Optimization method and device for business data offline query process, equipment and medium

Abstract

The invention relates to the field of information technology and financial science and technology, and discloses a business data offline query process optimization method, device, equipment and medium, and the method comprises the steps: obtaining a business data offline query business, analyzing a to-be-optimized process of the offline query business, recognizing process characteristics, determining a transformation mode and a process priority, and then, carrying out the optimization of the to-be-optimized process of the offline query business; the method comprises the steps of determining offline configuration equipment based on priorities, detecting equipment configuration data to obtain real-time data, analyzing data interaction quality, understanding a process use condition and making a transformation strategy, partitioning a to-be-optimized process according to the strategy, determining a transformation sequence and a time window, monitoring a window state to construct an optimized transformation path, and identifying a transformation task and a key transformation point. And finally generating a flow transformation scheme. And the working efficiency and accuracy of business data query are improved.

Description

Technical Field

[0001] The present invention relates to the fields of intelligent decision-making and financial technology, and in particular to a method, device, equipment and medium for optimizing an offline query process of business data. Background Art

[0002] With the continuous expansion and increasing complexity of corporate business, offline query of business data (for example, offline query of corporate sales business data) plays a vital role in corporate decision-making, operation management, etc.

[0003] At present, the query methods involving business data mainly include online query and offline query. Online query usually has relatively mature systems and processes. For example, the internal management system of the enterprise provides data query function, and relevant staff can log in to the system to query and obtain results. However, there are many problems with offline query. Offline query has the characteristics of diverse query objects, complex query content, and large demand differences. In addition, the requirements of different departments and different business scenarios are different, and it is difficult to form a unified standard process and interface like online query. The entire offline query process often relies too much on manual operation, which not only leads to a waste of human resources, but also has problems such as low efficiency and difficulty in ensuring data accuracy. Therefore, there is an urgent need for an optimization method for the offline query process of business data to improve the efficiency and accuracy of business data query. Summary of the invention

[0004] The present invention provides a method, device, equipment and medium for optimizing an offline query process of business data, so as to improve the working efficiency and accuracy of business data query.

[0005] In a first aspect, a method for optimizing an offline query process of business data is provided, comprising:

[0006] Obtaining offline query services of business data, analyzing the process to be optimized corresponding to the offline query services, identifying process characteristics corresponding to the process to be optimized, analyzing the transformation mode corresponding to the offline query services based on the process characteristics, and determining the process priority corresponding to the process to be optimized according to the transformation mode;

[0007] Based on the process priority, determine the offline configuration device corresponding to the offline query service, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device;

[0008] Analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage;

[0009] Based on the process transformation strategy, the process to be optimized is divided into process blocks to obtain transformation process blocks, the transformation sequence corresponding to the transformation process blocks is analyzed, and based on the transformation sequence, the transformation time window corresponding to the transformation process blocks is constructed;

[0010] Monitor the window status corresponding to the transformation time window, construct an optimized transformation path for the offline query business during the transformation process based on the window status, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks during task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

[0011] In a second aspect, a device for optimizing an offline query process of business data is provided, comprising:

[0012] A priority module is used to obtain offline query services of business data, analyze the process to be optimized corresponding to the offline query services, identify the process characteristics corresponding to the process to be optimized, analyze the transformation mode corresponding to the offline query services based on the process characteristics, and determine the process priority corresponding to the process to be optimized according to the transformation mode;

[0013] A real-time monitoring module, used to determine the offline configuration device corresponding to the offline query service based on the process priority, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device;

[0014] A strategy formulation module, used to analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage;

[0015] A window construction module is used to divide the process to be optimized into blocks based on the process transformation strategy to obtain transformation process blocks, analyze the transformation sequence corresponding to the transformation process blocks, and construct a transformation time window corresponding to the transformation process blocks based on the transformation sequence;

[0016] A solution generation module is used to monitor the window status corresponding to the transformation time window, construct an optimized transformation path for the offline query business during the transformation process based on the window status, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks during task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

[0017] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the above-mentioned method for optimizing the offline query process of business data are implemented.

[0018] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the optimization method of the above-mentioned business data offline query process are implemented.

[0019] Compared with the problems described in the background technology, firstly, the present invention obtains offline query services of business data and analyzes the process to be optimized corresponding to the query services, which helps to fully understand the actual situation of offline query services, accurately discover problems and deficiencies in the current process, optimize the process in a targeted manner, improve query efficiency and accuracy, and reduce unnecessary waste of time and errors. Secondly, the present invention determines the offline configuration equipment corresponding to the offline business data based on the process priority, and can determine the equipment configuration according to the process priority. Limited funds and equipment resources can be invested in equipment corresponding to processes that are crucial to offline query services and have high priorities, thereby avoiding waste and unreasonable allocation of resources and ensuring that the equipment can meet the ever-changing offline query business needs. Next, the present invention can determine whether the equipment response time is too long, whether the operation is smooth, whether the feedback is timely and accurate, etc. by evaluating the interaction quality corresponding to the real-time data of the equipment, so as to optimize the offline query services in a targeted manner and make the offline query services more efficient and convenient. Furthermore, based on the process transformation strategy, the present invention divides the process to be optimized into process blocks to obtain transformation process blocks, which can more clearly understand and grasp the structure and composition of the entire process to be optimized, and can decompose the complex process into several relatively independent modules, so that the function and role of each module are clearer, which is convenient for in-depth analysis of the problems existing therein and determination of the specific transformation direction. Finally, by monitoring the window status corresponding to the transformation time window, the present invention can clearly understand whether each transformation process block is carried out as planned within the predetermined time window, so that measures can be taken quickly to make adjustments when the progress is lagging behind, so as to ensure that the entire offline query business process transformation project is completed on time. Therefore, the optimization method, device, equipment and medium of the offline query process of business data proposed by the present invention can improve the work efficiency and accuracy of business data query. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0021] Figure 1 It is a schematic diagram of an application environment of a method for optimizing an offline query process of business data in one embodiment of the present invention;

[0022] Figure 2 It is a flow chart of a method for optimizing a business data offline query process in one embodiment of the present invention;

[0023] Figure 3 It is a structural schematic diagram of a device for optimizing an offline query process of business data in one embodiment of the present invention;

[0024] Figure 4 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0025] Figure 5 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The optimization method for offline query process of business data provided by the embodiment of the present invention can be applied in the following aspects: Figure 1In an application environment, the client communicates with the server through a network. The server can obtain offline query services of business data through the client, analyze the process to be optimized corresponding to the offline query service, identify the process characteristics corresponding to the process to be optimized, analyze the transformation mode corresponding to the offline query service based on the process characteristics, and determine the process priority corresponding to the process to be optimized according to the transformation mode; determine the offline configuration device corresponding to the offline query service based on the process priority, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device; analyze the data interaction quality corresponding to the real-time data of the device, and analyze the process usage of the offline query service based on the data interaction quality. Based on the process usage, formulate a process transformation strategy corresponding to the offline query business; based on the process transformation strategy, divide the process to be optimized into blocks to obtain transformed process blocks, analyze the transformation sequence corresponding to the transformed process blocks, and construct a transformation time window corresponding to the transformed process blocks based on the transformation sequence; monitor the window status corresponding to the transformation time window, and based on the window status, construct an optimized transformation path for the offline query business in the transformation process, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks in task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

[0028] The client may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices. The server may be implemented by an independent server or a server cluster consisting of multiple servers. The present invention is described in detail below through specific embodiments.

[0029] See also Figure 2 As shown, Figure 2 A flow chart of a method for optimizing an offline query process of business data provided by an embodiment of the present invention includes the following steps:

[0030] S1. Obtain offline query services of business data, analyze the process to be optimized corresponding to the offline query services, identify the process characteristics corresponding to the process to be optimized, analyze the transformation mode corresponding to the offline query services based on the process characteristics, and determine the process priority corresponding to the process to be optimized according to the transformation mode.

[0031] The present invention obtains offline query services of business data and analyzes the process to be optimized corresponding to the offline query services, which helps to fully understand the actual situation of offline query business work, can accurately discover problems and deficiencies in the current process, and can optimize the process in a targeted manner, thereby improving the efficiency and accuracy of the query and reducing unnecessary waste of time and the occurrence of errors.

[0032] Among them, the business data refers to various information and data mainly related to the financial field, including but not limited to stock prices, bond yields, exchange rates, financial market transaction data, corporate financial statement data, business data of financial institutions, etc., which are of great value for financial decision-making, investment analysis, risk management, etc.; the offline query business refers to a business activity that queries business data in a traditional way in a non-network environment, for example, a customer goes to a business outlet of a financial institution and queries the business data he needs by communicating with the staff or using the query equipment in the business outlet; or the internal staff of the financial institution uses specific offline tools and channels to retrieve and analyze business data to support business decision-making and customer service, etc.; the process to be optimized refers to that, optionally, the offline query business of obtaining business data can be implemented by a data collection tool, such as: using professional data collection tools to digitize paper documents and records of judicial organs, and extract query business information from them; the analysis of the process to be optimized corresponding to the offline query business can be implemented by a data analysis tool, such as: using Excel, SPSS and other data analysis tools to perform data analysis, and discovering inefficient links in the process through statistical data.

[0033] Furthermore, by identifying the process characteristics corresponding to the process to be optimized, the present invention can provide an in-depth understanding of the nature and internal structure of the process, clearly grasp the characteristics, interrelationships and operating methods of each link in the process, and accurately locate the key nodes and potential problem areas in the process, providing a solid foundation for the targeted formulation of optimization strategies.

[0034] Among them, the process characteristics refer to a series of unique attributes and characteristics of the process to be optimized for offline query business, which include the complexity of the process, that is, the number of steps and links contained in the process and the complexity of the relationship between them; the efficiency of the process, such as the time required to complete the entire process, resource consumption and processing speed of each link; the accuracy of the process, which involves the accuracy of the process in data processing, information transmission, etc., and whether it is prone to errors or deviations; the flexibility of the process, that is, the ability of the process to adapt to different query requirements and changes in business scenarios; the controllability of the process, including the difficulty of monitoring, managing and adjusting the process; the continuity of the process, that is, whether the connection between each link is smooth, whether there is interruption or disconnection; and also include the characteristics of the personnel participation, data volume, degree of technology application, etc. involved in the process. Optionally, the identification of the process characteristics corresponding to the process to be optimized can be achieved through a process observation method, such as: conducting on-site observations of the process to be optimized for offline query business, recording the operation methods, time consumption, personnel interactions, etc. of each link, and summarizing the process characteristics.

[0035] Furthermore, the present invention analyzes the transformation mode corresponding to the offline query business based on the process characteristics, which can make the transformation work more accurate and targeted, so that different process characteristics require different transformation strategies. For example, for processes with low efficiency and cumbersome links, it may be appropriate to adopt an automated transformation mode to simplify the process and improve the processing speed; for processes with high accuracy requirements but prone to deviations, it may be necessary to strengthen the transformation of data verification and quality control links, so as to truly and effectively solve the problems in the existing process and improve the overall performance and quality of the offline query business.

[0036] Among them, the transformation mode refers to different types of improvement and transformation methods adopted for the offline query business process to be optimized, which covers multiple aspects such as adjustment of process structure, update of technology application, optimization of personnel allocation and change of management mode. It can include automation transformation mode, that is, by introducing advanced information technology and automation equipment, reducing manual intervention and improving the operation efficiency and accuracy of the process, such as using intelligent query system to automatically retrieve and filter relevant information; process optimization mode, focusing on simplifying, merging or reordering the links in the existing process to eliminate unnecessary cumbersome steps and repetitive operations, and improve the overall efficiency of the process; digital transformation mode, converting traditional paper documents and manual records into into electronic data, realizing rapid transmission and sharing of information, and facilitating data analysis and management; intelligent transformation mode, using artificial intelligence, big data analysis and other technologies to intelligently analyze and predict query services, provide support for decision-making, and improve the accuracy and foresight of offline queries; there is also a collaborative transformation mode, which emphasizes strengthening the collaboration and communication between different departments or institutions in the offline query business process, breaking down information barriers, realizing resource sharing and work collaboration, and improving overall work efficiency and quality. Optionally, the transformation mode corresponding to the analysis of the offline query business can be achieved through a decision matrix tool, such as: constructing a decision matrix, comparing and evaluating different transformation modes with process characteristics, and determining the optimal transformation mode.

[0037] Furthermore, the present invention determines the process priority corresponding to the process to be optimized according to the transformation mode, can clarify the importance of each process under different transformation modes, and can prioritize human, material and time resources to the processes that have the greatest impact on the overall offline query business and the most significant transformation effects, thereby avoiding the dispersion and waste of resources. Secondly, it helps to improve the efficiency and effectiveness of the transformation work.

[0038] The process priority refers to the order and importance level determined for each process to be optimized based on a comprehensive analysis of key transformation areas, priority considerations, correlation levels and key feature items.

[0039] As an embodiment of the present invention, determining the process priority corresponding to the process to be optimized based on the transformation pattern includes: analyzing the key transformation areas corresponding to the transformation pattern; determining the priority considerations corresponding to the key transformation areas; based on the priority considerations, evaluating the degree of association between the process to be optimized and the key transformation areas; based on the degree of association, extracting key feature items in the process to be optimized; based on the key feature items, determining the process priority corresponding to the process to be optimized.

[0040] Among them, the key transformation area refers to the specific process range or business field that is determined to be the need for improvement and optimization in the transformation model of offline query business. It can be some links that frequently have problems, are inefficient or have a greater impact on the overall offline query work, such as specific types of query business processing processes, key nodes for data transmission, etc.; the priority consideration factors refer to a series of standards and conditions used to evaluate the importance and urgency of the process to be optimized after determining the key transformation area. These factors may include the degree of impact of the process on offline fairness, the potential contribution to improving work efficiency, the resource input-output ratio, technical feasibility, etc.; the degree of association refers to the degree of close connection between the process to be optimized and the key transformation area, which can be measured through multiple aspects, such as business relevance, frequency of data interaction, process dependency, etc.; the key feature items refer to specific elements extracted from the process to be optimized that can reflect the essential characteristics and important attributes of the process. These feature items may include the complexity of the process, the type of key data involved, the departments or personnel involved, time sensitivity, etc.

[0041] Furthermore, the analysis of the key transformation areas corresponding to the transformation mode can be achieved through a process decomposition analysis method, such as: carefully decomposing the overall process of the offline query business, analyzing the importance and improvement potential of each link under different transformation modes, and determining its key transformation areas; the determination of the priority considerations corresponding to the key transformation areas can be achieved through a multi-factor analysis method, such as: comprehensively considering multiple factors, such as business needs, technical feasibility, cost-effectiveness, etc., to determine the priority considerations for the key transformation areas; the evaluation of the degree of association between the process to be optimized and the key transformation areas can be achieved through a process mapping method, such as: comparing and mapping the process to be optimized with the key transformation areas, analyzing the business relevance, data interaction relationship and process dependence between the two, and evaluating the degree of association; the extraction of key feature items in the process to be optimized can be achieved through a principal component analysis method, such as: analyzing multiple features in the process and extracting the main components as key feature items; the determination of the process priority corresponding to the process to be optimized can be achieved through a weighted scoring method, such as: weighted scoring is performed for each process to be optimized based on the key feature items and priority considerations to determine the process priority.

[0042] S2. Based on the process priority, determine the offline configuration device corresponding to the offline query service, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time device data.

[0043] The present invention determines the offline configuration equipment corresponding to the offline query business based on the process priority, and can determine the equipment configuration according to the process priority. Limited funds and equipment resources can be invested preferentially in the equipment corresponding to the processes that are crucial to the offline query business and have high priority, thereby avoiding waste and unreasonable allocation of resources and ensuring that the equipment can meet the ever-changing offline query business needs.

[0044] Among them, the offline configuration equipment refers to various physical hardware equipment and related auxiliary facilities used in offline query business work, including but not limited to servers and storage devices for data storage, such as hard disk arrays, tape libraries, etc., to ensure that the large amount of data required in the query process can be safely and stably stored and read; query terminal equipment, such as computers, special query workstations, etc., for financial staff to query and operate information; data acquisition equipment, such as scanners, card readers, etc., used to convert paper documents or other forms of information into electronic data for query processing; network connection equipment, such as routers, switches, etc., to ensure smooth communication between offline devices and with other related systems; security protection equipment, such as firewalls, encryption equipment, etc., to ensure data security and confidentiality during offline query business processes; and other auxiliary equipment such as printing equipment, UPS (uninterruptible power supply), etc. Optionally, the determination of the offline configuration equipment corresponding to the offline query business can be achieved through project management tools, such as: planning and managing offline query business projects through project management software, including determining the required offline configuration equipment.

[0045] Furthermore, by querying the device configuration data corresponding to the offline configuration device, the present invention can fully understand the performance status and operating parameters of the device, so as to better evaluate whether it meets the needs of offline query business work, accurately judge the ability of the device in processing a large number of query tasks, and promptly discover possible performance bottlenecks, providing a basis for optimizing the query process and adjusting resource allocation.

[0046] Among them, the device configuration data refers to information that describes various attributes and parameters of offline configuration devices, including hardware configuration information of the device, such as processor model, core number and frequency, memory capacity and type, storage device capacity and type (such as hard disk capacity, solid-state hard disk or mechanical hard disk, etc.), graphics card performance parameters, etc.; network configuration information, such as network interface type (such as Ethernet, wireless, etc.), IP address allocation, network bandwidth, etc.; operating system information, such as operating system version, installed software and drivers, etc.; device connection method and interface information, such as USB interface number and version, video output interface type, etc.; device security configuration information, such as whether a firewall, anti-virus software, encryption module, etc. are installed; and other specific attribute information of the device, such as the manufacturer of the device, production date, device serial number, etc. Optionally, the query of the device configuration data corresponding to the offline configuration device can be implemented through a device self-test method, such as: the device configuration data can be obtained by starting the device's self-test program.

[0047] The present invention obtains real-time data of the device by performing real-time detection on the device configuration data, and can timely grasp the operating status and performance of the device. By real-time monitoring of various configuration parameters of the device, such as CPU usage, memory occupancy, hard disk read and write speed, etc., it can quickly discover whether the device has performance bottlenecks or abnormal conditions, so as to take timely measures to optimize or repair, thereby ensuring the smooth progress of offline query business work.

[0048] Among them, the real-time equipment data refers to the detailed data content that can accurately reflect the current actual operation status of the equipment, which is obtained by real-time detection of equipment configuration data, comprehensive consideration of dynamic parameter information, parameter change trends, trend quantification indicators and real-time characteristics of the equipment, etc., including but not limited to the specific values ​​of various equipment parameters, description of the equipment's operating status, and warnings of possible problems.

[0049] As an embodiment of the present invention, the real-time detection of the device configuration data to obtain the real-time data of the device includes: collecting dynamic parameter information in the device configuration data; analyzing the parameter change trend corresponding to the dynamic parameter information; quantitatively evaluating the parameter change trend to obtain a trend quantification index; analyzing the real-time characteristics of the device corresponding to the trend quantification index; based on the real-time characteristics of the device, real-time detection of the device configuration data to obtain the real-time data of the device.

[0050] Among them, the dynamic parameter information refers to those parameter contents in the device configuration data that change with time, such as the device's CPU usage, memory occupancy, hard disk read and write speed, network bandwidth usage, and other data information that changes constantly at different times; the parameter change trend refers to the change direction and law of the dynamic parameter information over a period of time, such as whether the CPU usage of a certain device is gradually increasing, remaining stable, or gradually decreasing; the trend quantification index refers to a numerical index obtained by converting the parameter change trend through a specific quantification method, for example, the intensity and characteristics of the parameter change trend can be represented by numerical values ​​such as the rising slope and fluctuation amplitude; the real-time characteristics of the device refer to the specific feature description that can reflect the current operating status of the device after analyzing the trend quantification index, such as the characteristics of the device being in a high-load operating state, a low-load operating state, a stable operating state, etc.

[0051] Furthermore, the collection of dynamic parameter information in the device configuration data can be achieved through a timed sampling method, such as setting a fixed time interval to collect the device configuration data and obtain dynamic parameter information; the analysis of the parameter change trend corresponding to the dynamic parameter information can be achieved through a trend prediction algorithm, such as linear regression, polynomial regression and other algorithms, which can predict the trend of dynamic parameter information and analyze the future change trend of parameters; the quantitative evaluation of the parameter change trend can be achieved through a comprehensive scoring method, such as comprehensively evaluating the change trends of multiple parameters and giving an overall quantitative score; the analysis of the real-time characteristics of the device corresponding to the trend quantitative indicators can be achieved through data mining tools, such as Weka, RapidMiner, etc., which can conduct in-depth analysis of trend quantitative indicators and extract real-time characteristics of the device; the real-time detection of the device configuration data can be achieved through a real-time monitoring tool, such as using a real-time monitoring tool to monitor and alarm various configuration data of the device in real time.

[0052] S3. Analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage.

[0053] By analyzing the data interaction quality corresponding to the real-time data of the device, the present invention can determine whether the device response time is too long, whether the operation is smooth, whether the feedback is timely and accurate, etc., so as to perform targeted optimization and make offline query business work more efficient and convenient.

[0054] Among them, the data interaction quality refers to the overall level and effect of the device in the process of interacting with users or other systems, which comprehensively considers the performance of various interaction dimensions, including the device's response speed, stability, ease of use, user satisfaction and other aspects.

[0055] As an embodiment of the present invention, the analysis of the data interaction quality corresponding to the real-time data of the device includes: extracting key interaction parameters in the real-time data of the device; analyzing the interaction feature performance corresponding to the key interaction parameters; determining the interaction dimension corresponding to the real-time data of the device based on the interaction feature performance; querying the interaction weak links in the interaction dimension; and analyzing the data interaction quality corresponding to the real-time data of the device based on the interaction weak links.

[0056] Among them, the key interaction parameters refer to important parameters that can directly reflect the interaction between the device and the user or other systems in the real-time data of the device, such as the response time of the device, data transmission rate, convenience parameters of operation, etc.; the interaction characteristic performance refers to the specific characteristics and states presented by the key interaction parameters, such as a short response time for efficient interaction, a stable data transmission rate for reliability of interaction, etc.; the interaction dimension refers to different aspects and angles used to evaluate the quality of device interaction, which may include performance dimensions (such as speed, stability), usability dimensions (such as ease of operation, clarity of error prompts), user experience dimensions (such as interface friendliness, timeliness of feedback), etc.; the weak links in interaction refer to specific links or aspects that perform poorly in the interaction dimension and can affect the quality of interaction, such as large fluctuations in data transmission rate in the performance dimension, and complex operation procedures in the usability dimension.

[0057] Furthermore, the extraction of key interaction parameters in the real-time data of the device can be achieved through a correlation analysis method, such as: analyzing the correlation between each parameter in the real-time data of the device and the interaction behavior, and extracting parameters with higher correlation as key interaction parameters; the analysis of the interaction feature performance corresponding to the key interaction parameters can be achieved through data visualization tools, such as: Tableau, PowerBI, etc., to visualize the key interaction parameters for easy analysis of the interaction feature performance; the determination of the interaction dimension corresponding to the real-time data of the device can be achieved through a hierarchical analysis method, such as: decomposing the device interaction quality problem into factors at different levels, and determining the interaction dimension by comparing the importance of each factor; the query of the interaction weak link in the interaction dimension can be achieved through a gap analysis method, such as: comparing the actual performance of the device in each interaction dimension with the expected target, and finding the link with a larger gap as the interaction weak link; the analysis of the data interaction quality corresponding to the real-time data of the device can be achieved through a weighted scoring method, such as: assigning different weights to each dimension according to the importance of each interaction dimension, scoring the performance of the device in each dimension, and comprehensively calculating to obtain the interaction quality evaluation result.

[0058] The present invention analyzes the process usage of the offline query business based on the data interaction quality, and can accurately determine whether the interaction between the user and the query system is smooth and efficient, thereby revealing possible problems in the process, such as cumbersome operations, slow responses, etc., and providing a clear direction for targeted optimization of the process.

[0059] Among them, the process usage refers to the actual operating status and specific usage of each link in the offline query process, including the user's operation frequency and duration of different query steps, such as the time spent by the user in entering query conditions, browsing query results, and performing data screening; the resource usage of each node in the process, such as the memory usage and CPU occupancy of a specific query module; the user's behavior patterns at different process stages, such as whether certain operations are often repeated, whether a specific query path is preferred, etc.; and possible problems and bottlenecks in the process, such as which links are prone to error prompts, which steps have a long response time that affects the user experience, etc. Optionally, the analysis of the process usage of the offline query business can be achieved through a process tracking method, such as: tracking the entire process of offline query, and recording the execution status and time consumption of each link.

[0060] Furthermore, the present invention formulates a process transformation strategy corresponding to the offline query business based on the process usage, which can accurately understand which links have problems such as low efficiency, poor user experience or resource waste, thereby achieving optimal allocation of resources and improving resource utilization efficiency.

[0061] Among them, the process transformation strategy refers to a systematic and comprehensive plan and method formulated to achieve the overall optimization of the offline query business process, which includes the overall arrangement of transformation measures for each key process node, as well as clear implementation steps, time nodes and resource allocation.

[0062] As an embodiment of the present invention, the process transformation strategy corresponding to the offline query business is formulated based on the process usage, including: sorting out the key process nodes in the process usage; analyzing the operating efficiency indicators corresponding to the key process nodes; based on the operating efficiency indicators, determining the direction to be transformed corresponding to the process usage; based on the direction to be transformed, generating transformation measures corresponding to the process usage; based on the transformation measures, formulating a process transformation strategy corresponding to the offline query business.

[0063] Among them, the key process nodes refer to the links that play a key role in the offline query business process and have an important impact on the smooth operation and efficiency of the entire process, such as the query condition input link, data retrieval link, result display link, etc.; the operating efficiency index refers to the specific parameters used to measure the operating efficiency of key process nodes, such as query response time, data retrieval accuracy, result display speed, etc.; the direction to be transformed refers to the direction that needs to be improved and optimized based on the analysis of the operating efficiency indicators of key process nodes, such as improving query response speed, improving data retrieval accuracy, optimizing result display method, etc.; the transformation measures refer to the specific action plans proposed for the direction to be transformed, such as optimizing the query algorithm to shorten the query response time, updating the data retrieval engine to improve accuracy, and using more intuitive charts to display results.

[0064] Furthermore, the combing of the key process nodes in the process usage can be achieved through a process analysis method, such as: conducting a detailed analysis of the entire process of the offline query business, and finding out the links that have a greater impact on the process results, frequent user interactions or are prone to problems as key process nodes; the analysis of the operating efficiency indicators corresponding to the key process nodes can be achieved through a time measurement method, such as: measuring the execution time of key process nodes, such as query response time, result generation time, etc., as operating efficiency indicators; the determination of the direction to be transformed corresponding to the process usage can be achieved through a gap analysis method, such as: comparing the actual operating efficiency indicators of the key process nodes with the expected goals, and finding out the aspects with larger gaps as the direction to be transformed; the generation of transformation measures corresponding to the process usage can be achieved through a measure generation tool, such as: Ideaflip, Miro, etc.; the formulation of the process transformation strategy corresponding to the offline query business can be achieved through an overall planning method, such as: formulating a comprehensive process transformation strategy based on the overall goal of the offline query business.

[0065] S4. Based on the process transformation strategy, the process to be optimized is divided into process blocks to obtain transformation process blocks, the transformation sequence corresponding to the transformation process blocks is analyzed, and based on the transformation sequence, a transformation time window corresponding to the transformation process blocks is constructed.

[0066] Based on the process transformation strategy, the present invention divides the process to be optimized into blocks to obtain transformed process blocks, which can more clearly understand and grasp the structure and composition of the entire process to be optimized, and can decompose the complex process into several relatively independent modules, so that the function and role of each module are clearer, which is convenient for in-depth analysis of the problems existing therein and determination of the specific transformation direction.

[0067] The transformation process block refers to a relatively independent process unit obtained by dividing the offline query business process to be optimized into blocks based on the process transformation strategy. Each transformation process block has specific functions and goals, covering a series of operation steps and activities from input to output, which may include query condition input module, data retrieval processing module, result display and analysis module and other different parts. Optionally, the process block division of the process to be optimized can be achieved through functional analysis, such as: dividing into blocks according to different functions of the process to be optimized.

[0068] Furthermore, by analyzing the transformation sequence corresponding to the transformation process blocks, the present invention can first process those transformation process blocks that have a greater impact on the entire offline query business process and have more obvious bottlenecks, and can reasonably arrange resources such as human, material and time to ensure sufficient resource investment in key links and improve resource utilization efficiency.

[0069] Among them, the transformation order refers to the order followed when transforming the transformed process blocks obtained after dividing the offline query business's to-be-optimized process into blocks, which takes into account factors such as the importance of each transformed process block in the entire process, interdependence, and the difficulty of transformation. The transformation order can be from key process blocks to auxiliary process blocks, or it can be arranged from large to small according to the degree of impact on user experience, or it can be determined according to the urgency of the transformation and the availability of resources. Optionally, the analysis of the transformation order corresponding to the transformed process blocks can be achieved through an importance evaluation method, such as: evaluating the importance of each transformed process block to the overall offline query business process, and giving priority to the transformation of high-importance process blocks.

[0070] The present invention constructs a transformation time window corresponding to the transformation process block based on the transformation sequence, which can reasonably arrange the sequence of various transformation tasks, avoid conflicts and interferences between the transformation work of different process blocks, and ensure that the transformation of the entire offline query business process is carried out in an orderly manner. It can better plan the allocation of human, material and technical resources, ensure that resources are concentrated in the corresponding transformation process block at a specific time node, and avoid idleness and waste of resources.

[0071] The transformation time window refers to the specific time period during which the transformation can be performed for each transformation process block, which comprehensively considers factors such as preliminary time planning, resource availability, and the impact of other related work.

[0072] As an embodiment of the present invention, constructing a transformation time window corresponding to the transformation process block based on the transformation sequence includes: analyzing key transformation nodes in the transformation sequence; determining a priority process block corresponding to the transformation process block based on the key transformation nodes; evaluating a transformation coefficient corresponding to the priority process block; formulating a preliminary time plan corresponding to the transformation process block according to the transformation coefficient; and constructing a transformation time window corresponding to the transformation process block based on the preliminary time plan.

[0073] Among them, the key transformation nodes refer to the key links or steps that have a significant impact on the transformation sequence and determine the direction and progress of the transformation, such as those transformation points that play a key role in improving the performance of the entire offline query business process, involve core function adjustments or have complex dependencies; the priority process block refers to the transformation process block that needs to be given priority during the transformation process based on the key transformation nodes; the transformation coefficient refers to a comprehensive indicator used to evaluate the difficulty of transformation, resource requirements, risk level, etc. of the priority process block, which may include considerations of multiple dimensions such as technical difficulty coefficient, time consumption coefficient, and manpower requirement coefficient; the preliminary time plan refers to a preliminary time arrangement plan formulated for the transformation process block based on the transformation coefficient, including the estimated start time, duration and end time of each process block.

[0074] Furthermore, the analysis of the key transformation nodes in the transformation sequence can be achieved through an influencing factor analysis method, such as: analyzing the influencing factors of each transformation process block on the performance, efficiency, user experience, etc. of the offline query business process, and determining the node with greater influence as the key transformation node; the determination of the priority process block corresponding to the transformation process block can be achieved through a multi-criteria decision algorithm, such as: establishing multiple evaluation criteria, such as urgency, benefit, risk, etc., and comprehensively evaluating the transformation process block through a multi-criteria decision algorithm to determine the priority process block; the evaluation of the transformation coefficient corresponding to the priority process block can be achieved through a risk assessment tool, such as: RiskMatrix, FMEA and other tools; the formulation of the preliminary time plan corresponding to the transformation process block can be achieved through a workload estimation method, such as: estimating the workload of each process block based on the transformation tasks and resource requirements of the priority process block, and then formulating a preliminary time plan in combination with available resources and time constraints; the construction of the transformation time window corresponding to the transformation process block can be achieved through a time management tool, such as: Todoist, Toggl and other tools, which can help manage and allocate time resources and construct a transformation time window.

[0075] S5. Monitor the window status corresponding to the transformation time window, and based on the window status, construct an optimized transformation path for the offline query business during the transformation process, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks in task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

[0076] By monitoring the window status corresponding to the transformation time window, the present invention can clearly understand whether each transformation process block is carried out as planned within the predetermined time window, so as to take prompt measures to make adjustments when progress lags, thereby ensuring that the entire offline query business process transformation project is completed on time.

[0077] Among them, the window status refers to the actual situation and performance of the transformation time window within a specific time period, including the progress of the transformation process block within the time window, such as the amount of work completed, the remaining workload, and whether it is proceeding as planned; the use of resources, such as the degree of consumption and the remaining amount of human, material and time resources; possible risks and problems, such as the impact of technical difficulties, external interference, etc. on the transformation progress; and coordination with other related process blocks or projects, etc. Optionally, the monitoring of the window status corresponding to the transformation time window can be achieved through project management tools, such as Trello, Asana, etc., which can be used to track the progress of the transformation process block, record resource usage, and intuitively display the window status through dashboards, task lists, etc.

[0078] Furthermore, the present invention constructs an optimized transformation path for the offline query business during the transformation process based on the window status, and can accurately grasp the progress and existing problems of each transformation process block, so as to adjust the transformation strategy in a targeted manner, select the most optimized path to promote the transformation work, clearly understand the direction and focus of the transformation, better collaborate and improve overall work efficiency.

[0079] Among them, the optimized transformation path refers to the specific action plan and steps formulated in the offline query transformation process to achieve efficient transformation, including which process blocks to transform first, what technical means to adopt, how to reasonably allocate resources, etc., to ensure that the transformation work is carried out efficiently and orderly.

[0080] As an embodiment of the present invention, constructing an optimized transformation path for the offline query business in the transformation process based on the window status includes: querying the transformation progress corresponding to the window status; determining the state level of the offline query business in the current transformation process based on the transformation progress; calculating the feasibility index corresponding to the offline query business based on the state level; analyzing the transformation optimization conditions corresponding to the feasibility index; and constructing an optimized transformation path for the offline query business in the transformation process based on the transformation optimization conditions.

[0081] Among them, the transformation progress refers to the completion degree and time progress of each transformation process block in the offline query business transformation process, such as the number of completed process blocks, the completion ratio of the ongoing process blocks and the estimated remaining time; the status level refers to the division level of the current transformation process of the offline query business according to the transformation progress, which can be divided into different levels such as not started, early, mid-term, late, and nearly completed, reflecting the overall stage and urgency of the transformation; the feasibility index refers to a quantitative indicator used to measure the possibility and feasibility of efficient transformation of offline query business, which comprehensively considers factors such as resource availability, technical difficulty, time constraints, etc. The higher the value, the greater the feasibility of efficient transformation; the transformation optimization conditions refer to the specific requirements and conditions that need to be met to achieve efficient transformation of offline query business, such as specific technical solutions, resource allocation requirements, time node constraints, etc.

[0082] Furthermore, the query of the transformation progress corresponding to the window status can be achieved through a progress prediction algorithm, such as: based on historical data and current progress, using an algorithm to predict future transformation progress; the determination of the status level of the offline query business in the current transformation process can be achieved through a decision tree algorithm, such as: building a decision tree model, and determining the status level according to key indicators and stage goals; the calculation of the feasibility index corresponding to the offline query business can be achieved through a hierarchical analysis algorithm, such as: determining the weight of each factor through a hierarchical analysis algorithm, and then scoring each indicator to calculate the feasibility index; the analysis of the transformation optimization conditions corresponding to the feasibility index can be achieved through a gap analysis tool, such as: using a gap analysis tool to compare the current state with the target state to find out where the transformation optimization conditions are; the construction of an optimized transformation path for the offline query business in the transformation process can be achieved through a critical path optimization method, such as: determining the key process blocks and key tasks in the transformation process, and building an efficient transformation path by optimizing the task execution sequence and time schedule on the critical path.

[0083] By identifying the transformation tasks corresponding to the optimized transformation paths and analyzing the key transformation points of the transformation tasks in task execution, the present invention can perform resource allocation and time scheduling in a more targeted manner, avoid waste of resources and time delays, and ensure that the transformation work is done well in the core links, thereby improving the quality of the entire offline query business transformation.

[0084] Among them, the transformation task refers to the various work contents that need to be specifically performed according to the efficient transformation path during the offline query business transformation process, such as optimization of a specific database, redesign of the user interface, improvement of the query algorithm and other specific actions; the key transformation point refers to the important link or factor that plays a decisive role in the transformation effect and affects the overall transformation quality and progress during the execution of the specific transformation task. For example, in the database optimization task, the key transformation point may be the index establishment method, the adjustment of the data storage structure, etc.; in the user interface redesign task, the key transformation point may be the convenience of user operation, the clarity of information display, etc. Optionally, the identification of the transformation task corresponding to the optimization transformation path can be achieved through a process analysis method, such as: a detailed analysis of the existing process of offline query is performed to find out the bottlenecks and optimizable points in the process, and determine them as specific transformation tasks; the analysis of the key transformation points of the transformation task in the task execution can be achieved through a risk analysis method, such as: analyzing the risks that may be faced during the execution of the specific transformation task, and determining the links with higher risks as key transformation points.

[0085] Furthermore, the present invention generates a process transformation plan corresponding to the offline query business based on the key transformation points, which can concentrate resources and energy to prioritize these key links, thereby speeding up the entire transformation process, enabling the offline query business to enjoy the benefits of the transformation more quickly, improving the quality of the transformation, and fundamentally solving the bottleneck problems in the business process, thereby improving the overall business quality.

[0086] Among them, the process transformation plan refers to a series of specific improvement measures and action plans formulated for offline query business based on the identified key transformation points, which includes the adjustment, optimization or redesign of each link in the existing business process to improve the efficiency, accuracy and user experience of offline query business. The process transformation plan involves technical improvements, such as database optimization, algorithm upgrades, etc.; it may also include management adjustments, such as personnel configuration optimization, workflow standardization, etc. At the same time, the process transformation plan will also clarify the implementation steps, time nodes, responsible persons and required resources of each transformation measure. Optionally, the generation of the process transformation plan corresponding to the offline query business can be achieved through a solution generation tool, such as: Lucidchart, Miro and other tools.

[0087] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0088] In one embodiment, a device for optimizing an offline query process of business data is provided, and the device for optimizing an offline query process of business data corresponds to the method for optimizing an offline query process of business data in the above embodiment. Figure 3 As shown, the optimization device for offline query process of business data includes a priority module 201, a real-time monitoring module 202, a strategy formulation module 203, a window construction module 204 and a solution generation module 205. The detailed description of each functional module is as follows:

[0089] The priority module 201 is used to obtain offline query services of business data, analyze the process to be optimized corresponding to the offline query services, identify the process characteristics corresponding to the process to be optimized, analyze the transformation mode corresponding to the offline query services based on the process characteristics, and determine the process priority corresponding to the process to be optimized according to the transformation mode;

[0090] A real-time monitoring module 202 is used to determine the offline configuration device corresponding to the offline query service based on the process priority, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time device data;

[0091] A strategy formulation module 203 is used to analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage;

[0092] The window construction module 204 is used to divide the process to be optimized into blocks based on the process transformation strategy to obtain transformation process blocks, analyze the transformation sequence corresponding to the transformation process blocks, and construct the transformation time window corresponding to the transformation process blocks based on the transformation sequence;

[0093] The solution generation module 205 is used to monitor the window status corresponding to the transformation time window, and based on the window status, construct an optimized transformation path for the offline query business during the transformation process, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks in task execution, and generate a process transformation solution corresponding to the offline query business based on the key transformation points.

[0094] In one embodiment, the priority module 201 determines the process priority corresponding to the process to be optimized according to the transformation mode, including: analyzing the key transformation area corresponding to the transformation mode; determining the priority consideration factors corresponding to the key transformation area; based on the priority consideration factors, evaluating the degree of correlation between the process to be optimized and the key transformation area; based on the degree of correlation, extracting key feature items in the process to be optimized; based on the key feature items, determining the process priority corresponding to the process to be optimized.

[0095] In one embodiment, the real-time monitoring module 202 performs real-time detection of the device configuration data to obtain real-time data of the device, including: collecting dynamic parameter information in the device configuration data; analyzing the parameter change trend corresponding to the dynamic parameter information; quantitatively evaluating the parameter change trend to obtain a trend quantification index; analyzing the real-time characteristics of the device corresponding to the trend quantification index; based on the real-time characteristics of the device, performing real-time detection of the device configuration data to obtain real-time data of the device.

[0096] In one embodiment, the strategy formulation module 203 performs analysis on the data interaction quality corresponding to the real-time data of the device, including: extracting key interaction parameters in the real-time data of the device; analyzing the interaction feature performance corresponding to the key interaction parameters; determining the interaction dimension corresponding to the real-time data of the device based on the interaction feature performance; querying the interaction weak links in the interaction dimension; and analyzing the data interaction quality corresponding to the real-time data of the device based on the interaction weak links.

[0097] In one embodiment, the strategy formulation module 203 formulates a process transformation strategy corresponding to the offline query business based on the process usage, including: sorting out the key process nodes in the process usage; analyzing the operating efficiency indicators corresponding to the key process nodes; based on the operating efficiency indicators, determining the direction to be transformed corresponding to the process usage; based on the direction to be transformed, generating transformation measures corresponding to the process usage; based on the transformation measures, formulating a process transformation strategy corresponding to the offline query business.

[0098] In one embodiment, the window construction module 204 constructs a transformation time window corresponding to the transformation process block based on the transformation sequence, including: analyzing key transformation nodes in the transformation sequence; determining the priority process block corresponding to the transformation process block based on the key transformation nodes; evaluating the transformation coefficient corresponding to the priority process block; formulating a preliminary time plan corresponding to the transformation process block according to the transformation coefficient; and constructing a transformation time window corresponding to the transformation process block based on the preliminary time plan.

[0099] In one embodiment, the solution generation module 205 constructs an optimized transformation path for the offline query business during the transformation process based on the window state, including: querying the transformation progress corresponding to the window state; determining the state level of the offline query business in the current transformation process based on the transformation progress; calculating the feasibility index corresponding to the offline query business based on the state level; analyzing the transformation optimization conditions corresponding to the feasibility index; and constructing an optimized transformation path for the offline query business during the transformation process based on the transformation optimization conditions.

[0100] For the specific definition of the optimization device for the offline query process of business data, please refer to the definition of the optimization method for the offline query process of business data above, which will not be repeated here. Each module in the above-mentioned optimization device for the offline query process of business data can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0101] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, the functions or steps on the service side of a method for optimizing an offline query process for business data are implemented.

[0102] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, the client-side functions or steps of a method for optimizing an offline query process for business data are implemented.

[0103] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0104] Obtaining offline query services of business data, analyzing the process to be optimized corresponding to the offline query services, identifying process characteristics corresponding to the process to be optimized, analyzing the transformation mode corresponding to the offline query services based on the process characteristics, and determining the process priority corresponding to the process to be optimized according to the transformation mode;

[0105] Based on the process priority, determine the offline configuration device corresponding to the offline query service, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device;

[0106] Analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage;

[0107] Based on the process transformation strategy, the process to be optimized is divided into process blocks to obtain transformation process blocks, the transformation sequence corresponding to the transformation process blocks is analyzed, and based on the transformation sequence, the transformation time window corresponding to the transformation process blocks is constructed;

[0108] Monitor the window status corresponding to the transformation time window, construct an optimized transformation path for the offline query business during the transformation process based on the window status, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks during task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

[0109] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0110] Obtaining offline query services of business data, analyzing the process to be optimized corresponding to the offline query services, identifying process characteristics corresponding to the process to be optimized, analyzing the transformation mode corresponding to the offline query services based on the process characteristics, and determining the process priority corresponding to the process to be optimized according to the transformation mode;

[0111] Based on the process priority, determine the offline configuration device corresponding to the offline query service, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device;

[0112] Analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage;

[0113] Based on the process transformation strategy, the process to be optimized is divided into process blocks to obtain transformation process blocks, the transformation sequence corresponding to the transformation process blocks is analyzed, and based on the transformation sequence, the transformation time window corresponding to the transformation process blocks is constructed;

[0114] Monitor the window status corresponding to the transformation time window, construct an optimized transformation path for the offline query business during the transformation process based on the window status, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks during task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

[0115] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0116] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0117] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0118] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should be included in the protection scope of the present invention. It should be noted that if software tools or components other than those of the company appear in the embodiments of this application, they are only used for illustration and do not represent actual use.

Claims

1. A method for optimizing the offline query process of business data, characterized in that: include: Obtaining offline query services of business data, analyzing the process to be optimized corresponding to the offline query services, identifying process characteristics corresponding to the process to be optimized, analyzing the transformation mode corresponding to the offline query services based on the process characteristics, and determining the process priority corresponding to the process to be optimized according to the transformation mode; Based on the process priority, determine the offline configuration device corresponding to the offline query service, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device; Analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage; Based on the process transformation strategy, the process to be optimized is divided into process blocks to obtain transformation process blocks, the transformation sequence corresponding to the transformation process blocks is analyzed, and based on the transformation sequence, the transformation time window corresponding to the transformation process blocks is constructed; Monitor the window status corresponding to the transformation time window, construct an optimized transformation path for the offline query business during the transformation process based on the window status, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks during task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

2. The method for optimizing the offline query process of business data according to claim 1, characterized in that: Determining the process priority corresponding to the process to be optimized according to the transformation mode includes: Analyze the key transformation areas corresponding to the transformation mode; Determine the priority factors corresponding to the key areas of transformation; Based on the priority considerations, evaluate the degree of correlation between the process to be optimized and the key area of ​​transformation; Based on the degree of association, extract key feature items in the process to be optimized; Based on the key feature items, the process priority corresponding to the process to be optimized is determined.

3. The method for optimizing the offline query process of business data according to claim 1, characterized in that: The real-time detection of the device configuration data to obtain the real-time data of the device includes: Collecting dynamic parameter information in the device configuration data; Analyzing parameter change trends corresponding to the dynamic parameter information; Quantitatively evaluate the parameter change trend to obtain a trend quantitative index; Analyze the real-time characteristics of the equipment corresponding to the trend quantitative indicators; Based on the real-time characteristics of the device, the device configuration data is detected in real time to obtain real-time data of the device.

4. The method for optimizing the offline query process of business data according to claim 1, characterized in that: The analyzing the data interaction quality corresponding to the real-time data of the device includes: Extracting key interaction parameters from the real-time data of the device; Analyzing the interaction feature performance corresponding to the key interaction parameters; Determining an interaction dimension corresponding to the real-time data of the device based on the interaction feature performance; Querying the weak interaction links in the interaction dimension; Based on the weak links in the interaction, the data interaction quality corresponding to the real-time data of the device is analyzed.

5. The method for optimizing the offline query process of business data according to claim 1, characterized in that: The process transformation strategy corresponding to the offline query service is formulated based on the process usage, including: Sorting out the key process nodes in the usage of the process; Analyze the operating efficiency indicators corresponding to the key process nodes; Based on the operation efficiency index, determine the direction to be transformed corresponding to the process usage; Based on the direction to be transformed, generating transformation measures corresponding to the process usage; Based on the transformation measures, a process transformation strategy corresponding to the offline query business is formulated.

6. The method for optimizing the offline query process of business data according to claim 1, characterized in that: The step of constructing a transformation time window corresponding to the transformation process block based on the transformation sequence includes: Analyzing key transformation nodes in the transformation sequence; Based on the key transformation node, determining a priority process block corresponding to the transformation process block; Evaluating the transformation coefficient corresponding to the priority flow block; According to the transformation coefficient, formulate a preliminary time plan corresponding to the transformation process block; Based on the preliminary time plan, a transformation time window corresponding to the transformation process block is constructed.

7. The method for optimizing the offline query process of business data according to claim 1, characterized in that: The step of constructing an optimization transformation path for the offline query service during the transformation process based on the window state includes: Query the transformation progress corresponding to the window status; Based on the transformation progress, determining a status level of the offline query service in the current transformation process; Based on the status level, calculating a feasibility index corresponding to the offline query service; Analyze the transformation optimization conditions corresponding to the feasibility index; Based on the transformation optimization conditions, an optimization transformation path for the offline query service during the transformation process is constructed.

8. A device for optimizing the offline query process of business data, characterized in that: include: A priority module is used to obtain offline query services of business data, analyze the process to be optimized corresponding to the offline query services, identify the process characteristics corresponding to the process to be optimized, analyze the transformation mode corresponding to the offline query services based on the process characteristics, and determine the process priority corresponding to the process to be optimized according to the transformation mode; A real-time monitoring module, used to determine the offline configuration device corresponding to the offline query service based on the process priority, query the device configuration data corresponding to the offline configuration device, perform real-time detection on the device configuration data, and obtain real-time data of the device; A strategy formulation module, used to analyze the data interaction quality corresponding to the real-time data of the device, analyze the process usage of the offline query service based on the data interaction quality, and formulate a process transformation strategy corresponding to the offline query service based on the process usage; A window construction module is used to divide the process to be optimized into blocks based on the process transformation strategy to obtain transformation process blocks, analyze the transformation sequence corresponding to the transformation process blocks, and construct a transformation time window corresponding to the transformation process blocks based on the transformation sequence; A solution generation module is used to monitor the window status corresponding to the transformation time window, construct an optimized transformation path for the offline query business during the transformation process based on the window status, identify the transformation tasks corresponding to the optimized transformation path, analyze the key transformation points of the transformation tasks during task execution, and generate a process transformation plan corresponding to the offline query business based on the key transformation points.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for optimizing the offline query process of business data as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for optimizing the offline query process of business data as described in any one of claims 1 to 7 are implemented.

Images