the block chain by the block chain system after receiving the data uplink request.
Step 102: and the block chain system receives the first data consistency result and sends a data statistics instruction to the data middlebox through an intelligent contract.
Intelligent contract: and (3) processing data consistency through rule matching, for example, if the same data A exists in both a service system and a data center and both are linked, setting a matching rule in an intelligent contract to judge whether the data of the two systems are consistent.
Step 103: and on the basis of the first data consistency result, the data center station counts data consistency indexes of the user data according to the data statistics instruction to generate a second data consistency result.
The block chain system sends a data statistics command to the data center station through an intelligent contract after chaining the data consistency result counted by the service system, the data center station counts the same data consistency index of the service system according to the received command, sends a chaining request to the block chain after completing the statistics, and writes second data consistency result data counted by the data center station into the block chain after receiving the chaining request.
Step 104: and the block chain system receives the second data consistency result, processes the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyzes the data consistency, generates a consistency analysis result, and writes the consistency analysis result into the block chain system.
After the statistical data of the consistency of the two parts of data of the business system and the data center station are written into the block chain system, the block chain system processes the statistical data of the consistency of the data submitted by the business system and the data center station through an intelligent contract, intelligently analyzes the consistency of the data, and writes the consistency analysis result into the block chain.
The intelligent analysis of data consistency is to set a consistency monitoring rule in an intelligent contract and monitor whether the data of a service system and a data center station are consistent or not according to the rule, for example: total data, index range.
Consistency analysis results:
1) and if the data consistency passes, the data consistency is given.
2) The data consistency is not passed, and the user data may have the following problems:
data volume problem: the data is more and less.
The problem of index range: the index is larger and smaller.
The data formats are not consistent.
Data is missing.
The step 104 further includes: and simultaneously sending the consistency analysis result to the service system and the data center station through the intelligent contract.
Step 105: and respectively judging whether the consistency analysis results meet the consistency rules set by the service system and the data center station, if so, executing step 106, and if not, executing step 107.
Step 106: and determining that the user data has consistency in the service system and the data center station.
Said step 106 is followed by: and sending the detection result of the user data to the user client.
Step 107: determining that the user data is not consistent within the business system and the data center.
Said step 107 is followed by: and processing the user data to generate processed user data, taking the processed user data as the user data, and returning to the step of enabling the service system to automatically complete data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
And the service system and the data center station distribute and analyze data consistency analysis results returned by the intelligent contract, and if the data are consistent and accord with the consistency rule established in advance, the service system and the data center station inform the user that the data accord with the requirements. If not, the service system and the data center station process corresponding data problems according to the data consistency problem analysis result given by the intelligent contract.
Data consistency refers to a comparison result of data consistency between a service system and a data center.
The result analysis model analyzes the analysis result according to the rule to obtain the type of the problem, and the specific data object pointed by the problem, such as: the total amount of data is inconsistent, and the data of which library and table is inconsistent.
And (3) processing the analysis result by the service system:
and if the data amount is inconsistent, the service system transmits the data to the data center again.
Data index range problem, business system detection statistics logic.
And if the data formats are inconsistent, the service system detects the data formats and normalizes the formats.
And (4) data is missing, and the business system detects the reason of the data missing and sends out a missing alarm.
And (3) processing the analysis result by the station in the data:
and if the data amount is inconsistent, counting the data again.
Data index range problem, data center station detection statistical logic.
And (4) detecting the data format in the data if the data format is not constant, and normalizing the format.
And (4) data is missing, and the station in the data detects the reason of the data missing and sends out a missing alarm.
And after the data center station finishes processing the problem, the service system counts the data consistency index again, sends a data uplink request to the block chain system after counting is finished, and performs uplink processing on data consistency result data after the block chain system receives the uplink request. And after the data is linked, the intelligent contract analyzes and processes the data consistency again.
The intelligent contract analyzes the result according to the data consistency, if the data consistency problem exists, the process is repeated until the data consistency meets the rule defined in advance, and the detection result is informed to the user
Fig. 2 is a structural diagram of a data quality monitoring system of a data center station based on a block chain technology, and as shown in fig. 2, a data quality monitoring system of a data center station based on a block chain technology includes: a service system, a block chain system and a data center.
The first data consistency result generating module 201 is configured to automatically complete data consistency index statistics on the user data according to a preset time period by using the service system, and generate a first data consistency result.
A data statistics instruction issuing module 202, configured to receive the first data consistency result by using the block chain system, and issue a data statistics instruction to the data center station through an intelligent contract.
A second data consistency result generating module 203, configured to calculate, based on the first data consistency result, a data consistency index for the user data according to the data statistics instruction by the data center, and generate a second data consistency result.
The consistency analysis result generating module 204 is configured to receive the second data consistency result by using the blockchain system, process the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyze data consistency, generate a consistency analysis result, and write the consistency analysis result into the blockchain system.
A first determining module 205, configured to determine whether the consistency analysis result meets a consistency rule jointly set by the service system and the data center station in the service system and the data center station, respectively, to obtain a first determination result.
A consistency determining module 206, configured to determine that the user data has consistency in the service system and the data center if the first determination result indicates that the consistency analysis result in the service system and the data center both conform to a consistency rule set by the service system and the data center.
An inconsistency determining module 207, configured to determine that the user data does not have consistency in the service system and the data center if the first determination result indicates that the consistency analysis result in the service system and the data center does not conform to the consistency rule jointly set by the service system and the data center.
In addition, the present invention further comprises:
a data uplink request sending module, configured to send a data uplink request to the block chain system.
And the consistency analysis result sending module is used for sending the consistency analysis result to the service system and the data center station simultaneously through the intelligent contract.
And the detection result sending module is used for sending the detection result of the user data to the user client.
And the processing module is used for processing the user data to generate processed user data, taking the processed user data as the user data, and returning to the step that the business system automatically completes data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
Compared with the prior art, the invention has the following advantages:
and intellectualization, wherein data consistency monitoring is automatically carried out according to configuration rules in the detection process, and the found problems are automatically processed.
Convenience, and the consistency of the data to be monitored can be monitored through simple configuration.
Monitoring can be performed, based on the non-tamper property of the block chain, the consistency detection data of the data after uplink and the consistency comparison result can be monitored.
The source can be traced, the block chain has non-tamper-ability, the verification process of the data consistency can be traced by using the block chain, and the source of the data quality problem can be traced more quickly.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. A data quality monitoring method of a data center station based on a block chain technology is characterized by comprising the following steps: a service system, a block chain system and a data center;
the service system automatically completes data consistency index statistics on user data according to a preset time period to generate a first data consistency result;
the block chain system receives the first data consistency result and sends a data statistics instruction to the data middlebox through an intelligent contract;
on the basis of the first data consistency result, the data center station counts data consistency indexes of the user data according to the data statistics instruction to generate a second data consistency result;
the block chain system receives the second data consistency result, processes the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyzes data consistency, generates a consistency analysis result, and writes the consistency analysis result into the block chain system;
respectively judging whether the consistency analysis results meet consistency rules set by the service system and the data center station to obtain first judgment results;
if the first judgment result indicates that the consistency analysis results in the service system and the data center station both accord with the consistency rule set by the service system and the data center station, determining that the user data has consistency in the service system and the data center station;
and if the first judgment result indicates that the consistency analysis results in the service system and the data center station do not accord with the consistency rule set by the service system and the data center station together, determining that the user data does not have consistency in the service system and the data center station.
2. The method for monitoring data quality of a data center station based on a block chain technology as claimed in claim 1, wherein the service system automatically completes data consistency index statistics on user data according to a preset time period to generate a first data consistency result, and then further comprising:
a data uplink request is sent to the blockchain system.
3. A method for data quality monitoring of a data center based on blockchain technology as claimed in claim 1, wherein said blockchain system receives said second data consistency result, and processes said first data consistency result and said second data consistency result by said intelligent contract, intelligently analyzes data consistency, generates consistency analysis result, and writes said consistency analysis result into said blockchain system, and thereafter further comprising:
and simultaneously sending the consistency analysis result to the service system and the data center station through the intelligent contract.
4. The method of claim 1, wherein the determining that the user data has consistency in the service system and the data center station further comprises:
and sending the detection result of the user data to the user client.
5. The method of claim 1, wherein the determining that the user data is inconsistent in the service system and the data center station further comprises:
and processing the user data to generate processed user data, taking the processed user data as the user data, and returning to the step of enabling the service system to automatically complete data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
6. A data quality monitoring system of a data center station based on a block chain technology is characterized by comprising: a service system, a block chain system and a data center;
the first data consistency result generation module is used for automatically completing data consistency index statistics on the user data according to a preset time period by utilizing the service system to generate a first data consistency result;
the data statistics instruction sending module is used for receiving the first data consistency result by using the block chain system and sending a data statistics instruction to the data center station through an intelligent contract;
a second data consistency result generation module, configured to calculate, based on the first data consistency result, a data consistency index for the user data according to the data statistics instruction by the data center, and generate a second data consistency result;
the consistency analysis result generation module is used for receiving the second data consistency result by using the block chain system, processing the first data consistency result and the second data consistency result through the intelligent contract, intelligently analyzing the data consistency, generating a consistency analysis result and writing the consistency analysis result into the block chain system;
the first judgment module is used for judging whether the consistency analysis results meet the consistency rules set by the service system and the data center station together respectively in the service system and the data center station to obtain a first judgment result;
a consistency determining module, configured to determine that the user data has consistency in the service system and the data center if the first determination result indicates that the consistency analysis results in the service system and the data center both conform to a consistency rule set by the service system and the data center;
and the inconsistency confirming module is used for determining that the user data does not have consistency in the service system and the data center if the first judgment result shows that the consistency analysis results in the service system and the data center do not accord with the consistency rule set by the service system and the data center together.
7. The system for data quality monitoring of a data center based on blockchain technology of claim 6, further comprising:
a data uplink request sending module, configured to send a data uplink request to the block chain system.
8. The system for data quality monitoring of a data center based on blockchain technology of claim 6, further comprising:
and the consistency analysis result sending module is used for sending the consistency analysis result to the service system and the data center station simultaneously through the intelligent contract.
9. The system for data quality monitoring of a data center based on blockchain technology of claim 6, further comprising:
and the detection result sending module is used for sending the detection result of the user data to the user client.
10. The system for data quality monitoring of a data center based on blockchain technology of claim 6, further comprising:
and the processing module is used for processing the user data to generate processed user data, taking the processed user data as the user data, and returning to the step that the business system automatically completes data consistency index statistics on the user data according to a preset time period to generate a first data consistency result.
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