Data center type financial data processing system and method based on business look-ahead

Abstract

The invention relates to the technical field of financial data management, in particular to a data center type financial data processing system and method based on business look-ahead, and the method comprises the steps: directly obtaining and generating data at a business generation stage through synchronously setting a double-platform architecture of a business platform module and a data platform module; the financial data management steps are optimized, the processing efficiency of business system data and financial data management processes is improved, a financial data processing rule engine is arranged in the business platform module, the standard unification of the data is realized, and the consistency of data sources and key indexes of the financial data in various processing processes is ensured; the technical problems that in the prior art, when financial data of a supply chain is checked and managed, the workload is large, and errors are prone to occurring are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of financial data management, and in particular to a data center-type financial data processing system and method based on business foresight. Background Art

[0002] In traditional supermarket supply chain business, due to the existence of multiple participants such as consumers, manufacturers, and operators, there are multiple data standards and multiple financial accounting systems in the front-end business financial data accounting management, which leads to a large workload and easy errors in the financial data processing process of the entire supply chain.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a data-centric financial data processing system and method based on business foresight, aiming to solve the technical problems of large workload and easy errors in the existing technology when calculating and managing the financial data of the supply chain.

[0005] To achieve the above object, the present invention provides a data center-type financial data processing system based on business foresight, the system comprising:

[0006] The data center-type financial data processing system based on business foresight includes: a business middle station module, a data middle station module and a data processing module, and the data processing module is connected to the business middle station module and the data middle station module respectively;

[0007] The business middle platform module is used to obtain business data of multiple dimensions;

[0008] The data processing module is used to drive the financial data processing rule engine in the business middle platform module to process the business data to obtain target financial data;

[0009] The data middle platform module is used to store the target financial data and generate financial statements based on the target financial data in response to user query requests.

[0010] Optionally, the business middle platform module includes: a business module, an engine module and a business data sharing module;

[0011] The business module is used to call a preset program interface to obtain business data of multiple dimensions of each node on the business chain;

[0012] The engine module is used to respond to the data processing request initiated by the data processing module and determine the corresponding target processing engine according to the data processing request;

[0013] The engine module is further used to control the target processing engine to perform financial data integration on the business data of each dimension to obtain target financial data;

[0014] The business data sharing module is used to send the business data of the multiple dimensions and the target financial data to the data processing module.

[0015] Optionally, the business module is further used to perform consistency processing on the business data of the multiple dimensions to obtain business data that meets preset format requirements.

[0016] Optionally, the business data includes at least: document data;

[0017] The engine module is also used to perform document accounting on the document data through a data accounting engine to obtain accounting data.

[0018] Optionally, the business data also includes: tax data and management and accounting data;

[0019] The engine module is also used to establish a communication connection between the document center and the engine module;

[0020] The engine module is further used to transmit the tax data and the accounting data to the document center based on the communication connection channel;

[0021] The engine module is further used to perform tax accounting on the tax data stored in the document center through a tax engine;

[0022] The engine module is also used to perform management and accounting calculations on the management and accounting data stored in the document center through the management and accounting engine.

[0023] Optionally, the document data includes at least: sales documents, rental documents, collection documents, transfer documents and tax documents, the tax data includes at least: reconciliation data, payment data and tax bureau, and the accounting data includes at least: accounting measurement data and accounting allocation data.

[0024] Optionally, the accounting data includes at least: general ledger entry data, general ledger entry data, voucher data, account balance data and asset card data.

[0025] Optionally, the data middle platform module is further used to respond to a user query request and determine corresponding target financial data based on the user query request;

[0026] A financial report is generated based on the target financial data and a preset report format.

[0027] Based on this, this embodiment further proposes a data center-type financial data processing method based on business foresight. The data center-type financial data processing system method based on business foresight is applied to the data center-type financial data processing system based on business foresight as described above. The data center-type financial data processing method based on business foresight includes:

[0028] The business middle platform module obtains business data of multiple dimensions;

[0029] The data processing module drives the financial data processing rule engine in the business middle platform module to process the business data to obtain target financial data;

[0030] The data middle platform module stores the target financial data and generates financial statements based on the target financial data in response to user query requests.

[0031] One or more technical solutions proposed in the present invention have at least the following technical effects: the present invention synchronously sets up a dual-middle-office architecture of a business middle-office module and a data middle-office module, thereby directly acquiring generated data during the business occurrence stage, optimizing the steps of financial data management, and improving the processing efficiency of business system data and financial data management processes. A financial data processing rule engine is set in the business middle-office module to achieve standard unification of data and ensure that the data source and key indicators of financial data are consistent within various processing processes, thereby avoiding the technical problems of large workload and easy errors in the prior art when calculating and managing the financial data of the supply chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0034] Figure 1 It is a schematic diagram of the architecture of a data center-type financial data processing system based on business foresight of the present invention;

[0035] Figure 2 A specific architecture diagram of a data center-type financial data processing system based on business foresight of the present invention;

[0036] Figure 3It is a functional schematic diagram of the dual-middle-station architecture of the business middle station and the data middle station of the present invention;

[0037] Figure 4 It is a flowchart of the first embodiment of the data-centric financial data processing method based on business foresight of the present invention.

[0038] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0039] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0040] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0041] Based on this, the embodiment of the present invention provides a data center-type financial data processing system based on business foresight, referring to Figure 1 , Figure 1 It is a schematic diagram of the architecture of a first embodiment of a data center-type financial data processing system based on business foresight of the present invention.

[0042] In this embodiment, the data center-type financial data processing system based on business foresight includes: a business middle platform module, a data middle platform module and a data processing module;

[0043] The business middle platform module is used to obtain business data of multiple dimensions;

[0044] The data processing module is used to drive the financial data processing rule engine in the business middle platform module to process the business data to obtain target financial data;

[0045] The data middle platform module is used to store the target financial data and generate financial statements based on the target financial data in response to user query requests.

[0046] It should be noted that the reference Figure 2 and Figure 3 , Figure 2 is a specific architecture diagram of a data center-type financial data processing system based on business foresight in an embodiment of the present invention, Figure 3This is a functional diagram of the dual-middle-office architecture of the business middle office and the data middle office in this embodiment, wherein the business middle office module is directly connected to the business system, and can directly extract various data in the business process from the business system to achieve the control of financial data from the beginning of the business. Compared with the traditional post-financial data control, this embodiment moves the control time boundary forward, thereby advancing the time node of financial data management, reducing the possibility of risk occurrence, and ensuring that business risks are effectively controlled.

[0047] In this embodiment, business data of multiple dimensions include but are not limited to market research data, store establishment data, product category planning data, procurement data, ordering data, distribution data, channel operation data, investment promotion data, influence data, and consumer operation data. Specifically, market research data include but are not limited to macro market research data, industry and competitive trend research data, store business district consumer research data, and brand insight and establishment data. Store establishment data include but are not limited to site selection data, store establishment standard data, construction management data, store establishment cost management data, and property daily maintenance data. Category planning data include but are not limited to space and item strategy data, SKU planning data, space management data, category adjustment data, etc. Procurement data include but are not limited to product supplier sourcing data, daily management product supplier data, and product cost management data etc. Ordering data includes but is not limited to forecasting order demand data, managing ordering data, managing inventory data, and order scheduling data, etc. Distribution data includes but is not limited to DC distribution network data, managing logistics operation performance data, transporting goods data, delivering goods data, and managing logistics revenue and expenditure data, etc. Channel operation data includes but is not limited to store, online, community, group purchase data, and managing wholesale data, etc. Investment promotion data includes but is not limited to investment promotion planning data, merchant management data, and evaluation of investment promotion performance data, etc. Marketing data includes but is not limited to planning marketing promotion activity data, executing marketing promotion activity data, and evaluating marketing promotion activity data, etc. Consumer operation data includes but is not limited to consumer insight research report data, designing membership system data, member full life cycle operation data, and member loyalty evaluation data, etc. This embodiment does not make specific restrictions on this.

[0048] In this embodiment, the data middle platform module stores at least multiple dimensional data such as product suppliers, logistics supply chain, store life cycle, consumer marketing and finance. Specifically, the product supplier data includes but is not limited to relevant information of the product domain such as product evaluation analysis, private brand analysis, product life cycle, imported products and new product analysis. It also includes relevant information of the supplier domain including supplier evaluation and supplier's entire life cycle. The logistics supply chain includes but is not limited to relevant information of the ordering domain such as abnormal products, inventory age management and inventory turnover.

[0049] It should be understood that the financial data processing rule engine includes an accounting engine, a tax engine, and an accounting engine. The accounting engine is mainly used to account for various documents and obtain accounting data, the tax engine is used to perform tax verification, and the accounting engine is used to measure and allocate accounting data. This embodiment does not impose specific restrictions on this.

[0050] Furthermore, the business middle platform module includes: a business module, an engine module and a business data sharing module;

[0051] The business module is used to call a preset program interface to obtain business data of multiple dimensions of each node on the business chain;

[0052] The engine module is used to respond to the data processing request initiated by the data processing module and determine the corresponding target processing engine according to the data processing request;

[0053] The engine module is further used to control the target processing engine to perform financial data integration on the business data of each dimension to obtain target financial data;

[0054] The business data sharing module is used to send the business data of the multiple dimensions and the target financial data to the data processing module.

[0055] It should be understood that different data processing requirements correspond to different rule engines. As mentioned above, the rule engine in this embodiment includes at least an accounting engine, a tax engine, and an accounting engine. When it is necessary to account for various documents, the data accounting engine can be used to perform document accounting on the document data to obtain accounting data, and transmit the accounting data to the data processing module for subsequent storage in a unified format to the data middle platform module.

[0056] Furthermore, the business module is also used to perform consistency processing on the business data of the multiple dimensions to obtain business data that meets the preset format requirements.

[0057] In specific implementation, consistent processing of business data in multiple dimensions means integrating tax, settlement, capital and other management and control requirements into the business middle platform, starting management and control from the time the business occurs, changing post-event management and control to pre-event management and control, and then converting various types of business data through a unified data format to obtain business data that meets the preset format requirements.

[0058] Further, the business data at least includes: document data;

[0059] The engine module is also used to perform document accounting on the document data through a data accounting engine to obtain accounting data.

[0060] Furthermore, the business data also includes: tax data and management and accounting data;

[0061] The engine module is also used to establish a communication connection between the document center and the engine module;

[0062] The engine module is further used to transmit the tax data and the accounting data to the document center based on the communication connection channel;

[0063] The engine module is further used to perform tax accounting on the tax data stored in the document center through a tax engine;

[0064] The engine module is also used to perform management and accounting calculations on the management and accounting data stored in the document center through the management and accounting engine.

[0065] Similarly, for tax data and accounting data, the tax engine can be used to perform tax accounting on the tax data stored in the document center, and the accounting engine can be used to perform accounting accounting on the accounting data stored in the document center.

[0066] Furthermore, the document data includes at least: sales documents, rental documents, collection documents, transfer documents and tax documents, the tax data includes at least: reconciliation data, payment data and tax bureau, and the accounting data includes at least: accounting measurement data and accounting allocation data.

[0067] The accounting data at least includes: general ledger entry data, general ledger entry data, voucher data, account balance data and asset card data.

[0068] Furthermore, the data middle platform module is also used to respond to a user query request and determine corresponding target financial data based on the user query request;

[0069] A financial report is generated based on the target financial data and a preset report format.

[0070] In the specific implementation, in order to meet the needs of users to issue financial reports accurately and efficiently and assist enterprises in business analysis and decision-making, the data middle platform module in this embodiment can not only store various financial data in a unified format, but also generate financial statements to strengthen staff's control over the rationality of business budget data; improve business and financial analysis capabilities, and strengthen business and strategic decision-making support capabilities.

[0071] This embodiment synchronously sets up a dual-middle-office architecture of a business middle-office module and a data middle-office module, thereby directly acquiring generated data during the business occurrence stage, optimizing the steps of financial data management, and improving the processing efficiency of business system data and financial data management processes. A financial data processing rule engine is set up in the business middle-office module to achieve standard unification of data, ensure that the data source and key indicators of financial data are consistent within various processing processes, and avoid the technical problems of large workload and easy errors in the prior art when calculating and managing the financial data of the supply chain.

[0072] Based on this, the embodiment of the present invention provides a data center-type financial data processing method based on business foresight, referring to Figure 3 , Figure 3 The figure is a flow chart of a first embodiment of a data-centric financial data processing method based on business foresight according to the present invention.

[0073] In this embodiment, the data-centric financial data processing method based on business foresight includes:

[0074] Step S10: The business middle platform module obtains business data of multiple dimensions.

[0075] Step S20: The data processing module drives the financial data processing rule engine in the business middle platform module to process the business data to obtain target financial data.

[0076] Step S30: The data middle platform module stores the target financial data and generates financial statements based on the target financial data in response to user query requests.

[0077] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a control computer or a cloud server, etc. The following takes the cloud server as an example to illustrate this embodiment and the following embodiments.

[0078] It should be noted that the business middle-office module is directly connected to the business system, and can directly extract various data in the business process from the business system to realize the management and control of financial data from the beginning of the business. Compared with the traditional post-financial data management, this embodiment moves the management time boundary forward, thereby advancing the time node of financial data management, reducing the possibility of risk occurrence, and ensuring that business risks are effectively controlled.

[0079] In this embodiment, business data of multiple dimensions include but are not limited to market research data, store establishment data, product category planning data, procurement data, ordering data, distribution data, channel operation data, investment promotion data, influence data, and consumer operation data. Specifically, market research data include but are not limited to macro market research data, industry and competitive trend research data, store business district consumer research data, and brand insight and establishment data. Store establishment data include but are not limited to site selection data, store establishment standard data, construction management data, store establishment cost management data, and property daily maintenance data. Category planning data include but are not limited to space and item strategy data, SKU planning data, space management data, category adjustment data, etc. Procurement data include but are not limited to product supplier sourcing data, daily management product supplier data, and product cost management data etc. Ordering data includes but is not limited to forecasting order demand data, managing ordering data, managing inventory data, and order scheduling data, etc. Distribution data includes but is not limited to DC distribution network data, managing logistics operation performance data, transporting goods data, delivering goods data, and managing logistics revenue and expenditure data, etc. Channel operation data includes but is not limited to store, online, community, group purchase data, and managing wholesale data, etc. Investment promotion data includes but is not limited to investment promotion planning data, merchant management data, and evaluation of investment promotion performance data, etc. Marketing data includes but is not limited to planning marketing promotion activity data, executing marketing promotion activity data, and evaluating marketing promotion activity data, etc. Consumer operation data includes but is not limited to consumer insight research report data, designing membership system data, member full life cycle operation data, and member loyalty evaluation data, etc. This embodiment does not make specific restrictions on this.

[0080] In this embodiment, the data middle platform module stores at least multiple dimensional data such as product suppliers, logistics supply chain, store life cycle, consumer marketing and finance. Specifically, the product supplier data includes but is not limited to relevant information of the product domain such as product evaluation analysis, private brand analysis, product life cycle, imported products and new product analysis. It also includes relevant information of the supplier domain including supplier evaluation and supplier's entire life cycle. The logistics supply chain includes but is not limited to relevant information of the ordering domain such as abnormal products, inventory age management and inventory turnover.

[0081] It should be understood that the financial data processing rule engine includes an accounting engine, a tax engine, and an accounting engine. The accounting engine is mainly used to account for various documents and obtain accounting data, the tax engine is used to perform tax verification, and the accounting engine is used to measure and allocate accounting data. This embodiment does not impose specific restrictions on this.

[0082] This embodiment synchronously sets up a dual-middle-office architecture of a business middle-office module and a data middle-office module, thereby directly acquiring generated data during the business occurrence stage, optimizing the steps of financial data management, and improving the processing efficiency of business system data and financial data management processes. A financial data processing rule engine is set up in the business middle-office module to achieve standard unification of data, ensure that the data source and key indicators of financial data are consistent within various processing processes, and avoid the technical problems of large workload and easy errors in the prior art when calculating and managing the financial data of the supply chain.

[0083] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, the computer-readable program instructions being used to execute the data-centric financial data processing method based on business foresight in the above-mentioned embodiment.

[0084] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0085] The computer-readable storage medium may be included in a data center-type financial data processing device based on business foresight; or may exist independently without being assembled into a data center-type financial data processing device based on business foresight.

[0086] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the data center-type financial data processing device based on business foresight, the data center-type financial data processing device based on business foresight can perform: data center-type financial data processing based on business foresight.

[0087] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0088] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0089] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0090] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned data-centric financial data processing method based on business foresight, and can solve the technical problems of data-centric financial data processing based on business foresight. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the data-centric financial data processing method based on business foresight provided by the above-mentioned embodiment, and will not be elaborated here.

[0091] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned data-centric financial data processing method based on business foresight.

[0092] The computer program product provided by the present application can solve the technical problem of data center-type financial data processing based on business foresight. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the data center-type financial data processing method based on business foresight provided by the above embodiment, and will not be repeated here.

[0093] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A data center-type financial data processing system based on business foresight, characterized in that: The data center-type financial data processing system based on business foresight includes: a business middle station module, a data middle station module and a data processing module, and the data processing module is connected to the business middle station module and the data middle station module respectively; The business middle platform module is used to obtain business data of multiple dimensions; The data processing module is used to drive the financial data processing rule engine in the business middle platform module to process the business data to obtain target financial data; The data middle platform module is used to store the target financial data and generate financial statements based on the target financial data in response to user query requests.

2. The system according to claim 1, characterized in that The business middle platform module includes: a business module, an engine module and a business data sharing module; The business module is used to call a preset program interface to obtain business data of multiple dimensions of each node on the business chain; The engine module is used to respond to the data processing request initiated by the data processing module and determine the corresponding target processing engine according to the data processing request; The engine module is further used to control the target processing engine to perform financial data integration on the business data of each dimension to obtain target financial data; The business data sharing module is used to send the business data of the multiple dimensions and the target financial data to the data processing module.

3. The system according to claim 2, characterized in that The business module is further used to perform consistency processing on the business data of the multiple dimensions to obtain business data that meets the preset format requirements.

4. The system according to claim 2, characterized in that The business data at least includes: document data; The engine module is also used to perform document accounting on the document data through a data accounting engine to obtain accounting data.

5. The system according to claim 2, characterized in that The business data also includes: tax data and accounting data; The engine module is also used to establish a communication connection between the document center and the engine module; The engine module is further used to transmit the tax data and the accounting data to the document center based on the communication connection channel; The engine module is further used to perform tax accounting on the tax data stored in the document center through a tax engine; The engine module is also used to perform management and accounting calculations on the management and accounting data stored in the document center through the management and accounting engine.

6. The system according to claim 2, characterized in that The document data at least includes: sales documents, rental documents, collection documents, transfer documents and tax documents; the tax data at least includes: reconciliation data, payment data and tax bureau; the accounting data at least includes: accounting measurement data and accounting allocation data.

7. The system according to claim 4, characterized in that The accounting data at least includes: general ledger entry data, general ledger entry data, voucher data, account balance data and asset card data.

8. The system of claim 1, wherein: The data middle platform module is further used to respond to a user query request and determine corresponding target financial data based on the user query request; A financial report is generated based on the target financial data and a preset report format.

9. A data-centric financial data processing method based on business foresight, characterized in that: The data center-type financial data processing system method based on business foresight is applied to the data center-type financial data processing system based on business foresight as described in claims 1 to 8 above, and the data center-type financial data processing method based on business foresight includes: The business middle platform module obtains business data of multiple dimensions; The data processing module drives the financial data processing rule engine in the business middle platform module to process the business data to obtain target financial data; The data middle platform module stores the target financial data and generates financial statements based on the target financial data in response to user query requests.

10. The method according to claim 9, characterized in that The business middle platform module includes: a business module, an engine module and a business data sharing module; The business module calls a preset program interface to obtain business data of multiple dimensions of each node on the business chain; The engine module responds to the data processing request initiated by the data processing module and determines the corresponding target processing engine according to the data processing request; The engine module controls the target processing engine to perform financial data integration on the business data of each dimension to obtain target financial data; The business data sharing module sends the business data of the multiple dimensions and the target financial data to the data processing module.

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