CN115269595A - Data label management method, system, medium and equipment based on data center - Google Patents

Abstract

The present disclosure relates to a data label management method, system, medium and device based on a data center. The method includes: using a data label scanning tool to scan a first data label in the data center and extract the first data label; Perform blood relationship analysis processing on the subsequent plurality of first data labels to obtain processed second data labels; deploy the processed second data labels in the test environment and compare with the stock labels to determine whether they are consistent, if they are consistent, The second data tag is not online; if it is inconsistent, the second data tag is online and configured. Compared with the system and method of the present disclosure, the label online verification scheme provided by the present disclosure will compare whether the first online label and the existing label are repeated, which solves the problem of repeated development and online labeling, and reduces the complexity and system redundancy. .

Description

Data label management method, system, medium and equipment based on data center

technical field

The present disclosure relates to the technical field of data label management, and more specifically, the present disclosure relates to a data label management method, system, medium, and device based on a data center.

Background technique

As a form of data with the highest value density in the data warehouse system, data labeling, its efficient management and use directly affects the company's business decisions and profits; therefore, the management of data labeling is very important. Currently on the market, enterprise data management systems generally cover scheduling management, table management, etc., but there is no comprehensive and systematic closed-loop management for these labels. The following are the current management methods in the industry:

For the management of label fields, the existing data management system can see all label fields on the table management module, or search for labels, and can find the table where the label is located: for example, there is label field a, which exists in both tables table1 and table2 , that is, enter table a, you can retrieve the table name of table1 and the a field and the table name a field of table2; then in the data monitoring system, you can also target the generation time, volatility, and data of a certain label field of a certain table Volume setting alarm monitoring.

However, the current labeling systems and labeling management measures have not formed a system and are too simple to solve some problems in daily production and use:

For example, there is the problem of repeated development and launch of labels; and the low utilization rate of some labels after launch, resulting in waste of resources.

Contents of the invention

In order to solve the technical problem that the labeling system and label management measures in the prior art are likely to cause waste of resources.

In order to achieve the above technical purpose, the present disclosure provides a data label management method based on a data center, including:

Using a data label scanning tool to scan and extract the first data label in the data platform to obtain the first data label;

Perform blood relationship analysis on the extracted plurality of first data tags to obtain processed second data tags;

Deploy the processed second data tag in the test environment and compare it with the stock tag to determine whether it is consistent. If it is consistent, the second data tag will not be launched; if not, the second data tag will be configured online.

Further, the blood relationship analysis process on the extracted multiple first data tags to obtain the processed second data tags specifically includes:

performing blood relationship analysis on the extracted plurality of first data tags according to the tag data type;

judging whether a plurality of the first data tags are consistent, if consistent, classify the plurality of first data tags into the same first data tag; if inconsistent, do not process;

An ID is configured according to the last first data tag processed by blood relationship analysis and a new second data tag is generated.

Further, the tag data type specifically includes:

Label generation logic, label field types, and/or data label result distributions.

Further, after the blood relationship analysis is performed on the extracted multiple first data tags, and after the processed second data tags are obtained, the method further includes:

Mark the second data label, and configure the validity period, business purpose and/or application system of the label.

Further, the step of deploying the processed second data tag into the test environment and comparing it with the stock tag to determine whether it is consistent specifically includes:

Deploy the processed second data label to the test environment and compare it with the stock label to determine whether the source table of the label, the way the label is generated, the result of the label data, and the distribution of the label data are consistent.

Further, after deploying the processed second data tag into the test environment and comparing it with the stock tag to determine whether it is consistent, it also includes:

Perform change processing or offline processing on the second data tag according to current business conditions.

Further, the change processing specifically includes:

changing the tag data type in the second data tag;

The offline processing specifically includes:

The second data label that is not renewed by the business party will go offline after the preset time threshold expires.

In order to achieve the above technical purpose, the present disclosure can also provide a data label management system based on the data center, including:

The label extraction module is used to scan and extract the first data label in the data center platform by using the data label scanning tool to obtain the first data label;

A tag processing module, configured to perform blood relationship analysis on the extracted first data tags to obtain processed second data tags;

The label online module is used to deploy the processed second data label to the test environment and compare it with the stock label to determine whether it is consistent. If it is consistent, the second data label will not be launched; Two data labels.

To achieve the above technical purpose, the present disclosure can also provide a computer storage medium on which a computer program is stored, and when the computer program is executed by a processor, it is used to implement the steps of the above-mentioned data label management method based on a data center.

In order to achieve the above-mentioned technical purpose, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the computer program, the above-mentioned data-based platform The steps of the data label management method.

The beneficial effects of the disclosure are:

Compared with before the improvement, the global label scanning scheme proposed in this disclosure solves the problem of manual recording of label assets in label sorting, which is easy to confuse and make mistakes, and realizes the standardization and automation of all label asset management;

Compared with the improvement before, the method of tag registration unique ID in the solution provided by this disclosure solves the problems of difficult tag search, ambiguous tag meaning, and difficult to distinguish tags with similar meanings in the actual management and use of tags, and reduces the complexity;

Compared with before the improvement, the label online verification scheme provided by this disclosure will compare whether the first online label and the stock label are duplicated, which solves the problem of repeated label development and online, and reduces complexity and system redundancy;

Compared with before the improvement, the label application analysis module provided by this disclosure monitors the whole scene of label use, so that enterprises can more comprehensively understand the use and application of labels in various systems, maximize the value of labels, and improve user experience ;

Compared with before the improvement, the tag validity period and tag offline method provided by this disclosure solve the problem of tag data redundancy and invalid data occupying system resources for a long time, and reduce storage space occupation;

Compared with the improvement before, the solution provided by the present disclosure is comprehensive, systematic, reliable, simple and convenient to use, and is a practical, effective and reproducible and popularizable method.

Description of drawings

FIG. 1 shows a schematic flow diagram of the method of Embodiment 1 of the present disclosure;

FIG. 2 shows a schematic flow diagram of the method of Embodiment 1 of the present disclosure;

FIG. 3 shows a schematic flow diagram of the method of Embodiment 1 of the present disclosure;

FIG. 4 shows a schematic structural diagram of a system according to Embodiment 2 of the present disclosure;

FIG. 5 shows a schematic structural diagram of a system according to Embodiment 2 of the present disclosure;

FIG. 6 shows a schematic structural diagram of Embodiment 4 of the present disclosure.

Detailed ways

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. It should be understood, however, that these descriptions are exemplary only, and are not intended to limit the scope of the present disclosure. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concepts of the present disclosure.

Various structural schematic diagrams according to embodiments of the present disclosure are shown in the accompanying drawings. The figures are not drawn to scale, with certain details exaggerated and possibly omitted for clarity of presentation. The shapes of various regions and layers shown in the figure and their relative sizes and positional relationships are only exemplary, and may deviate due to manufacturing tolerances or technical limitations in practice, and those skilled in the art will Regions/layers with different shapes, sizes, and relative positions can be additionally designed.

With the rapid development of cloud computing, big data, artificial intelligence and other IT technologies and their rapid integration with traditional industries, an industrial revolution brought about by digital and intelligent transformation is gestating.

With the continuous expansion of enterprise scale and business diversification - the middle-office service structure came into being. Ali released the "Double Middle Platform + ET" digital transformation methodology this year. "Double Middle Platform" refers to the digital middle platform and the business middle platform.

What is the data center:

The data center refers to the collection, calculation, storage, and processing of massive data through data technology, while unifying standards and calibers. After the data center unifies the data, it will form standard data, and then store it to form a big data asset layer, and then provide customers with efficient services. These services have a strong correlation with the business of the enterprise. They are unique to the enterprise and can be reused. They are the precipitation of the business and data of the enterprise. competitive advantage.

In a broad sense, the data center includes data technology, such as a series of technology collections, calculations, storage, and processing of massive data. The data center mentioned today includes data models, algorithm services, data products, data management, etc. It has a strong correlation with the business of the enterprise, and is unique to the enterprise and can be reused. For example, 2,000 basic models, 300 fusion models, and 50,000 labels built by the enterprise itself. It is the precipitation of enterprise business and data, which can not only reduce redundant construction and reduce the cost of chimney collaboration, but also the location of differentiated competitive advantage.

Reasons for establishing a data center:

Compared with the business middle station, the situation faced by the data middle station may be a little more complicated. Reasons for establishing a data center:

Big data can tell decision makers some potential rules, and use data to prove or judge decisions. In the past, we would use data to prove that our decisions were right or wrong, but now we use data to guide us to make the right decisions. In the era of big data, the sample is the whole, and big data can prevent forgery and deviation.

Data spawns artificial intelligence. Data is the foundation of artificial intelligence and can be fused to form new data. Data gives us unlimited innovation, let us keep trying.

Data is the instruction of the robot, and we form a data service thinking. Data is constantly changing, so machine intelligence becomes the decision-making link, and operations can be intelligent.

The goal of the middle office is to improve efficiency, data-based operations, and better support business development and innovation. It is responsible for multi-field, multi-BU, and multi-system collaboration. Zhongtai is a natural evolution of platformization. This evolution brings about a "decentralized" organizational model, highlighting the ability to reuse capabilities, coordinate control capabilities, and differentiated construction capabilities for business innovation.

Embodiment one:

As shown in Figure 1:

A data label management method based on a data center, including:

S101: Use a data label scanning tool to scan and extract the first data label in the data center to obtain the first data label;

S102: Perform blood relationship analysis on the multiple extracted first data tags to obtain processed second data tags;

S103: Deploy the processed second data tag in the test environment and compare it with the stock tag to determine whether it is consistent. If they are consistent, the second data tag will not be launched; if not, the second data tag will be deployed and configured.

Further, the pair S102 specifically includes:

performing blood relationship analysis on the extracted plurality of first data tags according to the tag data type;

judging whether a plurality of the first data tags are consistent, if consistent, classify the plurality of first data tags into the same first data tag; if inconsistent, do not process;

An ID is configured according to the last first data tag processed by blood relationship analysis and a new second data tag is generated.

In step S101, first use the Java language to develop a label scanning program (custom toolkit) to uniformly scan and extract all labels in the data center (data warehouse) to obtain the first data label.

In step S102, check the upstream dependency of the first data tag and the generation logic, tag field type, and data result distribution through blood relationship analysis. If they are consistent, it is the same tag; the system automatically registers a unique tag for each unique tag. label, and generate the above information and a unique ID number of the label.

In this way, each label of the system can be found in the system, without manual query and recording.

Further, the tag data type specifically includes:

Label generation logic, label field types, and/or data label result distributions.

Further, after the S102, the method further includes:

S104: Label the second data label, and configure the validity period, business purpose and/or application system of the label.

In step S104, the label developer configures necessary Chinese explanations and detailed meanings for the registered labels, and configures the validity period, business purpose, application system, etc. of the labels according to business needs to realize online management of all labels;

Further, the step of deploying the processed second data tag into the test environment and comparing it with the stock tag to determine whether it is consistent specifically includes:

Deploy the processed second data label to the test environment and compare it with the stock label to determine whether the source table of the label, the way the label is generated, the result of the label data, and the distribution of the label data are consistent.

In step S103, for the newly developed and launched tags, the mid-stage developers deploy the new tag codes to the test environment, and the verification program will automatically scan the new tag codes and compare the tag information with the existing ones. If the source table, generated If the code, tag data results, and data distribution are completely consistent, the tag already exists in the system and does not need to be launched. If not, a new tag will be launched.

After the new label is online, it can be found in the label query and display subsystem, and the new online label will be displayed on the homepage of the label management system and notified by email to the business personnel and middle-end developers, and the label after the launch is displayed on the development platform , the frequency of use in the scheduling system, and the application effect in the application system can all be displayed in the label display system.

As shown in Figure 3,

Further, after S103, it also includes:

S105: Perform change processing or offline processing on the second data tag according to the current service situation.

Further, the change processing specifically includes:

changing the tag data type in the second data tag;

The offline processing specifically includes:

The second data label that is not renewed by the business party will go offline after the preset time threshold expires.

In step S105, the online tag is mainly maintained during use, mainly includes tag change processing and tag offline processing.

When the business requirements are adjusted, the corresponding label business logic may also need to be changed. At this time, the label logic changes and the label ID remains unchanged, but the configuration information such as the corresponding source table, field explanation, and specific meaning will change; The label analyzes the label usage through the label query and analysis subsystem. The system will automatically push the developer and the business party to the label whose validity period is about to expire. After the developer and the business party confirm the renewal, the label will automatically renew. Confirmation of non-renewable tags can be set to go offline after a certain period of time (such as 1 month), and the system will automatically delete the tag field; thus realizing closed-loop management of all tag assets.

Embodiment two:

As shown in FIG. 4 , in order to achieve the above technical purpose, the present disclosure can also provide a data label management system 200 based on a data center, including:

The tag extraction module 201 is configured to use a data tag scanning tool to scan the first data tag in the data center and extract the first data tag;

A tag processing module 202, configured to perform blood relationship analysis on the extracted plurality of first data tags to obtain processed second data tags;

The label online module 203 is used to deploy the processed second data label in the test environment and compare it with the stock label to determine whether it is consistent. If it is consistent, the second data label will not be launched; Second data label.

The label processing module 202 is specifically used for:

performing blood relationship analysis on the extracted plurality of first data tags according to the tag data type;

judging whether a plurality of the first data tags are consistent, if consistent, classify the plurality of first data tags into the same first data tag; if inconsistent, do not process;

An ID is configured according to the last first data tag processed by blood relationship analysis and a new second data tag is generated.

As shown in FIG. 5, the data label management system 200 based on the data center described in this disclosure also includes:

The label labeling module 204 is configured to label the second data label, and configure the validity period, business purpose and/or application system of the label.

The label change processing module 205 is configured to perform change processing or offline processing on the second data label according to current business conditions.

Compared with the system and method of the present disclosure, the global label scanning scheme proposed by the present disclosure solves the problem of manual recording of label assets during label sorting, which is easy to confuse and make mistakes, and realizes the standardization and automation of all label asset management;

Compared with the system and method of the present disclosure, the method of registering a unique ID for the tag in the solution provided by the present disclosure solves the problems of difficult tag search, ambiguous tag meaning, and difficult distinction between tags with similar meanings in the actual management and use of tags. problem, reducing complexity;

Compared with the system and method of the present disclosure, the label online verification scheme provided by the present disclosure will compare whether the first online label and the stock label are duplicated, which solves the problem of repeated label development and online, and reduces the complexity and system redundancy. Remain;

Compared with the system and method of the present disclosure, the label application analysis module provided by the present disclosure monitors the whole scene of label use, so that enterprises can more comprehensively understand the use and application of labels in various systems, and make the value of labels Maximize and improve user experience;

Compared with the system and method of the present disclosure, the validity period of the label and the offline method of the label provided by the present disclosure solve the problem of redundancy of label data and long-term occupation of system resources by invalid data, and reduce the occupation of storage space;

Compared with the system and method of the present disclosure, the solution provided by the present disclosure is comprehensive, systematic, reliable, simple and convenient to use, and is a practical and effective method that can be replicated and promoted.

Embodiment three:

The present disclosure can also provide a computer storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is used to implement the steps of the above-mentioned data center-based data tag management method.

The computer storage medium of the present disclosure may be implemented using semiconductor memory, magnetic core memory, magnetic drum memory, or magnetic disk memory.

Semiconductor memory, mainly used in computers, mainly has two types of semiconductor memory elements: Mos and bipolar. Mos components are highly integrated, the process is simple but the speed is slow. Bipolar components are complex in process, high in power consumption, low in integration but fast in speed. After the advent of NMos and CMos, Mos memory began to play a major role in semiconductor memory. NMos is fast, for example, the access time of Intel's 1K-bit SRAM is 45ns. CMos consumes less power, and the 4K-bit CMos static memory access time is 300ns. The above-mentioned semiconductor memories are all random access memories (RAM), that is, they can be read and written into new content randomly during the working process. The semiconductor read-only memory (ROM) can be read randomly but cannot be written in during the working process, and it is used to store solidified programs and data. ROM is divided into non-rewritable fuse-type read-only memory ─ ─ PROM and rewritable read-only memory EPROM two.

Magnetic core memory has the characteristics of low cost and high reliability, and has more than 20 years of actual use experience. Before the mid-1970s, magnetic core memory was widely used as the main memory. Its storage capacity can reach more than 10 bits, and the fastest access time is 300ns. The typical magnetic core memory capacity in the world is 4MS ~ 8MB, and the access cycle is 1.0 ~ 1.5μs. After the rapid development of semiconductor storage replaced the magnetic core memory as the main memory, the magnetic core memory can still be used as a large-capacity expansion memory.

Drum memory, a magnetically recorded external memory. Due to its fast information access speed and stable and reliable work, although its capacity is small, it is gradually being replaced by disk storage, but it is still used as an external memory for real-time process control computers and medium and large computers. In order to meet the needs of small and microcomputers, ultra-small magnetic drums have appeared, which are small in size, light in weight, high in reliability, and easy to use.

Disk storage, a type of magnetically recorded external storage. It has the advantages of magnetic drum and magnetic tape storage, that is, its storage capacity is larger than that of magnetic drum, and its access speed is faster than that of magnetic tape storage, and it can be stored offline. Therefore, disks are widely used as large storage devices in various computer systems. capacity of external memory. Disks are generally divided into two categories: hard disks and floppy disks.

There are many types of hard disk storage. Structurally, it can be divided into interchangeable type and fixed type. Interchangeable disk platters can be exchanged, and fixed disk platters are fixed. There are two kinds of replaceable and fixed disks: multi-chip combination and single-chip structure, and both can be divided into fixed head type and movable head type. The capacity of the fixed head type disk is small, the recording density is low and the access speed is high, but the cost is high. The moving head type disk has a high recording density (up to 1000-6250 bits/inch), so it has a large capacity, but its access speed is lower than that of a fixed head disk. The storage capacity of disk products can reach hundreds of megabytes, the bit density is 6 250 bits per inch, and the track density is 475 tracks per inch. Among them, the multi-chip interchangeable disk storage has a large off-body capacity because the disk group can be replaced, and has a large capacity and high speed, and can store large-capacity intelligence data. It is widely used in online information retrieval systems and database management systems.

Embodiment four:

The present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the computer program, the above-mentioned data label management method based on the data center platform is realized. step.

Fig. 6 is a schematic diagram of the internal structure of an electronic device in one embodiment. As shown in FIG. 6, the electronic device includes a processor, a storage medium, a memory, and a network interface connected through a system bus. Wherein, the storage medium of the computer device stores an operating system, a database, and computer-readable instructions, and the database can store control information sequences. When the computer-readable instructions are executed by the processor, the processor can implement a data-based The platform's data label management method. The processor of the electrical device is used to provide computing and control capabilities, and supports the operation of the entire computer device. Computer-readable instructions may be stored in the memory of the computer device, and when the computer-readable instructions are executed by the processor, the processor may execute a data center-based data label management method. The network interface of the computer device is used for connecting and communicating with the terminal. Those skilled in the art can understand that the structure shown in FIG. 6 is only a block diagram of a part of the structure related to the solution of this application, and does not constitute a limitation on the computer equipment to which the solution of this application is applied. The specific computer equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

The electronic devices include, but are not limited to, smart phones, computers, tablet computers, wearable smart devices, artificial intelligence devices, power banks, etc.

In some embodiments, the processor can be composed of integrated circuits, for example, it can be composed of a single packaged integrated circuit, or it can be composed of multiple integrated circuits with the same function or different functions, including one or more central Processor (Central Processing unit, CPU), microprocessor, digital processing chip, graphics processor and a combination of various control chips, etc. The processor is the control core (Control Unit) of the electronic equipment, and uses various interfaces and lines to connect the various components of the entire electronic equipment, by running or executing programs or modules stored in the memory (such as executing remote data read and write programs, etc.), and call the data stored in the memory to execute various functions of the electronic device and process data.

The bus may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (EISA for short) bus or the like. The bus can be divided into address bus, data bus, control bus and so on. The bus is configured to implement communication between the memory and at least one processor.

Figure 6 only shows an electronic device with components, and those skilled in the art can understand that the structure shown in Figure 6 does not constitute a limitation to the electronic device, and may include fewer or more components than shown in the figure , or combinations of certain components, or different arrangements of components.

For example, although not shown, the electronic device may also include a power supply (such as a battery) for supplying power to each component. Preferably, the power supply may be logically connected to the at least one processor through a power management device, thereby realizing Charge management, discharge management, and power management functions. The power supply may also include one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components. The electronic device may also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be repeated here.

Further, the electronic device may also include a network interface. Optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which are usually used to communicate between the electronic device and A communication link is established between other electronic devices.

Optionally, the electronic device may further include a user interface, and the user interface may be a display (Display) or an input unit (such as a keyboard (Keyboard)). Optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, Organic Light-Emitting Diode) touch panel, and the like. Wherein, the display may also be properly referred to as a display screen or a display unit, and is used for displaying information processed in the electronic device and for displaying a visualized user interface.

Further, the computer-usable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function, etc.; use of the created data, etc.

In the several embodiments provided by the present invention, it should be understood that the disclosed devices, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each unit may physically exist separately, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software function modules.

The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. The scope of the present disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of the present disclosure, and these substitutions and modifications should all fall within the scope of the present disclosure.

Claims (10)

1. A data label management method based on a data center is characterized by comprising the following steps:

scanning a first data label in a data center station by using a data label scanning tool and extracting to obtain the first data label;

performing blood margin analysis processing on the extracted plurality of first data labels to obtain processed second data labels;

deploying the processed second data tag into a test environment, comparing the processed second data tag with the stock tag, judging whether the processed second data tag is consistent with the stock tag, and if so, not uploading the second data tag; and if the data tags are not consistent, the data tag is online and configured.

2. The method according to claim 1, wherein the obtaining of the processed second data tag by performing the blood-related analysis processing on the extracted plurality of first data tags specifically comprises:

performing blood margin analysis processing on the extracted plurality of first data labels according to the label data types;

judging whether the first data tags are consistent, and if so, classifying the first data tags into the same first data tag; if not, not processing;

an ID is configured according to the first data tag after the blood vessel analysis process and a new second data tag is generated.

3. The method according to claim 2, wherein the tag data type specifically comprises:

tag generation logic, tag field type, and/or data tag result distribution.

4. The method of claim 1, wherein after performing the blood-based analysis on the extracted plurality of first data tags to obtain a processed second data tag, the method further comprises:

and labeling the second data tag, and configuring the validity period, the service use and/or the application system of the tag.

5. The method of claim 1, wherein the step of deploying the processed second data tag into the test environment to compare the processed second data tag with the inventory tag to determine whether the processed second data tag is consistent with the inventory tag comprises:

and deploying the processed second data tags in a test environment to compare the processed second data tags with inventory tags, and judging whether a source table of the tags, a tag generation mode, a tag data result and tag data distribution are consistent.

6. The method according to any one of claims 1 to 5, wherein the step of deploying the processed second data tag into the test environment to compare with the inventory tag to determine whether the processed second data tag is consistent with the inventory tag further comprises:

and carrying out change processing or offline processing on the second data label according to the current service condition.

7. The method according to claim 6, wherein the change processing specifically includes:

changing the type of the tag data in the second data tag;

the offline processing specifically comprises:

and offline the second data label which is not updated by the service party after the preset time threshold value is expired.

8. A data station-based data tag management system, comprising:

the tag extraction module is used for scanning a first data tag in the data center station by using a data tag scanning tool and extracting the first data tag to obtain the first data tag;

the label processing module is used for performing blood margin analysis processing on the extracted plurality of first data labels to obtain processed second data labels;

the tag online module is used for deploying the processed second data tags into a test environment to compare with stock tags to judge whether the processed second data tags are consistent with the stock tags, and if so, the second data tags are not online; and if the data tags are not consistent, the data tag is online and configured.

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps corresponding to the data-middlebox-based data tag management method of any one of claims 1 to 7 when executing the computer program.

10. A computer storage medium having stored thereon computer program instructions for implementing the corresponding steps of the data-middlebox-based data tag management method of any one of claims 1-7 when executed by a processor.

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