CN115203277B

CN115203277B - Data decision method and device

Info

Publication number: CN115203277B
Application number: CN202211133657.6A
Authority: CN
Inventors: 董宁
Original assignee: Beijing Biyingte Information Technology Co ltd
Current assignee: Beijing Biyingte Information Technology Co ltd
Priority date: 2022-09-19
Filing date: 2022-09-19
Publication date: 2023-01-06
Anticipated expiration: 2042-09-19
Also published as: CN115203277A

Abstract

The disclosure provides a data decision method and device. The method comprises the following steps: acquiring a data conversion link relation graph between a data source and a data target address; acquiring mapping logic between a data result and a data display index; acquiring a data index blood margin guide map according to the data conversion link relation map and the mapping logic; selecting a data analysis model according to the business mode; determining risk information through a data analysis model and a data display index; and determining business improvement information according to the data index blood margin map and the risk information. According to the method and the device, data tracing can be performed through the data index blood margin map, maintenance is not needed, analysis processing is performed through a What-If analysis function in an Excel-like analysis mode, and the learning cost of business analysts is reduced. And relatively fixed business operation can be specified in an RPA mode, and the operation can be automatically completed through a robot, so that the operation problem caused by manual operation is reduced to the maximum extent.

Description

Data decision method and device

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a data decision method and apparatus.

Background

In the related technology, an enterprise can collect various business data, form an enterprise data asset directory list through business analysis, and design a data warehouse through an ETL tool or a data script of the data warehouse. However, when data is changed, the ETL process or script code needs to be adjusted, and the change cannot be responded to quickly. And the visualized contents such as an analysis report and a management cockpit are designed and developed according to business requirements, so that the subsequent behaviors of the user cannot be effectively monitored, and the data visualization effect is difficult to evaluate. In addition, at present, most of the warning is carried out in the process of configuring an index threshold, but due to rapid service change and timeliness of information touch, service departments cannot avoid all risks, and the warning effect is limited. In the aspect of use scenes, at present, enterprises are limited by the communication construction of data closed loops, data analysis is mainly carried out based on independent scenes, and the use scenes are limited.

The information disclosed in this background section is only for enhancement of understanding of the general background of the application and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

Disclosure of Invention

The embodiment of the disclosure provides a data decision method and device, which can trace the source of data through a data index blood margin map without maintenance, and perform analysis processing through a What-If analysis function in an Excel-like analysis mode, thereby reducing the learning cost of business analysts. And relatively fixed business operation can be standardized in an RPA mode, and is automatically completed through a robot, so that the operation problems caused by manual operation are reduced to the maximum extent, the strategy and the business portrait can be continuously saved and perfected, and the accuracy and the effectiveness of strategy and business risk coping are improved. And the information of circulation can be combined with the information communication mode in an enterprise, so that the information and the strategy can be conveniently conveyed, and the execution efficiency is improved.

In a first aspect of the embodiments of the present disclosure, a data decision method is provided, including:

acquiring a data conversion link relation graph between a data source and a data target address;

acquiring mapping logic between a data result and a data display index, wherein the data result is an operation result of data stored in a data target address;

acquiring a data index blood margin map according to the data conversion link relation map and the mapping logic;

selecting a data analysis model according to the business mode;

determining risk information through the data analysis model and the data display index;

and determining business improvement information according to the data index blood margin map and the risk information.

According to an embodiment of the present disclosure, the method further comprises:

and according to the historical data, the historical service mode and the historical operation result, establishing a data analysis model through a model establishing tool.

According to the embodiment of the disclosure, determining risk information through the data analysis model and the data presentation index includes:

processing the data display index through a What-If analysis function to obtain an analysis result;

and processing the analysis result through the data analysis model to obtain the risk information.

According to the embodiment of the disclosure, determining business improvement information according to the data index leading edge map and the risk information comprises:

determining a data source corresponding to risk information according to the data index blood margin map;

and determining service improvement information according to the risk information and the data source.

and performing sand table deduction on the data source according to the service improvement information to obtain a prediction improvement result.

and executing the service improvement information on the data source in a PRA mode under the condition that the predicted improvement result meets the improvement requirement.

and under the condition that the predicted improvement result meets the improvement requirement, storing the service improvement information into a strategy library.

In a second aspect of the embodiments of the present disclosure, a data decision apparatus is provided, including:

the relational graph module is used for acquiring a data conversion link relational graph from a data source to a data destination address;

the mapping module is used for acquiring mapping logic from a data result to a data display index, wherein the data result is an operation result of data stored in a data target address;

the map guiding module is used for acquiring a data index blood margin map according to the data conversion link relation map and the mapping logic;

the model module is used for selecting a data analysis model according to the business mode;

the risk module is used for determining risk information through the data analysis model and the data display index;

and the improvement module is used for determining service improvement information according to the data index blood margin map and the risk information.

According to an embodiment of the present disclosure, the apparatus is further configured to: and according to the historical data, the historical service mode and the historical operation result, establishing a data analysis model through a model establishing tool.

According to an embodiment of the present disclosure, the risk module is further to: processing the data display index through a What-If analysis function to obtain an analysis result; and processing the analysis result through the data analysis model to obtain the risk information.

According to an embodiment of the disclosure, the improvement module is further to: determining a data source corresponding to risk information according to the data index blood margin map; and determining service improvement information according to the risk information and the data source.

According to an embodiment of the present disclosure, the apparatus is further configured to: and performing sand table deduction on the data source according to the service improvement information to obtain a prediction improvement result.

According to an embodiment of the present disclosure, the apparatus is further configured to: and executing the service improvement information on the data source in a PRA mode under the condition that the predicted improvement result meets the improvement requirement.

According to an embodiment of the present disclosure, the apparatus is further configured to: and under the condition that the predicted improvement result meets the improvement requirement, storing the service improvement information to a strategy library.

In a third aspect of the embodiments of the present disclosure, a device for decision making using data is provided, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

In a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions, when executed by a processor, implement the above method.

Drawings

FIG. 1 schematically illustrates a flow diagram of a data decision method of an embodiment of the present disclosure;

fig. 2 schematically illustrates an application case diagram of a data decision method according to an embodiment of the present disclosure;

fig. 3 schematically illustrates a risk information analysis flow of an embodiment of the present disclosure;

FIG. 4 schematically illustrates a block diagram of a data decision device in accordance with an embodiment of the present disclosure;

FIG. 5 is a block diagram illustrating a data decision device in accordance with an exemplary embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present disclosure and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein.

It should be understood that, in various embodiments of the present disclosure, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the inherent logic of the processes, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

It should be understood that in the present disclosure, "including" and "having" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be understood that in the present disclosure, "plurality" means two or more. "and/or" is merely an association relationship describing an associated object, meaning that there may be three relationships, for example, and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "comprising a, B and C", "comprising a, B, C" means that all three of a, B, C are comprised, "comprising a, B or C" means comprising one of a, B, C, "comprising a, B and/or C" means comprising any 1 or any 2 or 3 of a, B, C.

It should be understood that in this disclosure, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, from which B can be determined. Determining B from a does not mean determining B from a alone, but may be determined from a and/or other information. And the matching of A and B means that the similarity of A and B is greater than or equal to a preset threshold value.

As used herein, the term "if" may be interpreted as "at \8230; …" or "in response to a determination" or "in response to a detection" depending on the context.

The technical solution of the present disclosure is explained in detail with specific examples below. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.

Fig. 1 exemplarily shows a flow diagram of a data decision method according to an embodiment of the present disclosure, as shown in fig. 1, the method includes:

step S101, acquiring a data conversion link relation graph between a data source and a data destination address;

step S102, obtaining mapping logic between a data result and a data display index, wherein the data result is an operation result of data stored in a data target address;

step S103, acquiring a data index blood vessel map according to the data conversion link relation map and the mapping logic;

step S104, selecting a data analysis model according to the business mode;

step S105, determining risk information through the data analysis model and the data display index;

and step S106, determining service improvement information according to the data index blood margin map and the risk information.

According to the embodiment of the disclosure, in daily operation of an enterprise, various service data can be collected, and statistics, analysis and display can be performed on the service data, and the service condition represented by the service data can be determined. Business data may include market data, sales data, financial data, human data, and the like. The present disclosure does not limit the type of traffic data.

According to the embodiment of the disclosure, in order to facilitate management and analysis of business data, a data index blood source guide graph can be obtained and used for tracing a data source when risk occurs in an operation business, so that a business causing the risk is determined, and business analysis is facilitated.

According to an embodiment of the present disclosure, in step S101, a data conversion link relation graph between a data source to a data destination address may be acquired. That is, in the data collection process, the data source for obtaining the data may include a source of daily business data, for example, sales data filled by a salesperson, sales data collected in an office system, and the like, which is not limited by the present disclosure. When the business data is collected, the data sources may be summarized to the target address, for example, into a table for summarizing statistics, and in the process of summarizing, a data conversion link relation graph, that is, a graph for determining a link relation between the data sources and the target address may be determined, and may be used for processing such as tracing the data sources.

According to the embodiment of the disclosure, in step S102, mapping logic between data results and data presentation indicators is obtained. After the summary analysis, a data result may be obtained, for example, after the sales data is summarized, a data result such as a total sales amount may be obtained, when the sales data is displayed, the data may be displayed according to a certain logical relationship, for example, when the sales amount is greater than a certain value, the sales data may be displayed in a certain mode, otherwise, when the sales amount is less than the certain value, the data may be displayed in another mode, that is, a mapping logic may exist between the data result and the data display, and the data result may be displayed through the mapping logic. The mapping logic may be obtained for ease of data management and traceability.

According to the embodiment of the disclosure, in step S103, a data index blood margin map can be obtained based on the obtained data conversion link relation map and mapping logic, so that when an index display service is abnormal or risky, a data source can be traced quickly, management and improvement on risks and abnormalities are facilitated, a service risk can be responded quickly, and risks can be managed and controlled quickly. And the data index blood margin map is automatically generated based on the data conversion link relation map and the mapping logic, so that the real-time performance is high, the creation and maintenance are not needed, and the use convenience is high.

Fig. 2 schematically illustrates an application case diagram of the data decision method according to the embodiment of the present disclosure.

According to the embodiment of the disclosure, after the data index blood vessel map is obtained, the data display index can be analyzed, so that the business risk can be determined.

According to an embodiment of the present disclosure, in analyzing business risk, a data analysis model may be used, the method further comprising: and according to the historical data, the historical business mode and the historical operation result, constructing a data analysis model through a model construction tool.

According to an embodiment of the present disclosure, the data analysis model may include multiple types, for example, a classification model, a decision model, and the like, which are combined with the business data, and the basis of the model may be a neural network model, a bayesian model, a regression model, a decision tree model, a support vector machine model, and the like.

According to embodiments of the present disclosure, a data analysis model may be constructed based on historical data, historical business patterns, and historical business results using a model construction tool, e.g., trained by historical data, historical business patterns, and historical business results, such that the data analysis model obtains the ability to determine risk information based on the data results. Further, the data analysis model can be saved to the model library so as to be reusable, and different models can correspond to different application scenarios, for example, a model for processing sales data can be used for analyzing risk information in the sales process, and a model for processing budget data can be used for analyzing risk information in the budget data. A data analysis model may be selected in step S104.

According to the embodiment of the disclosure, data display indexes can be visualized, for example, an analysis report is output, or a component data display cabin and the like, and meanwhile, analysis can be performed through a data analysis model.

According to an embodiment of the present disclosure, step S105 may include: processing the data display index through a What-If analysis function to obtain an analysis result; and processing the analysis result through the data analysis model to obtain the risk information.

Fig. 3 schematically illustrates a risk information analysis flow of an embodiment of the present disclosure. The data display indexes can be processed through excel-like What-If analysis functions to obtain analysis results, and the analysis results can be stored and reported.

According to the embodiment of the present disclosure, the analysis result may be processed through the above determined data analysis model, and risk information existing in the analysis result, for example, sales of a certain product is decreased, budget of a certain department is over-rated, and the like, is determined. The risk information can be reported, and after the processing strategy of the risk information is subsequently determined, the processing strategy can be stored in the database, so that the similar strategy can be repeatedly used when similar risk information is encountered subsequently.

According to an embodiment of the present disclosure, in step S106, determining service improvement information, step S106 may include: determining a data source corresponding to the risk information according to the data index blood margin map; and determining service improvement information according to the risk information and the data source.

According to the embodiment of the disclosure, the service improvement information is information required by a processing strategy for risk information, the processing strategy can be executed according to the service improvement information, and the processing strategy can be displayed through the decision signboard.

According to an embodiment of the present disclosure, the method further comprises: and performing sand table deduction on the data source according to the service improvement information to obtain a prediction improvement result. In the deduction process, action feedback may be obtained, for example, in simulating execution of a processing strategy, changes in data sources may be determined, action feedback may be obtained, and thus a prediction improvement result, i.e., whether risk information has been controlled, etc., may be determined.

According to an embodiment of the present disclosure, the method further comprises: and under the condition that the predicted improvement result meets the improvement requirement, storing the service improvement information into a strategy library. The established strategies can be stored in a strategy library, so that similar strategies are configured for risks when similar risks are encountered subsequently, and the risks are responded.

According to an embodiment of the present disclosure, the method further comprises: and executing the service improvement information on the data source in a PRA mode under the condition that the predicted improvement result meets the improvement requirement. And if the predicted improvement result meets the improvement requirement, executing the strategy on the data source in a PRA mode. And the actual improved effect can be determined.

According to the embodiment of the disclosure, the solidified and standard business operation content can be abstracted according to the strategy, and the RPA automatically completes the business operation, thereby realizing the automatic processing of the data flow.

According to the embodiment of the disclosure, in summary, in operation, the enterprise operation risk can be controlled based on the threshold value setting of the business key index (for example, the preset data source or data result with key function). And the effect evaluation is carried out on the service behavior of the risk handling of the user through sand table deduction, the optimal service improvement direction is intelligently predicted, and the service risk is avoided. And the high-efficiency circulation of the enterprise information data is completed and the business data closed loop is formed by combining the existing information interaction tools of the enterprise and realizing the circulation configuration of different contents among the data tools.

In an example, business processes can be managed through tagging and a business representation can be generated. When risk information appears, data simulation prediction is carried out on the improvement result of the service portrait through a sand table deduction tool, machine learning is assisted to continuously improve portrait accuracy, corresponding strategies are output according to different portrait characteristics, and the service improvement result is deduced through the strategies. And the service portrait and the strategy can be stored and can be continuously improved so as to more accurately and effectively deal with risks in subsequent operation. A standard template can be set for the management of a certain business portrait and a risk coping strategy, and in the process of coping with risk information, the standard template can be selected through the corresponding relation of the risk information and a data source, so that business operation is automatically completed through an RPA (remote procedure administration platform), and the coping of risks is realized. And, in the standard template, the parameter is adjustable, for example, in the coping strategy, the coping strength can be properly adjusted, for example, when coping with the risk of sales data decline, the number of salespeople can be increased, and the number of salespeople can be adjusted based on the actual situation.

Further, the information circulated in the above process may be communicated through an information communication manner (e.g., intranet, mail, intercom tool, etc.) inside the enterprise, for example, data aggregation is performed through the intranet, policy transmission is performed through the intercom tool, etc., and a workflow may be configured based on the policy, so as to implement a closed data service loop.

According to the method and the device, data source tracing can be carried out through the data index blood margin map, maintenance is not needed, analysis processing is carried out through a What-If analysis function in an Excel-like analysis mode, and the learning cost of business analysts is reduced. Relatively fixed business operation can be standardized in an RPA mode, and the operation can be automatically completed through a robot, so that the operation problems caused by manual operation are reduced to the maximum extent, the strategy and the business sketch can be continuously stored and perfected, and the accuracy and the effectiveness of strategy and business risk coping are improved. And the circulated information can be combined with the information communication mode in an enterprise, so that the information and the strategy can be conveniently conveyed, and the execution efficiency is improved.

Fig. 4 exemplarily illustrates a block diagram of a data decision device of an embodiment of the present disclosure, and as shown in fig. 4, the device includes:

the relational graph module is used for acquiring a data conversion link relational graph from a data source to a data target address;

the risk module is used for determining risk information through the data analysis model and the data display indexes;

According to an embodiment of the present disclosure, the risk module is further configured to: processing the data display index through a What-If analysis function to obtain an analysis result; and processing the analysis result through the data analysis model to obtain the risk information.

According to an embodiment of the disclosure, the improvement module is further to: determining a data source corresponding to the risk information according to the data index blood margin map; and determining service improvement information according to the risk information and the data source.

FIG. 5 is a block diagram illustrating a data decision device in accordance with an exemplary embodiment. The device 1600 may be provided as a terminal or server, for example. Device 1600 includes a processing component 1602, and memory resources, represented by memory 1603, for storing instructions, such as applications, that are executable by processing component 1602. The application programs stored in memory 1603 may include one or more modules each corresponding to a set of instructions. Further, the processing component 1602 is configured to execute instructions to perform the above-described methods.

The device 1600 may also include a power component 1606 configured to perform power management for the device 1600, a wired or wireless network interface 1605 configured to connect the device 1600 to a network, and an input/output (I/O) interface 1608. The device 1600 may operate based on an operating system stored in memory 1603, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.

The present invention may be methods, apparatus, systems and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therein for carrying out aspects of the present invention.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present invention may be assembler instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It is noted that, unless expressly stated otherwise, all features disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features. Where used, it is further preferred, even further and more preferred that the brief introduction of the further embodiment is made on the basis of the preceding embodiment, the contents of which further, preferably, even further or more preferred the rear band is combined with the preceding embodiment as a complete constituent of the further embodiment. Several further, preferred, still further or more preferred arrangements of the belt after the same embodiment may be combined in any combination to form a further embodiment.

It will be appreciated by persons skilled in the art that the embodiments of the invention described above and shown in the drawings are given by way of example only and are not limiting of the invention. The objects of the invention have been fully and effectively accomplished. The functional and structural principles of the present invention have been shown and described in the embodiments, and any variations or modifications may be made to the embodiments of the present invention without departing from the principles described.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.

Claims

1. A method for data decision making, comprising:

selecting a data analysis model according to the business mode;

determining service improvement information according to the data index blood margin map and the risk information;

determining risk information through the data analysis model and the data presentation indicators, including:

processing the analysis result through the data analysis model to obtain the risk information;

determining business improvement information according to the data index blood margin map and the risk information, wherein the business improvement information comprises the following steps:

determining a data source corresponding to the risk information according to the data index blood margin map;

determining service improvement information according to the risk information and the data source;

the method further comprises the following steps:

according to the historical data, the historical business mode and the historical operation result, a data analysis model is established through a model establishing tool;

the method further comprises the following steps:

performing sand table deduction on the data source according to the service improvement information to obtain a prediction improvement result;

the method further comprises the following steps:

executing the service improvement information on the data source in a PRA mode under the condition that the prediction improvement result meets the improvement requirement;

the method further comprises the following steps:

2. A data decision device, comprising:

the improvement module is used for determining service improvement information according to the data index blood margin map and the risk information;

the risk module is further used for processing the data display index through a What-If analysis function to obtain an analysis result;

the improvement module is further used for determining a data source corresponding to the risk information according to the data index blood margin map;

the model module is further configured to:

the improvement module is further configured to:

and under the condition that the predicted improvement result meets the improvement requirement, storing the service improvement information to a strategy library.

3. A data decision device, comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to invoke the memory-stored instructions to perform the method of claim 1.

4. A computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the method of claim 1.