A financial data integration method, system, computer and readable storage medium

Abstract

The application provides a financial data integration method, system, computer and readable storage medium, which comprises the following steps: receiving a user input financial data set in real time, and performing a full scan on the financial data set to correspondingly detect a plurality of financial elements contained in the financial data set; respectively matching a target data subset corresponding to each financial element in the financial data set, wherein each target data subset contains specific numerical values; performing standardization processing on each target data subset based on a first preset rule to generate a plurality of corresponding standard data sets, wherein the contents contained in each standard data set are different; creating a target two-dimensional coordinate system in real time, and respectively mapping a target data curve corresponding to each standard data set in the target two-dimensional coordinate system based on a second preset rule, and adding a corresponding data identifier to each target data curve. The application can effectively improve work efficiency.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a financial data integration method, system, computer, and readable storage medium. Background Technology

[0002] With the advancement of technology and the rapid development of the times, people have established various types of enterprises to provide products or services, which has made people's lives more convenient.

[0003] In their daily operations, existing enterprises all have certain expenses and income, which generate corresponding financial data. The financial data can intuitively reflect the enterprise's operating situation, making effective management of financial data particularly important.

[0004] Furthermore, in the process of processing financial data, most existing technologies first distinguish the categories of various financial data and then generate corresponding financial statements based on each category. However, although this method allows staff to observe the required financial data, it takes a long time and can easily lead to confusion when viewing the results, thus reducing work efficiency. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a financial data integration method, system, computer, and readable storage medium to solve the problem that the prior art requires staff to spend a long time to view financial data, and that the viewing results are easily confused.

[0006] The first aspect of the present invention proposes:

[0007] A financial data integration method, wherein the method includes:

[0008] The system receives a set of financial data input by the user in real time and performs a full scan of the set of financial data to detect the corresponding financial elements contained in the set of financial data.

[0009] In the financial data set, a target data subset corresponding to each financial element is matched, and each target data subset contains a specific numerical value;

[0010] Each of the target data subsets is standardized based on the first preset rule to generate several corresponding standard datasets, each of which contains different content.

[0011] A target two-dimensional coordinate system is created in real time, and target data curves corresponding to each of the standard datasets are mapped in the target two-dimensional coordinate system based on the second preset rule, and corresponding data identifiers are added to each of the target data curves.

[0012] The beneficial effects of this invention are as follows: by performing a full scan of the financial data set input by the user, it is possible to obtain several financial elements contained in the current financial data set. Based on this, targeted processing can be performed separately, and the required target data subsets can be matched separately. Furthermore, corresponding standardization processing can be performed separately, thereby uniformly converting them into a standard format and finally displaying them simultaneously in the form of curves in a unified target two-dimensional coordinate system. This allows staff to view multiple different data at the same time, and the results of each data are relatively clear, thereby improving work efficiency.

[0013] Furthermore, the step of standardizing each subset of target data based on a first preset rule to generate several corresponding standard datasets includes:

[0014] When each of the target data subsets is acquired in real time, several target values ​​contained in the target data subset are detected in real time.

[0015] The system detects the target time node corresponding to each target value in real time when it is generated, and performs standardization processing on the target data subset corresponding to the target time node to generate a corresponding standard dataset. The target time node is a specific value.

[0016] Furthermore, the step of standardizing the target data subset corresponding to the target time node to generate the corresponding standard dataset includes:

[0017] When each target time node is acquired in real time, the corresponding start time node and end time node are detected in real time.

[0018] Based on the start time node and the end time node, the target time threshold corresponding to the target data subset is determined in real time.

[0019] The target data subset is standardized according to the target time threshold to generate the corresponding standard dataset, and the target time threshold is unique.

[0020] Furthermore, the step of standardizing the target data subset according to the target time threshold to generate the corresponding standard dataset includes:

[0021] When the target time threshold is obtained in real time, a corresponding initial time axis is created based on the target time threshold;

[0022] Each target time node is mapped to the interior of the initial time axis to generate the corresponding target time axis in real time;

[0023] Each target value is mapped to the target time axis according to each target time node to generate a corresponding complete time axis in real time, and the complete time axis is set as the standard dataset. The complete time axis is unique.

[0024] Furthermore, the step of mapping the target data curve corresponding to each of the standard datasets in the target two-dimensional coordinate system based on the second preset rule includes:

[0025] When each of the aforementioned standard datasets is acquired in real time, the corresponding complete timeline is extracted in real time.

[0026] Each complete timeline is parsed to detect the corresponding time format and numerical format.

[0027] Based on the time format and the numerical format, the standard dataset is mapped to the target two-dimensional coordinate system to generate the target data curve.

[0028] Furthermore, the step of mapping the standard dataset to the target two-dimensional coordinate system based on the time format and the numerical format to generate the target data curve includes:

[0029] When the time format and numerical format corresponding to each complete time axis are determined, it is judged in real time whether the time format and numerical format of each complete time axis are consistent and uniform.

[0030] If it is determined in real time that the time format and numerical format of each complete time axis are consistent, then the target data curve corresponding to it is directly generated in real time in the target two-dimensional coordinate system based on the complete time axis.

[0031] Furthermore, the step of directly generating the corresponding target data curve in the target two-dimensional coordinate system in real time based on the complete time axis includes:

[0032] The time is set as the x-axis of the target two-dimensional coordinate system, and the numerical value is set as the y-axis of the target two-dimensional coordinate system.

[0033] The starting point and ending point corresponding to the complete time axis are detected in real time, and each target value is mapped to the target two-dimensional coordinate system in sequence according to the direction from the starting point to the ending point, so as to generate a number of connection points.

[0034] Each of the connection points is connected sequentially to generate the target data curve.

[0035] The second aspect of the present invention proposes:

[0036] A financial data integration system, wherein the system comprises:

[0037] The detection module is used to receive a set of financial data input by the user in real time and perform a full scan of the set of financial data to detect several financial elements contained in the set of financial data.

[0038] The matching module is used to match the target data subset corresponding to each of the financial elements in the financial data set, and each target data subset contains a specific value;

[0039] The processing module is used to perform standardization processing on each of the target data subsets based on a first preset rule to generate several corresponding standard datasets, each of which contains different content.

[0040] The mapping module is used to create a target two-dimensional coordinate system in real time, and to map the target data curves corresponding to each of the standard datasets into the target two-dimensional coordinate system based on the second preset rule, and to add corresponding data identifiers to each of the target data curves.

[0041] Furthermore, the processing module is specifically used for:

[0042] When each of the target data subsets is acquired in real time, several target values ​​contained in the target data subset are detected in real time.

[0043] The system detects the target time node corresponding to each target value in real time when it is generated, and performs standardization processing on the target data subset corresponding to the target time node to generate a corresponding standard dataset. The target time node is a specific value.

[0044] Furthermore, the processing module is specifically used for:

[0045] When each target time node is acquired in real time, the corresponding start time node and end time node are detected in real time.

[0046] Based on the start time node and the end time node, the target time threshold corresponding to the target data subset is determined in real time.

[0047] The target data subset is standardized according to the target time threshold to generate the corresponding standard dataset, and the target time threshold is unique.

[0048] Furthermore, the processing module is specifically used for:

[0049] When the target time threshold is obtained in real time, a corresponding initial time axis is created based on the target time threshold;

[0050] Each target time node is mapped to the interior of the initial time axis to generate the corresponding target time axis in real time;

[0051] Each target value is mapped to the target time axis according to each target time node to generate a corresponding complete time axis in real time, and the complete time axis is set as the standard dataset. The complete time axis is unique.

[0052] Furthermore, the mapping module is specifically used for:

[0053] When each of the aforementioned standard datasets is acquired in real time, the corresponding complete timeline is extracted in real time.

[0054] Each complete timeline is parsed to detect the corresponding time format and numerical format.

[0055] Based on the time format and the numerical format, the standard dataset is mapped to the target two-dimensional coordinate system to generate the target data curve.

[0056] Furthermore, the mapping module is specifically used for:

[0057] When the time format and numerical format corresponding to each complete time axis are determined, it is judged in real time whether the time format and numerical format of each complete time axis are consistent and uniform.

[0058] If it is determined in real time that the time format and numerical format of each complete time axis are consistent, then the target data curve corresponding to it is directly generated in real time in the target two-dimensional coordinate system based on the complete time axis.

[0059] Furthermore, the mapping module is specifically used for:

[0060] The time is set as the x-axis of the target two-dimensional coordinate system, and the numerical value is set as the y-axis of the target two-dimensional coordinate system.

[0061] The starting point and ending point corresponding to the complete time axis are detected in real time, and each target value is mapped to the target two-dimensional coordinate system in sequence according to the direction from the starting point to the ending point, so as to generate a number of connection points.

[0062] Each of the connection points is connected sequentially to generate the target data curve.

[0063] The third aspect of the present invention proposes:

[0064] A computer includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the financial data integration method as described above.

[0065] The fourth aspect of the present invention proposes:

[0066] A readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the financial data integration method as described above.

[0067] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0068] Figure 1 A flowchart of the financial data integration method provided in the first embodiment of the present invention;

[0069] Figure 2 The structural block diagram of the financial data integration system provided in the third embodiment of the present invention.

[0070] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0071] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0072] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0073] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0074] Please see Figure 1 The figure shows the financial data integration method provided in the first embodiment of the present invention. The financial data integration method provided in this embodiment enables staff to view multiple different data at the same time, and the results of each data are relatively obvious, thereby improving work efficiency.

[0075] Specifically, this embodiment provides:

[0076] A financial data integration method specifically includes the following steps:

[0077] Step S10: Receive the set of financial data input by the user in real time, and perform a full scan of the set of financial data to detect the financial elements contained in the set of financial data.

[0078] Step S20: Match the target data subsets corresponding to each financial element in the financial data set, and each target data subset contains a specific numerical value.

[0079] Step S30: Standardize each of the target data subsets based on the first preset rule to generate several corresponding standard datasets, each of which contains different content.

[0080] Step S40: A target two-dimensional coordinate system is created in real time, and target data curves corresponding to each of the standard datasets are mapped in the target two-dimensional coordinate system according to the second preset rule, and corresponding data identifiers are added to each of the target data curves.

[0081] Specifically, in this embodiment, it should first be noted that in order to accurately and effectively complete the centralized processing of various types of financial data, it is necessary to accurately obtain the characteristics of various types of financial data and perform unified standardization processing, so that they can be displayed in a standardized manner in a unified interface. Based on this, in practical applications, the present invention will pre-set a server and correspondingly set the financial data integration method within the server. Preferably, in daily use, the server will always be in standby mode. When the server receives a set of financial data input by the user through the user terminal in real time, the server will immediately activate the financial data integration method. Specifically, the present invention will immediately perform a full scan of the current financial data set, and at the same time, it can detect several financial elements contained in the current financial data set. Preferably, these several financial elements can be profit, assets and liabilities, and cash flow, etc.

[0082] Furthermore, after identifying the objects to be processed in real time, namely the aforementioned financial elements, the present invention will further match each target data subset corresponding to each current financial element within the current financial data set. Specifically, each target data subset contains a series of specific values. Based on this, in order to enable staff to intuitively observe the data contained within each target data subset, preferably, the present invention will first standardize each target data subset according to a pre-set first preset rule and generate several standard datasets accordingly. Similarly, the contents contained within each standard dataset are also different. Based on this, in order to provide a more intuitive display, the present invention preferably creates a target two-dimensional coordinate system in real time using existing CAD or UG software. Furthermore, it immediately maps the data contained in each standard dataset to the interior of the target two-dimensional coordinate system according to a pre-set second preset rule, and forms corresponding target data curves one by one. Specifically, the changes in each target data curve can intuitively reflect the changes in each of the above financial elements. At the same time, corresponding data labels are added to each target data curve in real time for clear differentiation, thereby enabling staff to observe multiple data simultaneously and improving work efficiency.

[0083] Second Embodiment

[0084] Furthermore, the step of standardizing each subset of target data based on a first preset rule to generate several corresponding standard datasets includes:

[0085] When each of the target data subsets is acquired in real time, several target values ​​contained in the target data subset are detected in real time.

[0086] The system detects the target time node corresponding to each target value in real time when it is generated, and performs standardization processing on the target data subset corresponding to the target time node to generate a corresponding standard dataset. The target time node is a specific value.

[0087] Furthermore, the step of standardizing the target data subset corresponding to the target time node to generate the corresponding standard dataset includes:

[0088] When each target time node is acquired in real time, the corresponding start time node and end time node are detected in real time.

[0089] Based on the start time node and the end time node, the target time threshold corresponding to the target data subset is determined in real time.

[0090] The target data subset is standardized according to the target time threshold to generate the corresponding standard dataset, and the target time threshold is unique.

[0091] Furthermore, the step of standardizing the target data subset according to the target time threshold to generate the corresponding standard dataset includes:

[0092] When the target time threshold is obtained in real time, a corresponding initial time axis is created based on the target time threshold;

[0093] Each target time node is mapped to the interior of the initial time axis to generate the corresponding target time axis in real time;

[0094] Each target value is mapped to the target time axis according to each target time node to generate a corresponding complete time axis in real time, and the complete time axis is set as the standard dataset. The complete time axis is unique.

[0095] Furthermore, the step of mapping the target data curve corresponding to each of the standard datasets in the target two-dimensional coordinate system based on the second preset rule includes:

[0096] When each of the aforementioned standard datasets is acquired in real time, the corresponding complete timeline is extracted in real time.

[0097] Each complete timeline is parsed to detect the corresponding time format and numerical format.

[0098] Based on the time format and the numerical format, the standard dataset is mapped to the target two-dimensional coordinate system to generate the target data curve.

[0099] Furthermore, the step of mapping the standard dataset to the target two-dimensional coordinate system based on the time format and the numerical format to generate the target data curve includes:

[0100] When the time format and numerical format corresponding to each complete time axis are determined, it is judged in real time whether the time format and numerical format of each complete time axis are consistent and uniform.

[0101] If it is determined in real time that the time format and numerical format of each complete time axis are consistent, then the target data curve corresponding to it is directly generated in real time in the target two-dimensional coordinate system based on the complete time axis.

[0102] Furthermore, the step of directly generating the corresponding target data curve in the target two-dimensional coordinate system in real time based on the complete time axis includes:

[0103] The time is set as the x-axis of the target two-dimensional coordinate system, and the numerical value is set as the y-axis of the target two-dimensional coordinate system.

[0104] The starting point and ending point corresponding to the complete time axis are detected in real time, and each target value is mapped to the target two-dimensional coordinate system in sequence according to the direction from the starting point to the ending point, so as to generate a number of connection points.

[0105] Each of the connection points is connected sequentially to generate the target data curve.

[0106] Furthermore, in this embodiment, it should be noted that after obtaining the required target data subset in real time through the above steps, in order to objectively and effectively standardize the current target data subset, preferably, the present invention needs to further detect several target values ​​contained in the current target data subset. Simultaneously, it further detects the target time node corresponding to the generation of each target value in the historical database, i.e., the corresponding generation time. Further, based on each current target time node, and in real time according to the chronological order of each time node, the corresponding start time node and end time node are further detected. This allows for the determination of the target time threshold corresponding to the current target data subset, i.e., the time span corresponding to the current target data subset, based on the current start time node and end time node. Based on this, using the current target time threshold as a foundation, and to further facilitate the mapping of subsequent data, a corresponding initial timeline will be created in real time. Since this initial timeline is incomplete, the present invention will further map each of the aforementioned target time nodes into the current initial timeline to obtain the required target timeline. Furthermore, the present invention also needs to further map the target values ​​corresponding to each current target time node into the current target timeline to finally generate the required complete timeline. At the same time, the current complete timeline and the corresponding data it contains will be set to the aforementioned standard dataset to facilitate subsequent processing.

[0107] Furthermore, after obtaining the required standard dataset through the above steps, in order to objectively and accurately perform graphical processing on the current standard dataset to generate the corresponding target data curve, preferably, the present invention will further detect the time format and numerical format corresponding to the complete time axis in the current standard dataset. Based on this, it is necessary to immediately perform real-time judgment. Preferably, it is necessary to judge in real time whether the time format and numerical format corresponding to each complete time axis are consistent and unified. Specifically, if they are consistent, it indicates that each complete time axis has a unified format, thus eliminating the need for secondary processing and allowing direct subsequent mapping processing. Conversely, if they are not consistent, it indicates that each complete time axis has a unified format, thus eliminating the need for secondary processing and allowing direct subsequent mapping processing. This indicates that the current complete timelines do not have a unified format. Therefore, it is necessary to adjust the format of each complete timeline to a unified format. Based on this, the above time can be set as the x-axis of the current target two-dimensional coordinate system, and the above values ​​can be set as the y-axis of the current target two-dimensional coordinate system. On this basis, the start point and end point of each complete timeline are detected, and then each target value is mapped to the target two-dimensional coordinate system in sequence from the start point to the end point. Corresponding connection points can be formed within the target two-dimensional coordinate system in sequence. Finally, by connecting each connection point in sequence, the corresponding target data curve can be formed for subsequent processing.

[0108] Please see Figure 2 The third embodiment of the present invention provides:

[0109] A financial data integration system, wherein the system comprises:

[0110] The detection module is used to receive a set of financial data input by the user in real time and perform a full scan of the set of financial data to detect several financial elements contained in the set of financial data.

[0111] The matching module is used to match the target data subset corresponding to each financial element in the financial data set, and each target data subset contains a specific value;

[0112] The processing module is used to perform standardization processing on each of the target data subsets based on a first preset rule to generate several corresponding standard datasets, each of which contains different content.

[0113] The mapping module is used to create a target two-dimensional coordinate system in real time, and to map the target data curves corresponding to each of the standard datasets into the target two-dimensional coordinate system based on the second preset rule, and to add corresponding data identifiers to each of the target data curves.

[0114] Furthermore, the processing module is specifically used for:

[0115] When each of the target data subsets is acquired in real time, several target values ​​contained in the target data subset are detected in real time.

[0116] The system detects the target time node corresponding to each target value in real time when it is generated, and performs standardization processing on the target data subset corresponding to the target time node to generate a corresponding standard dataset. The target time node is a specific value.

[0117] Furthermore, the processing module is specifically used for:

[0118] When each target time node is acquired in real time, the corresponding start time node and end time node are detected in real time.

[0119] Based on the start time node and the end time node, the target time threshold corresponding to the target data subset is determined in real time.

[0120] The target data subset is standardized according to the target time threshold to generate the corresponding standard dataset, and the target time threshold is unique.

[0121] Furthermore, the processing module is specifically used for:

[0122] When the target time threshold is obtained in real time, a corresponding initial time axis is created based on the target time threshold;

[0123] Each target time node is mapped to the interior of the initial time axis to generate the corresponding target time axis in real time;

[0124] Each target value is mapped to the target time axis according to each target time node to generate a corresponding complete time axis in real time, and the complete time axis is set as the standard dataset. The complete time axis is unique.

[0125] Furthermore, the mapping module is specifically used for:

[0126] When each of the aforementioned standard datasets is acquired in real time, the corresponding complete timeline is extracted in real time.

[0127] Each complete timeline is parsed to detect the corresponding time format and numerical format.

[0128] Based on the time format and the numerical format, the standard dataset is mapped to the target two-dimensional coordinate system to generate the target data curve.

[0129] Furthermore, the mapping module is specifically used for:

[0130] When the time format and numerical format corresponding to each complete time axis are determined, it is judged in real time whether the time format and numerical format of each complete time axis are consistent and uniform.

[0131] If it is determined in real time that the time format and numerical format of each complete time axis are consistent, then the target data curve corresponding to it is directly generated in real time in the target two-dimensional coordinate system based on the complete time axis.

[0132] Furthermore, the mapping module is specifically used for:

[0133] The time is set as the x-axis of the target two-dimensional coordinate system, and the numerical value is set as the y-axis of the target two-dimensional coordinate system.

[0134] The starting point and ending point corresponding to the complete time axis are detected in real time, and each target value is mapped to the target two-dimensional coordinate system in sequence according to the direction from the starting point to the ending point, so as to generate a number of connection points.

[0135] Each of the connection points is connected sequentially to generate the target data curve.

[0136] The fourth embodiment of the present invention provides a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the financial data integration method as described above.

[0137] The fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the financial data integration method as described above.

[0138] In summary, the financial data integration method and system provided by the above embodiments of the present invention enable staff to view multiple different data simultaneously, and the results of each data are relatively clear, thereby improving work efficiency.

[0139] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in a unified processor; or the above modules can be located in different processors in any combination.

[0140] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0141] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0142] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0143] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0144] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for integrating financial data, characterized in that, The method includes: The system receives a set of financial data input by the user in real time and performs a full scan of the set of financial data to detect several financial elements contained in the set of financial data. In the financial data set, a target data subset corresponding to each financial element is matched, and each target data subset contains a specific numerical value; Each of the target data subsets is standardized based on the first preset rule to generate several corresponding standard datasets, each of which contains different content. A target two-dimensional coordinate system is created in real time, and target data curves corresponding to each of the standard datasets are mapped in the target two-dimensional coordinate system according to the second preset rule, and corresponding data identifiers are added to each of the target data curves. The step of standardizing each subset of target data based on a first preset rule to generate several corresponding standard datasets includes: When each of the target data subsets is acquired in real time, several target values ​​contained in the target data subset are detected in real time. The target time node corresponding to each target value is detected in real time when it is generated, and the target data subset corresponding to it is standardized based on the target time node to generate the corresponding standard dataset. The target time node is a specific value. The step of standardizing the target data subset corresponding to the target time node to generate the corresponding standard dataset includes: When each target time node is acquired in real time, the corresponding start time node and end time node are detected in real time. Based on the start time node and the end time node, the target time threshold corresponding to the target data subset is determined in real time. The target data subset is standardized according to the target time threshold to generate the corresponding standard dataset, wherein the target time threshold is unique. The step of standardizing the target data subset according to the target time threshold to generate the corresponding standard dataset includes: When the target time threshold is obtained in real time, a corresponding initial time axis is created based on the target time threshold; Each target time node is mapped to the interior of the initial time axis to generate the corresponding target time axis in real time; Each target value is mapped to the target time axis according to each target time node to generate a corresponding complete time axis in real time, and the complete time axis is set as the standard dataset. The complete time axis is unique.

2. The financial data integration method according to claim 1, characterized in that: The step of mapping the target data curve corresponding to each of the standard datasets in the target two-dimensional coordinate system based on the second preset rule includes: When each of the aforementioned standard datasets is acquired in real time, the corresponding complete timeline is extracted in real time. Each complete timeline is parsed to detect the corresponding time format and numerical format. Based on the time format and the numerical format, the standard dataset is mapped to the target two-dimensional coordinate system to generate the target data curve.

3. The financial data integration method according to claim 2, characterized in that: The step of mapping the standard dataset to the target two-dimensional coordinate system based on the time format and the numerical format to generate the target data curve includes: When the time format and numerical format corresponding to each complete time axis are determined, it is judged in real time whether the time format and numerical format of each complete time axis are consistent and uniform. If it is determined in real time that the time format and numerical format of each complete time axis are consistent, then the target data curve corresponding to it is directly generated in real time in the target two-dimensional coordinate system based on the complete time axis.

4. The financial data integration method according to claim 3, characterized in that: The step of directly generating the corresponding target data curve in the target two-dimensional coordinate system in real time based on the complete time axis includes: The time is set as the x-axis of the target two-dimensional coordinate system, and the numerical value is set as the y-axis of the target two-dimensional coordinate system. The starting point and ending point corresponding to the complete time axis are detected in real time, and each target value is mapped to the target two-dimensional coordinate system in sequence according to the direction from the starting point to the ending point, so as to generate a number of connection points. Each of the connection points is connected sequentially to generate the target data curve.

5. A financial data integration system, characterized in that, The system for implementing the financial data integration method as described in any one of claims 1 to 4 includes: The detection module is used to receive a set of financial data input by the user in real time and perform a full scan of the set of financial data to detect several financial elements contained in the set of financial data. The matching module is used to match the target data subset corresponding to each financial element in the financial data set, and each target data subset contains a specific value; The processing module is used to standardize each of the target data subsets based on a first preset rule to generate several corresponding standard datasets, each of which contains different content. The mapping module is used to create a target two-dimensional coordinate system in real time, and to map the target data curves corresponding to each of the standard datasets into the target two-dimensional coordinate system based on the second preset rule, and to add corresponding data identifiers to each of the target data curves.

6. A computer 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, it implements the financial data integration method as described in any one of claims 1 to 4.

7. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the financial data integration method as described in any one of claims 1 to 4.

Images