CN112651817A - Intelligent financial decision big data analysis system - Google Patents
Intelligent financial decision big data analysis system Download PDFInfo
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- CN112651817A CN112651817A CN202011613054.7A CN202011613054A CN112651817A CN 112651817 A CN112651817 A CN 112651817A CN 202011613054 A CN202011613054 A CN 202011613054A CN 112651817 A CN112651817 A CN 112651817A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/12—Accounting
- G06Q40/125—Finance or payroll
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2428—Query predicate definition using graphical user interfaces, including menus and forms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
Abstract
The invention relates to the technical field of intelligent financial decision, and particularly discloses an intelligent financial decision big data analysis system, which comprises an acquisition module, a decision module and a decision module, wherein the acquisition module is used for acquiring enterprise data of an enterprise and other enterprises; the information processing module is used for diagnosing enterprise data of other enterprises and screening to obtain real data of other enterprises; analyzing the real data of other enterprises to generate a comparison report; analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating an enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating an enterprise expected third-stage report, and the like; and the generating module is used for outputting the expected report and the real report. The final displayed content of the system is mainly an expected report and a real report, the analysis capability of the system is visually and clearly displayed, a decision maker can conveniently compare the analysis capability, the user experience is good, and the convenience is high.
Description
Technical Field
The invention relates to the technical field of intelligent financial decision, in particular to an intelligent financial decision big data analysis system.
Background
With the continuous and deep application of the financial system, many enterprises realize that the computer management information system in the true sense is not only a financial account form, but also a set of system which can comprehensively embody the enterprise management means and adapt to the enterprise change at any time; in the financial decision making process, certain individuals who make decisions finally are interfered by external information, and information is collected when people want to make more intelligent decisions; with the arrival of the big data era, more reference data can be provided for the financial decision making process, but most of the corresponding big data analysis systems are not perfect, most of the existing intelligent financial decision making big data analysis systems only provide one decision guide and some probabilities, which can play a negative role on a decider to a certain extent, and the existing innovation points are that the system analysis capacity is improved, which is not necessarily inverted, and how to better integrate and display data to the decider is what the big data analysis system should do.
Disclosure of Invention
The invention aims to provide an intelligent financial decision big data analysis system to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
an intelligent financial decision big data analysis system, the system comprising:
the acquisition module is used for acquiring enterprise data of the enterprise and other enterprises;
the information processing module is used for diagnosing enterprise data of other enterprises and screening to obtain real data of other enterprises; analyzing the real data of other enterprises to generate a comparison report; analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating an enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating an enterprise expected third-stage report, and the like;
and the generating module is used for outputting the expected report and the real report.
The technical scheme adopted by the embodiment of the invention is further limited as follows: the acquisition module includes:
and the local acquisition unit is used for acquiring the enterprise data of the enterprise and storing the enterprise data in the local memory.
The network acquisition unit is used for acquiring enterprise data of other enterprises, and the enterprise data of the other enterprises at least comprises two periods; the acquisition step comprises: the method comprises the steps that original business data of each enterprise are collected and stored in a big data storage unit, wherein the big data storage unit comprises an Sqoop data extraction tool, a Storm real-time data acquisition tool, an HDFS file transmission tool and an API interface Restful service tool; and cleaning, converting and loading the collected original trip data to generate enterprise data of other enterprises.
The technical scheme adopted by the embodiment of the invention is further limited as follows: the information processing module includes:
the diagnosis method is that the enterprise data of other enterprises are subjected to rationality analysis through big data, and the rationality analysis refers to the steps of acquiring capital expenditure, market scale, price trend, cost structure of other enterprises, and generating and predicting an enterprise asset liability statement, a profit statement and a cash flow statement of the other enterprises; comprehensively analyzing the historical operation performance of the enterprise and comparing the historical operation performance with the longitudinal and transverse operation performance to generate a historical operation performance trend graph, comparing the generated historical operation performance trend graph with the financial models of the existing enterprises in the same field, judging the trend, and further screening to obtain real data of other enterprises;
the first processing unit is used for analyzing the screened real data of other enterprises, integrating the real data of other enterprises and generating an enterprise database; selecting an automatically generated financial statement template file, calling corresponding real data of other enterprises from an enterprise database, filling or replacing part or all of active cells in the industrial statement template file after processing to generate a final statement file, and storing the generated statement file into a corresponding statement database; the financial statement template file is characterized in that external custom plug-ins are added into part or all of Excel cells on the basis of Excel forms, and corresponding calculation strategies are set in part of the Excel cells.
The technical scheme adopted by the embodiment of the invention is further limited as follows: the information processing module further includes:
a second processing unit: the method is used for analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating the enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating the enterprise expected third-stage report, and the like.
The technical scheme adopted by the embodiment of the invention is further limited as follows: the generated enterprise database is a large relational database which supports SQLServer, Oracle, db2, infomix and Sybase.
The technical scheme adopted by the embodiment of the invention is further limited as follows: and storing the financial model of the existing enterprise in the same field in a model memory, wherein the model memory is a read-only memory, judging the authority of an accessor when receiving an access request, copying the financial model and outputting if the authority of the accessor is enough, and the copied file is used as a comparison file of the generated historical operation performance trend graph.
The technical scheme adopted by the embodiment of the invention is further limited as follows: the generation module comprises:
the display unit is used for displaying the output expected report forms and the real report forms in an arranged manner, so that the comparison of a user is facilitated; the output expected reports are arranged as a line and are arranged in an ascending mode from left to right according to the period number, the real reports are arranged as a second line and correspond to the expected reports in the first line according to the period number, the rightmost end of the first line is the latest expected report, and the leftmost end of the second line is the first-stage real report.
Compared with the prior art, the invention has the beneficial effects that: the invention diagnoses the acquired enterprise data of other enterprises, screens out more real enterprise data, processes the enterprise data of the enterprise and the enterprise data of other enterprises through the information processing module, analyzes the first-stage real report and all comparison reports of the enterprise, predicts and generates the enterprise expected second-stage report, analyzes the first-stage and second-stage real reports and all comparison reports of the enterprise, predicts and generates the enterprise expected third-stage report, and so on, and finally generates and displays the expected report and the real report through the generating module, the content displayed by the system is the expected report and the real report, the analysis capability of the system is visually and clearly displayed, the comparison of decision makers is convenient, the system only processes the data, does not make decisions, is positioned at an auxiliary function, correspondingly, the required hardware cost is greatly reduced, the use feeling is good, the convenience is extremely high.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 is a flow chart diagram of an intelligent financial decision big data analysis method.
FIG. 2 is a block diagram of a structure of an intelligent financial decision big data analysis system.
FIG. 3 is a block diagram of the structure of an acquisition module in the intelligent financial decision big data analysis system.
FIG. 4 is a block diagram of the structure of the information processing module in the intelligent financial decision big data analysis system.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
Fig. 1 shows a flow chart of an intelligent financial decision big data analysis system provided by an embodiment of the present invention, which includes:
acquiring enterprise data of the enterprise and other enterprises;
diagnosing enterprise data of other enterprises, and screening to obtain real data of other enterprises; analyzing the real data of other enterprises to generate a comparison report; analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating an enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating an enterprise expected third-stage report, and the like;
and outputting the expected report and the real report.
Example 2
Fig. 2 is a block diagram showing the structure of the intelligent financial decision big data analysis system, wherein the intelligent financial decision big data analysis system 10 comprises:
the acquisition module 11 is used for acquiring enterprise data of the enterprise and other enterprises;
the information processing module 12 is used for diagnosing enterprise data of other enterprises and screening to obtain real data of other enterprises; analyzing the real data of other enterprises to generate a comparison report; analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating an enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating an enterprise expected third-stage report, and the like;
the generating module 13 is used for outputting an expected report and a real report;
further, fig. 3 shows a block diagram of a component structure of an obtaining module 11 in the intelligent financial decision big data analysis system, where the obtaining module 11 includes:
a local acquiring unit 111, configured to acquire enterprise data of an enterprise and store the enterprise data in a local storage;
a network acquiring unit 112, configured to acquire enterprise data of other enterprises, where the enterprise data of other enterprises includes at least two periods; the acquisition step comprises: the method comprises the steps that original business data of each enterprise are collected and stored in a big data storage unit, wherein the big data storage unit comprises an Sqoop data extraction tool, a Storm real-time data acquisition tool, an HDFS file transmission tool and an API interface Restful service tool; cleaning, converting and loading the collected original trip data to generate enterprise data of other enterprises;
specifically, fig. 4 shows a block diagram of a component structure of the information processing module 12 in the intelligent financial decision big data analysis system, where the information processing module 12 includes:
the diagnosis unit 121 is used for diagnosing enterprise data of other enterprises, and the diagnosis method is to perform rationality analysis on the enterprise data of other enterprises through big data, wherein the rationality analysis is to acquire capital expenditure, market scale, price trend, cost structure of other enterprises, and generate predicted enterprise asset liability statement, profit statement and cash flow statement; comprehensively analyzing the historical operation performance of the enterprise and comparing the historical operation performance with the longitudinal and transverse operation performance to generate a historical operation performance trend graph, comparing the generated historical operation performance trend graph with the financial models of the existing enterprises in the same field, judging the trend, and further screening to obtain real data of other enterprises;
the first processing unit 122 is configured to analyze the screened real data of the other enterprises, integrate the real data of the other enterprises, and generate an enterprise database; selecting an automatically generated financial statement template file, calling corresponding real data of other enterprises from an enterprise database, filling or replacing part or all of active cells in the industrial statement template file after processing to generate a final statement file, and storing the generated statement file into a corresponding statement database; the financial statement template file is characterized in that an external custom plug-in is added into a part or all of Excel cells on the basis of Excel forms, wherein a part of the Excel cells are provided with corresponding calculation strategies;
the second processing unit 123 is configured to analyze the first-stage real report and all comparison reports of the enterprise, predict and generate an enterprise expected second-stage report, analyze the first-stage and second-stage real reports and all comparison reports of the enterprise, predict and generate an enterprise expected third-stage report, and so on.
Example 3
Different from the embodiment 2, in the present embodiment, the intelligent financial decision big data analysis system 10 is further limited, and the generated enterprise database is a large relational database, and the large relational database supports SQLServer, Oracle, db2, infomix and Sybase;
further, the financial model of the existing enterprise in the same field is stored in a model memory, the model memory is read-only memory, when an access request is received, the authority of an accessor is judged, if the authority of the accessor is enough, the financial model is copied and output, and the copied file is used as a comparison file of the generated historical operation performance trend graph;
specifically, the generating module 13 includes: the display unit is used for displaying the output expected report forms and the real report forms in an arranged manner, so that the comparison of a user is facilitated; the output expected reports are arranged as a line and are arranged in an ascending mode from left to right according to the period number, the real reports are arranged as a second line and correspond to the expected reports in the first line according to the period number, the rightmost end of the first line is the latest expected report, and the leftmost end of the second line is the first-stage real report.
The intelligent financial decision big data analysis system adopts a computer hardware system in a von Neumann structure and comprises an arithmetic unit, a controller, a memory, input equipment and output equipment; the output device comprises a touch screen display, and the touch screen display can be used as the output device and also can be used as the output device;
the controller fetches instructions and analyzes the instructions one by one from the memory, then completes corresponding operations according to the instruction requirements, generates a series of control commands, enables all parts of the computer to automatically, continuously and coordinately act to form an organic whole, realizes the input of programs, the input of data, the operation and the output of results, and the arithmetic operation or the logic operation generated in the process is completed by the arithmetic unit; the Memory comprises a Read-Only Memory (ROM) for storing a computer program, and a protection device is arranged outside the Memory.
Illustratively, a computer program can be partitioned into one or more modules, which are stored in memory and executed by a processor to implement the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the terminal device. For example, the computer program may be divided into units or modules of the berth-status display system provided by the various system embodiments described above.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal equipment and connects the various parts of the entire user terminal using various interfaces and lines.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the terminal device by operating or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory mainly comprises a storage program area and a storage data area, wherein the storage program area can store an operating system, application programs (such as an information acquisition template display function, a product information publishing function and the like) required by at least one function and the like; the storage data area may store data created according to the use of the berth-state display system (e.g., product information acquisition templates corresponding to different product types, product information that needs to be issued by different product providers, etc.), and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The terminal device integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the modules/units in the system according to the above embodiment may be implemented by a computer program, which may be stored in a computer-readable storage medium and used by a processor to implement the functions of the embodiments of the system. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. An intelligent financial decision big data analysis system, the system comprising:
the acquisition module is used for acquiring enterprise data of the enterprise and other enterprises;
the information processing module is used for diagnosing enterprise data of other enterprises and screening to obtain real data of other enterprises; analyzing the real data of other enterprises to generate a comparison report; analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating an enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating an enterprise expected third-stage report, and the like;
and the generating module is used for outputting the expected report and the real report.
2. The intelligent financial decision big data analysis system of claim 1, wherein the acquisition module comprises:
and the local acquisition unit is used for acquiring the enterprise data of the enterprise and storing the enterprise data in the local memory.
3. The network acquisition unit is used for acquiring enterprise data of other enterprises, and the enterprise data of the other enterprises at least comprises two periods; the acquisition step comprises: the method comprises the steps that original business data of each enterprise are collected and stored in a big data storage unit, wherein the big data storage unit comprises an Sqoop data extraction tool, a Storm real-time data acquisition tool, an HDFS file transmission tool and an API interface Restful service tool; and cleaning, converting and loading the collected original trip data to generate enterprise data of other enterprises.
4. The intelligent financial decision big data analysis system of claim 2, wherein the information processing module comprises:
the diagnosis method is that the enterprise data of other enterprises are subjected to rationality analysis through big data, and the rationality analysis refers to the steps of acquiring capital expenditure, market scale, price trend, cost structure of other enterprises, and generating and predicting an enterprise asset liability statement, a profit statement and a cash flow statement of the other enterprises; comprehensively analyzing the historical operation performance of the enterprise and comparing the historical operation performance with the longitudinal and transverse operation performance to generate a historical operation performance trend graph, comparing the generated historical operation performance trend graph with the financial models of the existing enterprises in the same field, judging the trend, and further screening to obtain real data of other enterprises;
the first processing unit is used for analyzing the screened real data of other enterprises, integrating the real data of other enterprises and generating an enterprise database; selecting an automatically generated financial statement template file, calling corresponding real data of other enterprises from an enterprise database, filling or replacing part or all of active cells in the industrial statement template file after processing to generate a final statement file, and storing the generated statement file into a corresponding statement database; the financial statement template file is characterized in that external custom plug-ins are added into part or all of Excel cells on the basis of Excel forms, and corresponding calculation strategies are set in part of the Excel cells.
5. The intelligent financial decision big data analysis system of claim 3, wherein the information processing module further comprises:
a second processing unit: the method is used for analyzing the first-stage real report and all comparison reports of the enterprise, predicting and generating the enterprise expected second-stage report, analyzing the first-stage and second-stage real reports and all comparison reports of the enterprise, predicting and generating the enterprise expected third-stage report, and the like.
6. An intelligent financial decision big data analysis system as claimed in claim 3 where the generated enterprise database is a large relational database supporting SQLServer, Oracle, db2, infomix and Sybase.
7. The intelligent financial decision big data analysis system according to claim 3 or 5, wherein the financial models of the existing enterprises in the same field are stored in a model memory, the model memory is read-only memory, when an access request is received, the authority of an accessor is judged, if the authority of the accessor is enough, the financial models are copied and output, and the copied file is used as a comparison file of the generated historical operation performance trend graph.
8. The intelligent financial decision big data analysis system of claim 4, wherein the generation module comprises:
the display unit is used for displaying the output expected report forms and the real report forms in an arranged manner, so that the comparison of a user is facilitated; the output expected reports are arranged as a line and are arranged in an ascending mode from left to right according to the period number, the real reports are arranged as a second line and correspond to the expected reports in the first line according to the period number, the rightmost end of the first line is the latest expected report, and the leftmost end of the second line is the first-stage real report.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113361949A (en) * | 2021-06-24 | 2021-09-07 | 上海基甸信息科技有限公司 | Performance management system based on big data analysis |
| CN113609829A (en) * | 2021-08-20 | 2021-11-05 | 广东电网有限责任公司 | Report processing system and method based on financial big data |
| CN116610681A (en) * | 2023-07-20 | 2023-08-18 | 深圳维格云科技有限公司 | Data processing method, device, equipment and computer program for multidimensional table |
| CN117057942A (en) * | 2023-10-12 | 2023-11-14 | 之江实验室科技控股有限公司 | Intelligent financial decision big data analysis system |
-
2020
- 2020-12-30 CN CN202011613054.7A patent/CN112651817A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113361949A (en) * | 2021-06-24 | 2021-09-07 | 上海基甸信息科技有限公司 | Performance management system based on big data analysis |
| CN113609829A (en) * | 2021-08-20 | 2021-11-05 | 广东电网有限责任公司 | Report processing system and method based on financial big data |
| CN116610681A (en) * | 2023-07-20 | 2023-08-18 | 深圳维格云科技有限公司 | Data processing method, device, equipment and computer program for multidimensional table |
| CN116610681B (en) * | 2023-07-20 | 2023-12-12 | 深圳维格云科技有限公司 | Data processing method, device, equipment and computer program for multidimensional table |
| CN117057942A (en) * | 2023-10-12 | 2023-11-14 | 之江实验室科技控股有限公司 | Intelligent financial decision big data analysis system |
| CN117057942B (en) * | 2023-10-12 | 2024-01-30 | 之江实验室科技控股有限公司 | Intelligent financial decision big data analysis system |
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