CN115641944A - Intelligent data management method and device, computer equipment and storage medium - Google Patents

Abstract

The embodiment of the invention discloses a data intelligent management method, a data intelligent management device, computer equipment and a storage medium. The method comprises the following steps: acquiring index data of a hospital service system and input index data to obtain total index data; processing the index total data to obtain a processing result; and sending the processing result to a terminal so as to display the processing result at the terminal. By implementing the method provided by the embodiment of the invention, the accuracy of the data can be improved, the working intensity of workers is reduced, the working efficiency of the workers is improved, the informatization of the prior hospital quality data work is realized, and the fine management work of the hospital quality data is further promoted.

Description

Intelligent data management method and device, computer equipment and storage medium

Technical Field

The invention relates to a data management method, in particular to an intelligent data management method, an intelligent data management device, computer equipment and a storage medium.

Background

Medical quality is taken as a core element of hospital medical management, and throughout the whole medical process, not only the medical department, the quality management office and other functional departments need to strengthen supervision and management, but also the first-line clinical department personnel need to improve medical safety consciousness and master medical safety knowledge, and the improvement is continued. However, the medical quality management has low working efficiency, the system management does not form a system, an effective auditing and supervising mechanism is lacked, and the development of the hospital is influenced, so that a scientific and efficient informatization system is urgently needed by many hospitals to help the hospitals to realize the systematic management of the medical quality data.

The traditional manual form input and management has low efficiency and easy error in work; due to the lack of system support, the manual data has long data acquisition time and is difficult to check; the hospital has a plurality of systems, the system interrelation is complex, and the data acquisition difficulty is high; after the data is obtained at present, workers need to use table tools such as Excel and the like to correlate and summarize the data, and finally a quality control index is formed; due to the lack of professional data management tools, the statistics is large and tedious, data statistics errors are easily caused, further leading layer decision making is influenced, and the data processing difficulty is high due to the lack of professional data analysis and statistics tools; and no professional data management system exists, and data export and tabulation are not easy.

Therefore, a new method is needed to be designed, so that the accuracy of the data is improved, the working intensity of workers is reduced, the working efficiency of the workers is improved, the informatization of the prior hospital quality data work is realized, and the fine management work of the hospital quality data is further promoted.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provides a data intelligent management method, a data intelligent management device, computer equipment and a storage medium.

In order to achieve the purpose, the invention adopts the following technical scheme: the intelligent data management method comprises the following steps:

acquiring index data of a hospital service system and input index data to obtain total index data;

processing the index total data to obtain a processing result;

and sending the processing result to a terminal so as to display the processing result at the terminal.

The further technical scheme is as follows: the acquiring of index data of a hospital service system and the entered index data to obtain total index data includes:

building a data warehouse;

loading index data of the hospital business system to a data warehouse through the ETL;

inputting index data to a data warehouse;

and reading the index data in the data warehouse to obtain total index data.

The further technical scheme is as follows: the processing the index total data to obtain a processing result includes:

screening and filtering the total index data to obtain a filtering result;

performing data grouping and summarization on the filtering results to obtain a summarization result;

and carrying out data row-column rotation on the summary result to obtain a processing result.

The further technical scheme is as follows: the sending the processing result to a terminal to display the processing result at the terminal includes:

and sending the processing result to a terminal so as to display the processing result in a data icon visualization mode at the terminal.

The further technical scheme is as follows: the sending the processing result to the terminal so as to further include, after the terminal displays the processing result:

and on the basis of different protection safety levels of the front-end production system on the total index data, online protection is performed on the total index data in different environments in a mode of combining multiple data protection technologies.

The further technical scheme is as follows: the front-end-based production system is different in protection security level of the total index data, and online protection is performed on the total index data in different environments in a mode of combining multiple data protection technologies, and the method comprises the following steps:

a set of disaster recovery system is built in a local information data center to carry out a local disaster recovery center of the index total data;

using the data in the disaster recovery storage pool to verify or connect with the service of the local data center;

and establishing a remote disaster recovery system to perform multipoint disaster recovery on the index total data.

The invention also provides a data intelligent management device, which comprises:

the total data acquisition unit is used for acquiring index data of a hospital service system and input index data to obtain total index data;

the processing unit is used for processing the index total data to obtain a processing result;

and the sending unit is used for sending the processing result to a terminal so as to display the processing result at the terminal.

The further technical scheme is as follows: the total data acquisition unit includes:

the warehouse building subunit is used for building a data warehouse;

the loading subunit is used for loading the index data of the hospital business system to the data warehouse through the ETL;

the recording subunit is used for recording the index data to the data warehouse;

and the reading subunit is used for reading the index data in the data warehouse to obtain the total index data.

The invention also provides computer equipment which comprises a memory and a processor, wherein the memory is stored with a computer program, and the processor realizes the method when executing the computer program.

The invention also provides a storage medium storing a computer program which, when executed by a processor, implements the method described above.

Compared with the prior art, the invention has the beneficial effects that: according to the invention, by acquiring the total index data, processing the total index data and sending the processing result to the terminal for displaying, the accuracy of the data is improved, the working intensity of workers is reduced, the working efficiency of the workers is improved, the informatization of the prior hospital quality data work is realized, and the fine management work of the hospital quality data is further promoted.

The invention is further described below with reference to the accompanying drawings and specific embodiments.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic view of an application scenario of an intelligent data management method according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart illustrating a method for intelligently managing data according to an embodiment of the present invention;

FIG. 3 is a schematic sub-flowchart of a data intelligent management method according to an embodiment of the present invention;

FIG. 4 is a schematic sub-flowchart of a data intelligent management method according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a system provided by an embodiment of the present invention;

FIG. 6 is a flowchart illustrating a data intelligent management method according to another embodiment of the present invention;

FIG. 7 is a schematic sub-flowchart of a data intelligent management method according to another embodiment of the present invention;

FIG. 8 is a diagram illustrating an overall information-based framework according to an embodiment of the present invention;

FIG. 9 is a schematic block diagram of an intelligent data management device according to an embodiment of the present invention;

fig. 10 is a schematic block diagram of a total data obtaining unit of the intelligent data management device according to the embodiment of the present invention;

FIG. 11 is a schematic block diagram of a processing unit of the intelligent data management device according to an embodiment of the present invention;

FIG. 12 is a schematic block diagram of an intelligent data management device according to another embodiment of the present invention;

FIG. 13 is a schematic block diagram of an online protection unit of an intelligent data management device according to another embodiment of the present invention;

fig. 14 is a schematic block diagram of a computer device provided in an embodiment of 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 some, not all, embodiments of the present invention. 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.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of an intelligent data management method according to an embodiment of the present invention. Fig. 2 is a schematic flow chart of a data intelligent management method according to an embodiment of the present invention. The intelligent data management method is applied to a server. The server and the terminal carry out data interaction to realize the function of acquiring index data from a hospital service system; the method comprises the following steps of providing a function of manually inputting index data for data which are not in a system; the data is extracted, converted, cleaned and summarized; the function of managing the data, sorting the data into indexes and checking detailed data; mobile office can be realized, and the system can be accessed through a mobile phone, so that convenience is brought to business personnel; performing a data chart visualization function, generating a chart and the like according to data; carrying out multi-dimensional statistical analysis on the data to improve decision-making capability; the data summarization function can be provided, and various data analysis and quality control analysis are realized; and carrying out early warning according to the index condition, reminding that the index exceeds the range, and the like.

Fig. 2 is a flowchart illustrating a data intelligent management method according to an embodiment of the present invention. As shown in fig. 2, the method includes the following steps S110 to S130.

And S110, acquiring index data of a hospital service system and the input index data to obtain total index data.

In this embodiment, the index total data refers to index data of the hospital business system and a set of entered index data.

Specifically, a data acquisition layer is provided: the bottom layer is various data sources, mainly collects and analyzes the hospital bottom layer data, integrates scattered data, including core business data, user data, log data and the like of the hospital, and generally has two modes of traditional ETL offline collection and real-time collection.

In an embodiment, referring to fig. 3, the step S110 may include steps S111 to S114.

S111, building a data warehouse;

s112, loading index data of the hospital business system to a data warehouse through the ETL;

s113, inputting index data into a data warehouse;

and S114, reading the index data in the data warehouse to obtain total index data.

In the embodiment, hospital data sequentially passes through three stages of data generation, data storage and processing and data application from generation to application, data generated by a business system is loaded to a data warehouse through ETL, further processed in the data warehouse, and finally data analysis and visual display are realized.

For the top application to be good, the data construction of the bottom layer is very important, so the first step of the data management platform construction is to construct a data warehouse. Generally, data warehouses are technically designed in a three-tier architecture: ODS, DW, DM. The ODS is called the OperationDataStore, i.e. the operation data store. It is the layer closest to the data in the data source, and the data in the data source is extracted, cleaned, and transmitted, namely, after ETL in the legend, it is loaded into this layer. The data at this layer is mostly classified according to the classification of the source business system. DW is called DataWarehouse, i.e. data warehouse, and is the main body of data warehouse. Here, data obtained from the ODS layer establishes various data models in terms of topics. DM is collectively referred to as DateMarket, a data mart or broad sheet, and may also be referred to as or DWS. The DM layer is a theme layer oriented to final application, is generally designed according to the requirement of a front-end report, performs multi-table association on detail data of the DW layer, is used for providing subsequent service query, and has the main function of improving the query performance of the report.

The data after ETL cleaning is the data needed by people to establish a system, and at this time, the data needs to pass through a data warehouse connected with a hospital. This results in the underlying data for the hospital business system.

And S120, processing the index total data to obtain a processing result.

In this embodiment, the processing result refers to a processing result of processing the index total data.

In an embodiment, referring to fig. 4, the step S120 may include steps S121 to S123.

And S121, screening and filtering the total index data to obtain a filtering result.

In this embodiment, the filtering result refers to a result formed after data screening and filtering are performed on the total index data.

And S122, grouping and summarizing the filtering results to obtain a summarized result.

In this embodiment, the summary result refers to a result formed by grouping and grouping the data.

And S123, performing data row-column rotation on the summarized result to obtain a processing result.

In this embodiment, the processing result refers to a sum result formed by performing row-column rotation processing on the data.

In this embodiment, a data storage and processing layer is provided, where data of a data bottom layer is provided, and then data preprocessing is performed according to different requirements and scenes, and the data is stored in a suitable persistent storage layer, such as OLAP, machine learning, a database, and the like; the data analysis layer is mainly used for simply processing data and then carrying out deep analysis and mining.

Specifically, the integrated data is often data in a heterogeneous data source, so that the relationship data needs to be preliminarily processed, for example, screening indexes, and the like, and the processed table is stored in a service package as a basis for data analysis, which is called a self-service data set. The data processing method is characterized in that the data processing method is equivalent to a data container through a self-service data set mode, the IT puts cleaned data into the data set, and if the business feels that basic data are not satisfactory or cross-table combination is needed, the data set can be established independently and the data processing is carried out by the IT. After the IT personnel create the data connection and the data set, a basic data model is constructed for business personnel, and a layer of basic model for business understanding is provided. The service then further processes the data in the data set, such as screening data, filtering data, grouping and summarizing data, and performing row-column-rotation on the data, and the processed data is the final data.

And S130, sending the processing result to a terminal so as to display the processing result at the terminal.

In this embodiment, the processing result is sent to the terminal, so that the processing result is displayed in the terminal in a data icon visualization manner.

Specifically, the cleaned data is obtained, the service can be visually displayed, and the method is user-oriented, so that the service can know own data in the most intuitive and rapid mode and acquire data indexes according to own requirements.

Setting contents such as a performance assessment range, an index architecture, an index sequence, an index name, an index attribute, a calculation formula, an index source, index guidance and the like according to data of a data warehouse, and configuring a data acquisition method; finally, the indexes are assembled into a third-level official hospital index, a grade hospital evaluation index and a grade hospital evaluation data index (NCIS).

Referring to fig. 5, system management: the method comprises the following steps of managing hospital yards, wherein the hospital yards comprise a yard code, a yard abbreviation and a yard full name, and the yard code requirement is consistent with the yard code of an original system; managing departments, including managing department codes and department names, wherein the requirement of the department codes is consistent with the department codes of the original system; carry out unified management to quality control personnel, administrative or technical offices personnel, managers includes: name, login account, department to which the account belongs, system authority, and the like; the role and the authority can be managed, and the user authority can be flexibly distributed;

and (3) personal center management: modifying the personal information and the password;

data source management: managing different data sources, and supporting a database source and an interface mode to acquire data; corresponding data cleaning, clearing and summarizing can be carried out according to different data; supports various database data sources such as MYSQL, ORACLE and the like;

index dictionary management: setting the source of the index, the index calculation formula and the relevant policy data; classifying the indexes, including classifying according to an index system and classifying according to index categories (financial indexes, assessment indexes and operation indexes);

data entry management: the data entry management function can design different forms according to different data, including but not limited to the contents of times of people, number of people, amount of money, date and the like, and the form contents are data which cannot be obtained from a system at present and need to be manually entered or imported in the forms; the data entry management function can provide a template import function according to the form content;

index management: managing index data sources, showing modes and data testing; summarizing the indexes into an index table;

the performance index module of the third-level public hospital: the three-level public hospital performance index management module is used for carrying out statistical management on 150 specific indexes under the index system; reporting inspection data of large medical equipment; reporting data of clinical examination items through quality evaluation among national rooms; reporting the case death condition of the low-risk group; covering and reporting the high-quality nursing service ward; reporting the prescription of the comment prescription; reporting the purchasing condition of the basic medicine; reporting the condition of the winning bid drugs in the centralized purchasing of the national organization drugs; reporting the application function level condition of the electronic medical record; reporting the daily hospitalization workload of the medical practitioners; reporting the number of pharmacists; reporting the situation of the personnel expenditure accounting for the business expenditure; reporting the income energy consumption condition; reporting the balance of balance; reporting the condition of assets and liabilities; reporting the job title structure condition of the health technicians; reporting the proportion of anesthesia, pediatrics, severe cases, pathology and doctors of traditional Chinese medicine; reporting medical care conditions; the hospital receives the report of the condition of other hospitals for the advanced maintenance; reporting qualification examination condition of a hospital inpatients taking part in a doctor for the first time; the hospital undertakes the report of the situation of the cultured medical talents; reporting subject construction conditions; reporting the satisfaction condition of the patient; the basic information statistics of the hospital is reported;

five central indicators: index display (data display, report export, data detail check, and the like): chest pain center index: indexes such as the number of chest pain patients and emergency processing time, data display, report export, detailed data check and the like; the central index of stroke: indexes such as the number of the stroke patients and rescue conditions, data display, report export, data detail check and the like; wound center index: indexes such as the number of severely wounded people, emergency processing time, discharge condition and the like, data display, report export, data detail checking and the like; central indexes of critical pregnant and lying-in women: indexes such as the number of the gravities of the pregnant and lying-in women, emergency processing time, discharge condition and the like, data display, report export, detailed data check and the like; critical children and neonates treatment center indexes: indexes such as the number of critical medical records, emergency handling events, discharge conditions and the like, data display, report export, detailed data check and the like;

and (3) reporting indexes: reporting data of the chest pain center; reporting the stroke center data; reporting the data of the wound center; reporting central data of the critical pregnant and lying-in women; critical children and neonates treatment center data are reported;

grade hospital evaluation index module: index display (data display, report export, data detail check, and the like): grade hospital evaluation indexes; resource allocation and operation data indexes; medical service capability and hospital quality safety indexes; key professional quality control indexes; clinical application quality control indexes of key medical technology;

and (3) reporting indexes: reporting the configuration condition of the bed; reporting the medical service capability condition; reporting the quality index condition of the hospital; reporting medical safety index conditions; reporting medical safety index conditions; reporting medical quality control index conditions of anesthesia major; reporting the medical quality control index condition of the critical medical specialty; reporting the medical quality control index condition of emergency professional; reporting the medical quality control index condition of clinical examination specialty; reporting the professional medical quality control index condition of the respiratory medicine; reporting the medical quality control index condition of obstetrical department specialty; reporting the medical quality control index condition of the nervous system disease; reporting the medical quality control index condition of the kidney disease specialty; reporting medical quality control index conditions of nursing major; reporting medical quality control index conditions of medical affair management major; reporting the clinical application quality control index condition of the hematopoietic stem cell transplantation technology; reporting the condition of the clinical application quality control indexes of the homogeneous islet transplantation technology; reporting the quality control index condition of clinical application of the allogeneic exercise system structural tissue transplantation technology; reporting the quality control index condition of clinical application of the allogeneic corneal transplantation technology; reporting the quality control index condition of clinical application of the allogeneic skin transplantation technology; reporting the quality control index condition of clinical application of a sex resetting technology; reporting the condition of the quality control indexes of clinical application of the proton and heavy ion accelerator radiotherapy technology; reporting the quality control index condition of the clinical application of the radioactive particle implantation treatment technology; reporting the clinical application quality control index conditions of the tumor deep heat treatment and whole body heat treatment technologies; reporting the condition of the clinical application quality control indexes of the tumor ablation treatment technology; reporting the condition of the quality control indexes of clinical application of the ventricular assist technology; reporting the condition of the quality control indexes of clinical application of the artificial intelligence auxiliary diagnosis technology; reporting the condition of the quality control indexes of the clinical application of the artificial intelligent adjuvant therapy technology; reporting the condition of the quality control indexes of clinical application of the craniofacial surgical correction technology for craniomaxillofacial deformity; reporting the condition of clinical application quality control indexes of oral cavity, maxillofacial tumor and craniomaxillary combined radical treatment technology; reporting the technical conditions of human organ donation, acquisition and transplantation;

national medical quality management and control information Network (NCIS) data index: index display (data display, report export, data detail check, and the like): a second-level and third-level comprehensive hospital medical quality management control condition questionnaire; a daily chemotherapy medical quality and safety evaluation index questionnaire; a questionnaire of medical quality and safety evaluation indexes of the day operation; a questionnaire of clinical blood medical quality and safety evaluation indexes; a questionnaire of medical quality management control conditions of critical care medical specialties; a questionnaire for emergency professional medical quality management control conditions; a medical quality management control condition questionnaire for anesthesia specialty; a medical quality management control condition questionnaire for hospital infection management major; clinical examination professional medical quality management control condition questionnaire; a medical quality management control condition questionnaire for pathology specialty; medical quality management control condition questionnaires for medical speciality; medical record professional medical quality management control condition questionnaire; a medical quality management control condition questionnaire for respiratory medicine specialty; a medical quality management control condition questionnaire for kidney disease-dialysis technology specialty; a professional infectious disease medical quality management control condition questionnaire; a questionnaire of medical quality management control conditions of the digestive endoscopy specialty; a medical quality management control condition questionnaire of obstetrical department major; a medical quality management control condition questionnaire for rehabilitation specialty; medical quality management control condition questionnaire of the oral medicine major; a questionnaire of medical quality management control conditions of the ultrasonic medical profession; a cardiovascular disease professional medical quality management control condition questionnaire; a medical quality management control condition questionnaire for outpatient service; medical quality management control condition questionnaire of tumor major; a professional medical quality management control condition questionnaire of nervous system diseases; a clinical nutrition professional medical quality management control condition questionnaire; a medical quality management control condition questionnaire for the plastic and beauty profession; a health examination and management professional medical quality management control condition questionnaire; a questionnaire of otolaryngology professional medical quality management control conditions; a questionnaire of medical quality management control conditions of ophthalmic specialty; a questionnaire of medical quality management control conditions of nuclear medicine major; a questionnaire of pain professional medical quality management control conditions; a radiographic professional medical quality management control condition questionnaire;

and (3) reporting data: reporting the in-patient death index condition; reporting the re-returning index condition; reporting hospital acquired index conditions of inpatients; reporting relevant index conditions of twenty key disease species; reporting the relevant index conditions of sixteen key tumors in non-operative treatment; reporting relevant index conditions of fourteen key malignant tumor hospitalization operation treatments; reporting the operation management index condition of the hospital; reporting the quality index condition of the disease breeding process; reporting the additional information condition; reporting the daily chemotherapy medical quality and safety evaluation index questionnaire condition; reporting the medical quality of the operation in the daytime and the condition of a safety evaluation index questionnaire; reporting the medical quality of the clinical blood and the condition of a safety evaluation index questionnaire; reporting the condition of a questionnaire of the medical quality management control condition of the critical medical specialty; reporting the condition of a questionnaire of emergency professional medical quality management control condition; reporting the condition of a questionnaire of medical quality management control condition of anesthesia specialty; reporting the medical quality management control condition questionnaire condition of the infection management specialty of the hospital; reporting the condition of a questionnaire for clinical examination professional medical quality management control condition; reporting the medical quality management control condition questionnaire condition of the pathology specialty; reporting medical quality management control condition questionnaires of the medical profession; report the medical quality management control condition questionnaire condition of the medical record specialty; reporting the condition of a medical quality management control condition questionnaire of the department of respiratory medicine; reporting the condition of a professional medical quality management control condition questionnaire of the kidney disease-dialysis technology; report the condition of a professional medical quality management control condition questionnaire of infectious diseases; reporting the medical quality management control condition questionnaire condition of the digestive endoscopy specialty; the obstetrical department professional medical quality management control condition questionnaire condition is reported; reporting the medical quality management control condition questionnaire condition of the rehabilitation specialty; reporting the medical quality management control condition questionnaire condition of the oral medical specialty; reporting the condition of a questionnaire of the medical quality management control condition of the ultrasonic medical specialty; reporting the medical quality management control condition questionnaire condition of the cardiovascular disease major; reporting the medical quality management control condition questionnaire condition of outpatient service specialty; report the medical quality management control condition questionnaire condition of the tumor major; reporting the condition of a professional medical quality management control condition questionnaire of the nervous system disease; reporting the condition of a clinical nutrition professional medical quality management control condition questionnaire; form the professional medical quality management of cosmetology and control the situation of the questionnaire to report; reporting the health examination and management professional medical quality management control condition questionnaire condition; reporting the condition of a questionnaire of the professional medical quality management control condition of the ear, nose and throat; reporting the condition of a questionnaire of medical quality management control conditions of the ophthalmology specialty; reporting the condition of a questionnaire of the medical quality management control condition of the nuclear medicine major; reporting the condition of a questionnaire of pain professional medical quality management control conditions; reporting the condition of a questionnaire of professional medical quality management control conditions of the radiographic image;

a mobile terminal of the mobile phone: using a mobile terminal of the mobile phone to display each index module: a third-level public hospital performance index module; five central indicators; grade hospital reviews the data index; national medical quality management and control information Network (NCIS) data index.

According to the intelligent data management method, the total index data are obtained, processed and sent to the terminal for displaying, so that the data accuracy is improved, the working strength of workers is reduced, the working efficiency of the workers is improved, the informatization of the prior hospital quality data work is realized, and the fine management work of the hospital quality data is further promoted.

Fig. 6 is a flowchart illustrating a data intelligent management method according to another embodiment of the present invention. As shown in fig. 6, the intelligent data management method of the present embodiment includes step S240. Steps S210 to S230 are similar to steps S110 to S130 in the above embodiment, and are not described herein again. The added step S240 in the present embodiment is explained in detail below.

S240, on the basis that the protection security levels of the total index data by the front-end production system are different, online protection is performed on the total index data in different environments in a mode of combining multiple data protection technologies.

Specifically, a set of complete and uniform data protection system is constructed, data protection of various computer systems is managed in a centralized mode, safety and reliability of data of a front-end application system data system are guaranteed, and reliable recovery capability is achieved when software logic errors, hardware faults or disasters occur.

In an embodiment, referring to fig. 7, the step S240 may include steps S241 to S243.

S241, building a set of disaster recovery system in a local information data center to perform a local disaster recovery center of the index total data;

and S242, verifying or connecting the service of the local data center by using the data in the disaster recovery storage pool.

And S243, establishing a remote disaster recovery system to perform multipoint disaster recovery of the index total data.

Specifically, on the basis of different security levels of data protection by the front-end production system, a mode of combining multiple data protection technologies is adopted to perform online protection on data under different environments, a set of complete and uniform data protection system is constructed, centralized management data protection is realized, the safety and reliability of the data of the front-end application system data system are ensured, and reliable recovery capability is provided when software logic errors, hardware faults or disasters occur. The method and the device realize real-time backup of data of the key application system, can restore the data to any time point when necessary, and can quickly take over the application when a service system has a disaster failure, thereby avoiding causing long-time shutdown of the service system. Aiming at the importance of the system, a remote backup disaster recovery system of the system can be built, and the safety and reliability of system data are ensured to the maximum extent.

And establishing service continuity guarantee measures for a core service system, meeting the requirement of emergency takeover construction content at any time point, solving the risk of service interruption caused by physical faults and logic faults of the service system, and switching the service to a disaster recovery platform in time and quickly to ensure the continuous service of the core service.

For a virtualized flat service system and other service systems, a periodic mode can be adopted for data disaster recovery, and the data disaster is recovered to disaster recovery equipment, so that the data recovery work can be timely carried out after important data is lost or damaged.

The method comprises the steps of establishing unified management disaster backup resources, strategies and centralized monitoring, finally realizing data security operation and maintenance, reducing operation risks, operation and maintenance cost, operation energy consumption, operation and maintenance workload of a data center and liberating productivity of IT operation and maintenance personnel, thereby improving the overall operation and maintenance capacity of the hospital information data center and realizing flexible development of information system services.

In practice, when the informatization of the backup data fails or seriously fails, the backup data needs to be exercised in a certain time period due to the second defense line, and the integrity and the correctness of the backup data and the reliability of backup equipment need to be verified, so that disaster recovery practice needs to be performed regularly.

And constructing a remote disaster recovery system. For a core service system, a set of disaster recovery system is deployed in a remote disaster recovery center, and when a disaster caused by irresistible reasons occurs in a main production center, the disaster recovery center can be used as a second production center for production to guarantee the continuity of services.

Referring to fig. 8, a set of disaster recovery system is built in the local information data center to implement the local disaster recovery center. And the disaster recovery platform directly uses the data in the disaster recovery storage pool to carry out verification or directly connects with the service of the local data center. In the future, a different-place disaster recovery system can be established to realize a multi-point disaster recovery system.

Specifically, a set of data pp-CDP rapid disaster recovery solution is recommended and configured, a real-time data backup function is provided, the data security of the application server at any time in the I/O level is ensured, IT is helped for IT management personnel to meet the service protection requirement in the information environment, and the continuous service of the service is realized.

The Datapp-CDP is a set of integrated special disaster recovery equipment integrating data storage and disaster recovery functions; the Datapp-CDP does not change any structure of the existing informatization, and can be connected with the informatization through an Ethernet or an FC (the two can coexist) link; the Datapp-CDP is accessed into the data network in a bypass mode, and has no change and influence on the existing network topology and no influence on the normal operating system, application and production data. And installing CDPAgent user end software on the server, and synchronizing an operating system, application and data of the server into a storage space of the CDP. There are several ways to synchronize data in the Datapp-CDP: performing data synchronization according to a fixed time point; synchronized by cycle time, such as once every five minutes; according to the synchronous mode, the bandwidth capacity shortage in the synchronous process can be automatically converted into the asynchronous mode; according to the mode of the set bandwidth; the modes can be set according to the field condition; the Datapp-CDP can provide multiple copies of time points for each protected object, the maximum support is 1000 copies, which is equivalent to 1000 complete data states available at any time, and multi-history point protection is realized; the data copy needs to be extracted (the data before deletion or modification is searched), the data copy only needs to be loaded, and the unloading is carried out after the data is obtained, so that the service system does not need to be stopped or interrupted, and the operation of normal service is not influenced. The remote computer room is provided with the same set of Datapp-CDP disaster recovery system, all disaster recovery data of the local computer room are synchronized to remote CDP equipment through a special line, the data in the remote computer room can also be synchronized only on the CDP equipment of the host computer room, and the data can be disaster recovery; the Datapp-CDP adopts a sector network ablation technology and a narrow-band transmission technology to simplify and optimize data, reduces the data volume required to be transmitted, reduces the bandwidth requirement, and realizes a high-efficiency remote disaster recovery effect.

Data real-time protection, guarantee that data "0" is lost: the digital storage Datapp-CDP product provides a complete real-time data protection system independent of an application system. And installing a CDP user side on the application server and setting a real-time protection strategy.

The CDP user terminal makes continuous I/O record on the protected core service system, and after the data video recording function is started, the Datapp-CDP will open up an area on the disk separately for recording each historical I/O of the production volume. When the recovery is carried out, the data can be recovered to any historical point, even any one I/O through the pull rod, the data of the historical point can be independently inquired, the state of a production coil is not influenced, the data can be recovered to any historical track (second level and I/O level), the recovery process can be completed instantly, the recovery mechanism is completely different from a recovery mechanism of a traditional system, and the recovery speed and the recovery capability to any time point are far ahead of the industry. The data of the Datapp-CDP can be immediately used, the lengthy data rollback process of various backup technologies is not needed, the data can be immediately used, and the recovery is independent of the data volume. Based on the above data synchronization model, the digital storage technology Datapp-CDP disaster recovery product accommodates any type of application data without separately purchasing options for different applications such as Oracle, sybase, SQL, etc.

For important data, a periodic mode is adopted for data disaster tolerance, and various data synchronization modes can be adopted: performing data synchronization according to a fixed time point; for example: at 12 o' clock each day, synchronization began. Synchronized according to cycle time, such as once per hour and minute; according to the synchronous mode, the bandwidth capacity shortage in the synchronous process can be automatically converted into the asynchronous mode; and setting a fixed value bandwidth according to the mode of setting the bandwidth, and carrying out data synchronization on the data backup by using the fixed value bandwidth.

The production server bears a large amount of computing tasks daily, and computing resources are very limited, so that the disaster recovery system is required to be incapable of occupying the resources of the server during data backup. The Datapp-CDP disaster recovery system adopts a continuous scanning technology of bottom-layer disk I/O, abandons the protocol consumption of various upper-layer file systems, only labels the change quantity in the disk track sector, and synchronously copies in real time, so that the consumption of the production host resources by the CDP disaster recovery system at any moment is controlled within 1 percent, the memory occupation is only kept at about 10MB, and the system is a set of invisible disaster recovery system.

Various malicious viruses threaten the business system to be defended, and the digital storage Datapp-CDP disaster recovery system provides a solution for all the time. The Datapp-CDP not only protects the service data on the production host, but also protects the operating system and the application software system on the whole disk. When logic errors such as malicious virus attack, software system breakdown, system error blue screen and the like occur, the rollback can be completed by a special system recovery tool within 5 minutes, the system is recovered to the original normal state, more importantly, the whole recovery is in a completely controllable range, and the loss of the latest service data cannot be caused.

The data storage Datapp-CDP disaster recovery system can perform primary data synchronization when completing the disaster recovery protection of the local application system, after the complete synchronization of the initialization, all the subsequent protection is synchronously stored based on the data change quantity, the format of the data cannot be changed in all the processes, and the compression and the duplication removal cannot be performed. In the future, remote disaster recovery machine rooms can be built in different places. A set of Datapp-CDP disaster recovery system is deployed in the disaster backup machine room, remote replication modules are respectively configured, and the two-place three-center disaster recovery solution scheme is formed by the remote replication modules and the CDP system of the local machine room. The remote replication module of the Datapp-CDP has a good deduplication optimization technology, can reduce the data volume required to be transmitted, and combines a flexible replication strategy to improve the transmission efficiency and finally reduce the required transmission band.

The data of the main machine room needs to be synchronized to the disaster-tolerant standby machine room in time when a remote disaster-tolerant system is constructed, and a large private line bandwidth cannot be configured between two local machine rooms generally, so that the data increment and the network bandwidth requirement need to be calculated in detail, and the best disaster-tolerant effect is realized with the minimum cost. According to the calculation, the amount of data that can be transmitted by a 1Mbps private line 8 hours per day (data is mainly generated in 8 hours) is: 1Mbps × 8 hours × 3600 seconds =3600MB; therefore, after the data increment of the main computer room production system is counted in detail, the bandwidth required by disaster tolerance can be calculated: data increment ÷ 8 hours ÷ 3600 seconds × 8 (B conversion to B) = required bandwidth Mbps; in consideration of the reduction in transmission speed caused by link jitter or instability, practical planning equipment is usually implemented according to the bandwidth requirement of 3 times.

The reapplication module of the digital data pp-CDP disaster recovery system provides a sector grid ablation technology, the minimum data unit for transmission is ablated to 512 bytes, and the data is cut into smaller data blocks and then compared, so that larger data volume can be transmitted in a very small bandwidth.

By the sector grid ablation technology, the Datapp-CDP can realize efficient data replication under the condition of a low-bandwidth link, the occupied bandwidth is 1/50 of the bandwidth occupied by the disk array disaster recovery technology, and a large amount of bandwidth cost is saved. The data pp-CDP disaster recovery system in the two places machine rooms can realize the duplicate removal function in the link after being provided with the Replication remote copy module. When data is transmitted at a main control end, redundancy data blocks are removed and deleted after the data is cut through a micro-block transmission technology, only the most simplified data blocks are reserved for transmission, and after the data reaches a disaster recovery end, the data is restored and written into a remote disaster recovery storage space. After the data de-duplication technology is adopted for simplification, the redundant data volume can be effectively reduced by 40%, and the transmission efficiency is improved.

The Datapp-CDP disaster recovery system provides a function of allopatric transmission based on a plurality of replication policies, and the data is replicated from the production site to the storage device of the remote site according to the required replication policies.

Continuous I/O based replication policy: a particular time of day. For example: 12 on nights each day: 00 start copying; a duration interval. For example: replication every 10 minutes; the incremental threshold is replicated. For example: the new data starts to copy beyond 5 MB; the several strategies can be used singly or in combination, and a very flexible strategy triggering mechanism is provided for an administrator, so that the data can be protected from disasters.

The core of constructing the remote disaster recovery system aims to prevent huge risks caused by site-level faults. The validity of data is usually not verified in time, and when a disaster actually occurs, there is still a risk that data cannot be recovered. Therefore, the digital storage Datapp-CDP allopatric disaster recovery system has the capability of emergency takeover and the capability of rehearsal and can effectively solve the problem.

After the data of the main computer room is remotely synchronized to the disaster recovery backup computer room, the digital storage Datapp-CDP can restore the original format of the data at the disaster recovery backup end, so that the data of the disaster recovery backup end and the data of the disaster recovery end are the same, the data recovery backup computer room also has the capacity of online data recovery and emergency take-over, and the disaster recovery drilling of a service system can be carried out in a mounted mode, so that the disaster recovery backup computer room can play an important take-over role when a site-level fault occurs.

When a database file or application file is found to be lost or corrupted, recovery using the Datapp-CDP requires only 3 steps of approximately 1 minute of recovery time. The Datapp-CDP can make a timed/real-time data copy on the mirrored production data, if a single file is lost or damaged, a time point (1000 copies of data) without loss can be found to extract the data copy for loading, then a disk can be added in the disk management of the application host, and the data copy is opened to directly find the lost file and copy the file back to the original disk.

When the database or the application system cannot be started due to data damage caused by logic errors, the logical resources or the data copies in the Datapp-CDP can be used for taking over. By utilizing the snapshot technology, various intentional and unintentional data deletion actions can be completely prevented, and different data versions at different times can be traced for data analysis or test. In combination with the data real-time protection technique of the Datapp-CDP, the data loss can be reduced to the level of "seconds".

The Datapp-CDP may also be used for takeover and recovery when the hard disk is poisoned, misformatted, mispartitioned, but not physically damaged. First, when a production disk is unavailable, the logical resources on the Datapp-CDP may be used for service takeover. The method comprises the following steps: the synchronous relation is disconnected, then the system disk and the data disk which are synchronized by the Datapp-CDP are distributed to the application host, and then the disk signature is changed into the disk signature used in the production environment, and the whole process can be finished within 1 minute, so that the method is very simple and convenient. Then, the data is synchronized to the original production disk in the background using the data recovery function of the CDPagent.

The failure of a hard disk is a serious threat, and often has fatal lethality to a business system, which often leads to complete paralysis of many business systems. The conventional IT systems in various industries generally have no good solution to the faults, and the backup systems spend a large amount of time to restore to the backup points of the previous day, namely the data storage indexes of RPO and the service restoration indexes of RTO cannot be achieved.

In the system, the data storage disaster recovery backup architecture completely solves the problem. Once the hard disk of the core fails, the Datapp-CDP equipment immediately takes over the running of the core hard disk, and the application system only needs to wait for a short hang-up time, so that the failure of the disk system is completely brought into the range which cannot cause service threat, and the killer problem of a plurality of IT systems is completely solved. After the hard disk is replaced, the data recovery function of the Datapp-CDP is used for synchronizing the data to a new hard disk in the background.

The Datapp-CDP protection scheme can restore the operating system, and when the system partition is damaged and cannot be started, the system disk in the Datapp-CDP can be directly used for starting, so that the restoration time can be greatly shortened, and the server can continue to work in a diskless mode.

The Datapp-CDP provides the following way for operating system recovery. Replace the original OS disk recovery system with the OS image on the Datapp-CDP (first choice): by the mode, the Datapp-CDP can complete the recovery of the operating system level under the VMware environment in only 1 minute. Packaging historical points of an operating system disk of a physical application server on the Datapp-CDP into a disk, distributing the disk to an ESX/ESxi server, replacing an original operating system disk of a physical machine in a bare machine distribution mode, immediately eliminating faults, normally starting production, continuously repairing operating system files of the original operating system disk after the disk is idle, and replacing a temporarily started Datapp-CDP disk.

The benefit of this approach is that normal operation of the service can be resumed immediately. Recovery of the system using RecoveryCD: the method provides a recovery mode of the operating system of the RecoveryCD, and the method needs a RecoveryCD optical disc, the optical disc is put into a new bare computer, the corresponding magnetic disc in the Datapp-CDP can be found out through the guidance of the CD, the data of the magnetic disc is recovered to the new bare computer, and then the data is started from the local magnetic disc of the server. This method requires a data copying process, and the length of time depends on the size of the data and the network bandwidth.

The advantage of this approach is a one-time, fully integrated repair operation without the need for a second shutdown.

The Datapp-CDP technology is a protection technology of continuous time points of data, and the fundamental role of the Datapp-CDP technology is to complete fault recovery at any time point at the moment of fault so as to achieve the effect of rapid and continuous service and fundamentally solve the inherent weakness of low recovery capability and non-fine time strategy in the traditional backup. The birth of the technology causes a revolution in the backup field and the disaster recovery field, and the adopted key technologies comprise: in an actual disaster recovery system, remote backup is often limited by bandwidth. Generally, 2-4M transmission bandwidth must adopt a disaster tolerance technology suitable for narrow band (a typical 2M network, the maximum number of bytes transmitted per hour is only 720MB, which does not refer to the actual data volume), otherwise, the disaster tolerance system will block and overflow data, and cannot work normally at all. The disaster recovery technology of the digital memory provides the optimization technology of the narrow-band transmission. In a general conventional disaster recovery technology based on a disk array and the like, a transmission unit is based on Block transmission, so that small data is often updated, and remote transmission requires about 4KB minimum of transmission data (Block definition). In the remote module of the digital disaster recovery technology, a sector grid ablation technology is provided, the minimum data unit to be transmitted is ablated to 512 bytes (the general software level technology is 1 block4096 bytes, and the hardware level technology is block16000 bytes), and a larger data volume can be transmitted in a very small bandwidth. The bandwidth occupied by the Datapp-CDP replication technology is 1/50 of the bandwidth occupied by the disk array disaster recovery technology, and is 1/6 of the bandwidth occupied by the conventional disaster recovery technology. The compression mode can also greatly reduce the bandwidth occupation, and the conventional situation can also reach the compression ratio of 4-5 times. Therefore, if the data is transmitted on the wide area network, the disaster recovery data transmission bandwidth cost is high, the digital sector grid ablation technology is very in line with the requirements of the narrow-band environment disaster recovery system, efficient data replication can be performed under the condition of a low-bandwidth link, and a large amount of bandwidth investment is saved for users. The Datapp-CDP adopts a virtualization storage technology to abstract and uniformly manage the rear-end storage equipment, shields the particularity of the hardware of the storage equipment to a server layer, and only keeps the uniform logical characteristics of the hardware, thereby realizing the functions of storage integration, centralized management and the like. The Datapp-CDP is a set of enterprise-level storage service software with comprehensive functions, and operates under a centralized management interface. By means of the administrator, a completely new storage network can be built, or intelligent functions can be added to the current infrastructure of the administrator. The traditional disaster recovery system which does not adopt the continuous data copy technology can not solve the disaster (called soft error, also called dynamic RPO) with the highest probability of manual error, because the remote data transmission can 'faithfully' copy the data to a remote place completely, and the damaged data can also be copied to the remote place, thereby causing the system to be completely incapable of running. Therefore, the 'automatic continuous data copy technology' in the backup scheme not only meets the functional requirement of data mirroring (namely hard errors) when the main storage is down, but also realizes the functions of preventing and correcting soft errors, and provides powerful guarantee for the normal operation of the system. In the Datapp-CDP, an important function is a multi-time point data copy technology, so that the business system of the noble party can realize the storage of version data of each time period at a short time interval. The Datapp-CDP can provide a very high level of up to 1000 automatic data copy points per application volume, i.e., ensure that each application volume has a full image per day with a storage density of 5 minutes or 1 full image every 1 hour within 10 days. High density mapping ensures that the RPO (dynamic and static) of the system is minimized. Once any kind of data loss error occurs, the maintainer can find the latest version and recover immediately. Data copy recovery is independent of data volume, and large data volume extraction is also only a minute. The mechanism of the data copy is to store the original time point data of the data block after the time point changes by using a cache, and once the system is required to retreat to a certain time point, a pointer of historical time point data can be immediately extracted by a time point data copy mode, so that the instantaneous mapping and recovery mechanism of the historical data is realized. The data copy mechanism can easily and quickly realize the instant recovery of database data, file data, system data and other time points in a disaster recovery backup system, and ensure the functional application of data extraction, analysis, query and the like.

Under the protection of the automatic continuous time point data copy technology, the quick recovery of the current and historical data is no longer difficult. Such efficient backup and restore techniques are unique to disaster-tolerant backup solutions.

The Datapp-CDP continuous I/O recording technique can restore data to any historical track (both second and I/O levels). After the data recording function is enabled, the Datapp-CDP will open a separate area on the disk for recording each historical I/O of the production volume. When the data is recovered, the data can be recovered to any historical point, even any i/o, through the pull rod, and the data of the historical point can be independently inquired, so that the state of the production roll is not influenced.

The digitally stored Datapp-CDP is provided with high speed write technology. The high-speed writing performance accelerating function can comprehensively improve the disk writing performance managed by the Datapp-CDP. When the disk performance can not meet the I/O requirement of the host, the overall performance can be obviously improved by using high-speed writing performance acceleration in cooperation with high-speed disk equipment. The principle of high speed write performance acceleration is: the high-speed disk equipment is arranged at the front end, the production data can be sequentially written into the high-speed disk equipment, and then the data in the cache is randomly written into the back-end storage according to the strategy set by the high-speed writing performance acceleration. The digital data pp-CDP also has a high-speed readout technology. The high-speed read performance acceleration function can comprehensively improve the disk read performance managed by the Datapp-CDP. When the high-speed reading performance is used for acceleration, the Datapp-CDP divides the disk into a plurality of areas with equal capacity, monitors which areas are frequently read, and then maps the data blocks of the areas into the high-speed disk, so that the speed of reading the disk by the application host is increased. If the Datapp-CDP monitors that certain regions are no longer being read often, then the region is moved out of the high speed disk.

The project system platform is developed by a B/S framework, a Web site is used for logging in, the access authority of the system needs to be developed on the Internet, and the safety of the system needs to be ensured by technical means. The method of the embodiment actively discovers the access behaviors of malicious IPs such as scanning IP, zombie IP, C & C, proxy IP and the like to WEB services, records an alarm log aiming at the malicious access behaviors and timely informs operation and maintenance management personnel to intercept the access behaviors of the malicious IPs. The method adopts double security engines, establishes a security model for a WEB service system through machine learning, assists the security engines to improve accuracy and reduce false alarm rate, and detects unknown security threats through the established security model. The intelligent security engine is internally provided with 780-class security rules, common OWASPTOP10 attack behaviors such as SQL injection, XSS, webshell, command injection and middleware bugs can be protected, and the security WAF obtains OWASPWEB application firewall authentication. The false alarm rate of the security engine is less than 0.5%; the detection rate of the safety engine is more than 98.6%; the security engine missing report rate is less than 0.2%; local DDOS protection and cloud DDOS linkage protection; professional application layer DDOS protection capability; the original detection algorithm adopts a double detection algorithm of request rate and request concentration; the CC attack can be detected based on various combined conditions such as URL, request header field, target IP, request method and the like, and the CC attack can be intercepted aiming at accurate CC attack behaviors such as short message interface, API interface, login page and the like; CC attacks the meat machine more dispersedly, it is foreign meat machine to attack in many cases, WAF can set up the regional detection algorithm of user, isolate the foreign or other provincial and municipal meat machine attacks; JS challenge can be performed after the CC rule is triggered, and man-machine discrimination can be quickly realized; self-learning a user flow model, such as newly-built and concurrent parameters, monitoring whether the flow is abnormal according to the flow model, and starting a CC (communication control) protection strategy as required; and (4) supporting CC slow attack protection, such as Slowhead and Slowbody. Only one key on the WAF is needed to be opened to realize the cloud DDOS protection of the domain name; 3-7 layers of anti-D protection are provided; the D-resistant protection capability of 100G is provided; 7X24 hour all-weather service; and (3) realizing rapid security detection, wherein different from a security feature library, the security white list does not analyze and extract WEB attack behaviors but analyzes and summarizes rules of normal access behaviors, so that detection logic of assumed security is realized. Different websites have respective independent characteristics and access rules, so the white list security feature of the WEB application firewall is clarified and defended by adopting a self-learning modeling technology, flow learning is carried out on the protected websites, and a set of security white list rules aiming at the website characteristics is finally formed by continuous security analysis and convergence based on probability statistics. In general, a WEB application firewall blocks only matched attack requests based on matching of security rules. The stateless feature matching technology has the risk of exhaustive attack, and an intruder can break through or bypass the rule matching mechanism of the WEB application firewall as long as the intruder has enough attack samples and time. If some users have deployed the WEB application firewall, the security vulnerability is still detected, namely the attack feature library of the vulnerability scanning tool is larger than the WEB application firewall feature library. The fire wall for the Minyu WEB application adopts an attacker state tracking mechanism, can intelligently identify the difference between misoperation of a user and a malicious attacker, and achieves the aim of tracking the attacker. After the attacker behavior is positioned, the blocking of the IP address of the attacker for a certain time can be realized, so that the risk of exhaustive attack is reduced. The intelligent attacker tracking analysis technology can effectively relieve the following security risks.

Specifically, the transparent proxy deployment mode supports a transparent tandem deployment approach. The system is connected in series in a user network, can realize plug and play, and does not need a user to change the configuration of network equipment and a server. The deployment is simple and easy to use, and the method is applied to most user networks. The network structure of the user does not need to be changed, and the method is transparent to the user; the safety protection capability is strong; the failure recovery is fast, and Bypass can be supported. The WAF adopts a reverse proxy mode to access a network environment in a bypass mode, a destination mapping table of a network firewall needs to be changed, the network firewall maps a service port address of the WAF, and an IP address of a server is hidden. The system can be deployed by-pass, is opaque to a user network and has strong protection capability; the failure recovery time is slow, the Bypass is not supported, and the domain name or the address needs to be mapped to the original server again during recovery; the mode is applied to complex environments, such as environments in which devices cannot be directly connected in series; when accessing, firstly accessing the service port address configured by the imperial WAF; support VRRP master and slave; the WAF adopts a reverse proxy mode to access the network environment in a bypass mode, a policy routing PBR is needed to be made on a core switch, the flow of a client access server is pulled to the WAF, and the next hop address of the policy routing is the service port address of the WAF. By-passable deployment, opaque to the user network; the failure recovery time is slow, bypass is not supported, and the router strategy routing configuration is required to be deleted during recovery; the mode is applied to complex environments, such as environments in which devices cannot be directly connected in series; still visiting the website server when visiting; and the VRRP master and slave are supported. And a bypass monitoring mode is adopted, a server port mirror image is made on the switch, the flow is copied to the Min WAF, and the online service is not influenced during deployment. In bypass mode the WAF will only alarm and not block. The transparent bridge mode is pure transparent in the true sense, does not change any content of the changed data packet, such as a source port and a TCP sequence number, does not track a TCP session, and can support a routing asymmetric environment. In the dual-machine HA mode, the WAFs operate in an Active, standby mode, that is, one of the WAFs is in a detection protection mode, and the other WAF is in a Standby mode, and when a link connected to one of the WAFs or the WAF itself fails, the Standby WAF negotiates to enter the detection protection mode. The WAF negotiates the main-standby relation through a VRRP protocol under a reverse proxy, only the host works under normal conditions, the standby machine does not work, and when the WAF host has problems, the standby machine is automatically switched to the host to work.

Fig. 9 is a schematic block diagram of a data intelligent management apparatus 300 according to an embodiment of the present invention. As shown in fig. 9, the present invention also provides a data intelligent management device 300 corresponding to the above data intelligent management method. The intelligent management device 300 includes a unit for executing the intelligent management method of data, and the device may be configured in a server. Specifically, referring to fig. 9, the intelligent data management device 300 includes a total data acquisition unit 301, a processing unit 302, and a sending unit 303.

A total data acquiring unit 301, configured to acquire index data of a hospital service system and input index data to obtain total index data; a processing unit 302, configured to process the total index data to obtain a processing result; a sending unit 303, configured to send the processing result to a terminal, so as to display the processing result on the terminal.

In one embodiment, as shown in fig. 10, the total data obtaining unit 301 includes a warehouse building subunit 3011, a loading subunit 3012, a logging subunit 3013, and a reading subunit 3014.

A warehouse building subunit 3011 configured to build a data warehouse; a loading subunit 3012, configured to load, to the data warehouse, index data of the hospital business system through the ETL; the input subunit 3013 is configured to input index data to the data warehouse; and a reading subunit 3014, configured to read the index data in the data warehouse to obtain total index data.

In one embodiment, as shown in fig. 11, the processing unit 302 includes a filtering subunit 3021, a summarizing subunit 3022, and a forwarding subunit 3023.

A filtering subunit 3021, configured to perform data screening and filtering on the total index data to obtain a filtering result; a summarizing subunit 3022, configured to perform data grouping and summarizing on the filtering result to obtain a summarizing result; and a row-turning subunit 3023, configured to perform row-column data turning on the summary result to obtain a processing result.

In an embodiment, the sending unit 303 is configured to send the processing result to a terminal, so as to display the processing result in a data icon visualization manner on the terminal.

Fig. 12 is a schematic block diagram of a data intelligent management device 300 according to another embodiment of the present invention. As shown in fig. 12, the intelligent data management device 300 of the present embodiment is added with an online protection unit 304 on the basis of the above embodiments.

And the online protection unit 304 is configured to perform online protection on the total index data in different environments by adopting a manner of combining multiple data protection technologies based on different protection security levels of the total index data by the front-end production system.

In an embodiment, referring to fig. 13, the online protection unit 304 includes a disaster recovery system construction subunit 3041, a verification subunit 3042, and a remote establishment subunit 3043.

A disaster recovery system construction subunit 3041, configured to construct a set of disaster recovery systems in a local information data center, so as to perform a local disaster recovery center for the total index data; and an authentication subunit 3042, configured to authenticate or receive a service of the local data center using the data in the disaster-backup storage pool. A remote establishing subunit 3043, configured to establish a remote disaster recovery system, so as to perform multipoint disaster recovery on the total index data.

It should be noted that, as can be clearly understood by those skilled in the art, the detailed implementation process of the intelligent data management device 300 and each unit can refer to the corresponding description in the foregoing method embodiments, and for convenience and brevity of description, no further description is provided herein.

The intelligent data management device 300 may be implemented in the form of a computer program that can run on a computer device as shown in fig. 14.

Referring to fig. 14, fig. 14 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of a plurality of servers.

Referring to fig. 14, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.

The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer programs 5032 include program instructions that, when executed, cause the processor 502 to perform a method for intelligent management of data.

The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.

The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 can execute a data intelligent management method.

The network interface 505 is used for network communication with other devices. Those skilled in the art will appreciate that the configuration shown in fig. 14 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation of the computer device 500 to which the present application is applied, and that a particular computer device 500 may include more or less components than those shown, or combine certain components, or have a different arrangement of components.

Wherein the processor 502 is configured to run the computer program 5032 stored in the memory to implement the following steps:

acquiring index data of a hospital service system and input index data to obtain total index data; processing the index total data to obtain a processing result; and sending the processing result to a terminal so as to display the processing result at the terminal.

In an embodiment, when the processor 502 implements the step of acquiring the index data of the hospital service system and the entered index data to obtain total index data, the following steps are specifically implemented:

building a data warehouse; loading index data of the hospital business system to a data warehouse through the ETL; inputting index data into a data warehouse; and reading the index data in the data warehouse to obtain total index data.

In an embodiment, when implementing the step of processing the total index data to obtain a processing result, the processor 502 specifically implements the following steps:

screening and filtering the total index data to obtain a filtering result; performing data grouping and summarization on the filtering results to obtain a summarization result; and carrying out data row-column rotation on the summary result to obtain a processing result.

In an embodiment, when the processor 502 implements the step of sending the processing result to the terminal, so as to display the processing result at the terminal, the following steps are specifically implemented:

and sending the processing result to a terminal so as to display the processing result in a data icon visualization mode at the terminal.

In an embodiment, after the step of sending the processing result to the terminal to display the processing result at the terminal, the processor 502 further implements the following steps:

and on the basis of different protection safety levels of the front-end production system on the total index data, online protection is performed on the total index data in different environments in a mode of combining multiple data protection technologies.

In an embodiment, when the processor 502 implements that the total index data based on the front-end production system has different protection security levels, and performs an online protection step on the total index data in different environments by using a combination of multiple data protection technologies, the following steps are specifically implemented:

a set of disaster recovery system is built in a local information data center to carry out a local disaster recovery center of the index total data; using the data in the disaster recovery storage pool to verify or connect with the service of the local data center; and establishing a remote disaster recovery system to perform multi-point disaster recovery of the index total data.

It should be understood that, in the embodiment of the present application, the processor 502 may be a Central Processing Unit (CPU), and the processor 502 may also be other general-purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

It will be understood by those skilled in the art that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing relevant hardware. The computer program includes program instructions, and the computer program may be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.

Accordingly, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program, when executed by a processor, causes the processor to perform the steps of:

acquiring index data of a hospital service system and input index data to obtain total index data; processing the index total data to obtain a processing result; and sending the processing result to a terminal so as to display the processing result at the terminal.

In an embodiment, when the processor executes the computer program to implement the step of acquiring the index data of the hospital service system and the entered index data to obtain total index data, the following steps are specifically implemented:

building a data warehouse; loading index data of the hospital business system to a data warehouse through an ETL (extract transform load); inputting index data to a data warehouse; and reading the index data in the data warehouse to obtain total index data.

In an embodiment, when the processor executes the computer program to implement the step of processing the index total data to obtain a processing result, the processor specifically implements the following steps:

screening and filtering the total index data to obtain a filtering result; performing data grouping and summarization on the filtering results to obtain a summarization result; and carrying out data row-column rotation on the summarized result to obtain a processing result.

In an embodiment, the processor implements the sending of the processing result to the terminal by executing the computer program, so that when the terminal displays the processing result, the following steps are implemented:

and sending the processing result to a terminal so as to display the processing result in a data icon visualization mode at the terminal.

In an embodiment, the processor, after executing the computer program to send the processing result to the terminal, further implements the following steps after the step of displaying the processing result by the terminal:

and on the basis of different protection safety levels of the front-end production system on the total index data, online protection is performed on the total index data in different environments in a mode of combining multiple data protection technologies.

In an embodiment, the processor executes the computer program to realize that the front-end production system-based data has different protection security levels for the total index data, and performs online protection for the total index data in different environments by combining a plurality of data protection technologies. When the steps are carried out, the following steps are concretely realized:

building a set of disaster recovery system in a local information data center to perform a local disaster recovery center of the index total data; using the data in the disaster recovery storage pool to verify or connect with the service of the local data center; and establishing a remote disaster recovery system to perform multi-point disaster recovery of the index total data.

The storage medium may be a usb disk, a removable hard disk, a Read-only memory (ROM), a magnetic disk or an optical disk, and various computer readable storage media that can store program codes.

Those of ordinary skill in the art will appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.

The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.

While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. The intelligent data management method is characterized by comprising the following steps:

acquiring index data of a hospital service system and input index data to obtain total index data;

processing the index total data to obtain a processing result;

and sending the processing result to a terminal so as to display the processing result at the terminal.

2. The intelligent data management method according to claim 1, wherein the acquiring of index data of hospital business system and the entered index data to obtain total index data comprises:

building a data warehouse;

loading index data of the hospital business system to a data warehouse through the ETL;

inputting index data to a data warehouse;

and reading the index data in the data warehouse to obtain total index data.

3. The intelligent data management method according to claim 2, wherein the processing of the total index data to obtain a processing result comprises:

carrying out data screening and filtering on the total index data to obtain a filtering result;

performing data grouping and summarization on the filtering results to obtain a summarization result;

and carrying out data row-column rotation on the summary result to obtain a processing result.

4. The intelligent data management method of claim 1, wherein the sending the processing result to a terminal for displaying the processing result at the terminal comprises:

and sending the processing result to a terminal so as to display the processing result in a data icon visualization mode at the terminal.

5. The intelligent data management method of claim 1, wherein the sending the processing result to the terminal for displaying the processing result further comprises:

and on the basis of different protection safety levels of the front-end production system on the total index data, performing online protection on the total index data in different environments by adopting a mode of combining multiple data protection technologies.

6. The intelligent data management method according to claim 5, wherein the front-end production system based on different protection security levels for the total index data adopts a combination of multiple data protection technologies to perform online protection for the total index data in different environments, and the method includes:

a set of disaster recovery system is built in a local information data center to carry out a local disaster recovery center of the index total data;

using the data in the disaster recovery storage pool to verify or connect with the service of the local data center;

and establishing a remote disaster recovery system to perform multipoint disaster recovery on the index total data.

7. Data wisdom management device, its characterized in that includes:

the system comprises a total data acquisition unit, a data processing unit and a data processing unit, wherein the total data acquisition unit is used for acquiring index data of a hospital service system and input index data so as to obtain total index data;

the processing unit is used for processing the index total data to obtain a processing result;

and the sending unit is used for sending the processing result to a terminal so as to display the processing result at the terminal.

8. The intelligent management device for data of claim 7, wherein the total data acquisition unit comprises:

the warehouse building subunit is used for building a data warehouse;

the loading subunit is used for loading the index data of the hospital service system to the data warehouse through the ETL;

the recording subunit is used for recording the index data to the data warehouse;

and the reading subunit is used for reading the index data in the data warehouse to obtain the total index data.

9. A computer device, characterized in that it comprises a memory, on which a computer program is stored, and a processor, which when executing the computer program, implements the method according to any one of claims 1 to 6.

10. A storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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