CN116882916A - Cash flow calculating method and cash flow calculating system - Google Patents
Cash flow calculating method and cash flow calculating system Download PDFInfo
- Publication number
- CN116882916A CN116882916A CN202310723024.9A CN202310723024A CN116882916A CN 116882916 A CN116882916 A CN 116882916A CN 202310723024 A CN202310723024 A CN 202310723024A CN 116882916 A CN116882916 A CN 116882916A
- Authority
- CN
- China
- Prior art keywords
- item
- cash flow
- data
- items
- sub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000004364 calculation method Methods 0.000 claims abstract description 39
- 238000005553 drilling Methods 0.000 claims abstract description 22
- 238000004458 analytical method Methods 0.000 claims abstract description 16
- 230000001939 inductive effect Effects 0.000 claims description 33
- 238000003860 storage Methods 0.000 claims description 11
- 238000004891 communication Methods 0.000 claims description 8
- 230000008859 change Effects 0.000 abstract description 6
- 238000012790 confirmation Methods 0.000 abstract description 6
- 238000004422 calculation algorithm Methods 0.000 abstract description 5
- 239000010410 layer Substances 0.000 description 11
- 238000010586 diagram Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000009960 carding Methods 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 239000002356 single layer Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- 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
- G06Q40/02—Banking, e.g. interest calculation or account maintenance
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Finance (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Accounting & Taxation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Development Economics (AREA)
- Technology Law (AREA)
- Quality & Reliability (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Operations Research (AREA)
- Tourism & Hospitality (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The application discloses a cash flow calculation method and a cash flow calculation system. The method comprises the following steps: acquiring a dependency table of cash flow items, wherein the dependency table comprises a dependency relationship and a scene switch; establishing a dependency model of the cash flow project according to the dependency relationship; obtaining an initial tree model through drilling analysis according to the dependency model; determining a target tree model according to the scene switch and the initial tree model; determining a data set of the target tree model; and determining cash flow of the cash flow project according to the data set of the target tree model. The application passes through the algorithm of drilling analysis, so that a user can generate a calculation formula for each cash flow item only by configuring the dependency relationship among each cash flow item, the workload of the user for early service confirmation is reduced, the efficiency is higher, and the expansibility of the later cash flow item change work is increased.
Description
Technical Field
The application relates to the technical field of financial cash flow calculation, in particular to a cash flow calculation method and a cash flow calculation system.
Background
At present, market competition in the heavy industry is severe, and as the operation scale becomes huge, continuous optimization on financial cash flow management of a company is required to ensure sufficient and stable cash flow conditions of the company so as to meet the market competition requirement. In the current industry cash flow calculation module, each cash flow item calculation formula adopts a calculation method which is configured independently, service personnel manually performs independent calculation setting for calculation and combination formulas of each item, and calculates each cash flow item value through a program background. However, the prior art scheme has the following problems:
(1) The cash flow calculation formulas are configured for each item independently, so that the difficulty of system function expansion is increased, a large number of item calculation formulas are changed due to the fact that items are added or reduced, and the early-stage business confirmation workload of a customer is increased;
(2) The method can not meet the inconsistent requirement of the calculation formulas of the same cash flow item under multiple scenes;
(3) With the increase of the calculation items required by the late business expansion, the difficulty of using the system by the user can be increased, and the using experience is reduced.
Disclosure of Invention
The embodiment of the application aims to provide a cash flow calculation method and a cash flow calculation system, which are used for solving the problems of complex cash flow calculation mode and low efficiency in the prior art.
To achieve the above object, a first aspect of the present application provides a method for calculating cash flow, applied to a cash flow calculation system, the method comprising:
acquiring a dependency table of cash flow items, wherein the dependency table comprises a dependency relationship and a scene switch;
establishing a dependency model of the cash flow project according to the dependency relationship;
obtaining an initial tree model through drilling analysis according to the dependency model;
determining a target tree model according to the scene switch and the initial tree model;
determining a data set of the target tree model;
and determining cash flow of the cash flow project according to the data set of the target tree model.
In the embodiment of the application, obtaining the initial tree model through drilling analysis according to the dependency model comprises the following steps:
determining basic sub-items and inductive items of the dependency model;
drilling the inductive items layer by layer according to the dependency paths of the dependency models to obtain basic sub-items corresponding to the inductive items and coefficients of the basic sub-items;
and determining an initial tree model according to the inductive items and the basic sub-items corresponding to the inductive items and the coefficients of the basic sub-items.
In an embodiment of the present application, determining the dataset of the target tree model includes:
determining basic sub-item data of a basic sub-item;
and determining a data set of the target tree model according to the basic sub-items, the inductive items, the coefficients of the basic sub-items and the basic sub-item data.
In an embodiment of the present application, the base sub-item includes:
an accounting document type basic sub-item, a refund type basic sub-item and a refund type basic sub-item.
In an embodiment of the present application, the cash flow computing system communicates with the SAP ledger total database, and determining base sub-item data for the base sub-item includes:
acquiring first historical data of an SAP general ledger total database and preset control conditions;
and according to preset control conditions, respectively summarizing the first historical data into the accounting document base sub-items to obtain the base sub-item data of the accounting document base sub-items.
In the embodiment of the present application, the cash flow computing system is further respectively in communication with the SAP ledger database and the first preset database, the basic sub-item data of the refund type basic sub-item includes first refund data and second refund data, and determining the basic sub-item data further includes:
acquiring second historical data of the SAP ledger database, and taking the second historical data as first refund data;
and acquiring first preset data of a first preset database in an ETL mode, and taking the first preset data as second refund data.
In an embodiment of the present application, the cash flow computing system is further in communication with a second preset database, and determining the base sub-item data further comprises:
and acquiring second preset data of a second preset database in an ETL mode, and taking the second preset data as basic sub-item data of the funding type basic sub-item.
In an embodiment of the present application, the target tree model includes:
a group project tree model, a host tree project model, and an accessory project tree model.
A second aspect of the application provides a cash flow computing system comprising:
a memory configured to store instructions; and
a processor configured to invoke the instructions from the memory and when executing the instructions, to enable a method according to the cash flow calculation described above.
A third aspect of the application provides a machine-readable storage medium having stored thereon instructions for causing a machine to perform a method of cash flow calculation according to the above.
Through the technical scheme, the dependency list of the cash flow item is obtained, wherein the dependency list comprises a dependency relationship and a scene switch; establishing a dependency model of the cash flow project according to the dependency relationship; obtaining an initial tree model through drilling analysis according to the dependency model; determining a target tree model according to the scene switch and the initial tree model; determining a data set of the target tree model; and determining cash flow of the cash flow project according to the data set of the target tree model. The application passes through the algorithm of drilling analysis, so that a user can generate a calculation formula for each cash flow item only by configuring the dependency relationship among each cash flow item, the workload of the user for early service confirmation is reduced, the efficiency is higher, and the expansibility of the later cash flow item change work is increased.
Additional features and advantages of embodiments of the application will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain, without limitation, the embodiments of the application. In the drawings:
FIG. 1 schematically illustrates a flow chart of a method of cash flow calculation in accordance with an embodiment of the present application;
fig. 2 schematically illustrates a block diagram of a cash flow computing system in accordance with an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the detailed description described herein is merely for illustrating and explaining the embodiments of the present application, and is not intended to limit the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that, if directional indications (such as up, down, left, right, front, and rear … …) are included in the embodiments of the present application, the directional indications are merely used to explain the relative positional relationship, movement conditions, etc. between the components in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indications are correspondingly changed.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.
Fig. 1 schematically shows a flow chart of a method of cash flow calculation according to an embodiment of the present application. As shown in FIG. 1, an embodiment of the present application provides a cash flow computing method for use in a cash flow computing system, which may include the following steps.
Step 101, acquiring a dependency table of cash flow items, wherein the dependency table comprises a dependency relationship and a scene switch;
102, establishing a dependency model of cash flow items according to the dependency relationship;
step 103, obtaining an initial tree model through drilling analysis according to the dependency model;
step 104, determining a target tree model according to the scene switch and the initial tree model;
step 105, determining a data set of the target tree model;
and 106, determining the cash flow of the cash flow project according to the data set of the target tree model.
In the cash flow calculation method in the prior art, summary is simply carried out through a detail balance list, but with the increase of the number of basic items and the improvement of the level of summary items, accurate and even useful information is difficult to obtain from the basic items, and the calculation difficulty is also improved. Based on the above, the application provides a cash flow calculation method, which is applied to a cash flow calculation system, and by means of a down-drilling analysis algorithm, a user only needs to configure the dependency relationship among each cash flow item, and the cash flow calculation system can automatically generate a calculation formula for each cash flow item, so that the workload of the user for early-stage business confirmation is greatly reduced, and the expansibility of later-stage cash flow item change work is improved.
Specifically, the cash flow computing system may first obtain a dependency table of cash flow items preset by a user, where the dependency table includes a dependency relationship and a scene switch. Dependency relationships are also known as "logical relationships," and in project management refers to relationships that represent changes in one of two activities (leading and trailing) will affect the other. In the embodiment of the application, the dependency relationship refers to the dependency relationship among cash flow items, and a dependency model of the cash flow items can be established according to the dependency relationship among the cash flow items. In the dependency model, two sides of one single dependency relationship of a single layer can be respectively called a parent term and a child term, the dependency model refers to that for a single cash flow item (child term), a summary item (parent term) on the upper layer is traced upwards, a corresponding up-down corresponding relationship is established, and a corresponding summary coefficient when the child item summarizes the parent term is specified. The initial tree model is a mathematical operation set for drilling down all the inductive items according to the dependency relationship between the parent and child items of the dependency model, so as to divide all the inductive items into a series of basic child items.
The scene switch is used for controlling the main control conditions including condition control, display control, inverse control and the like according to the requirements of different scenes and the related control conditions set according to actual conditions. Through the filtering of the control conditions, a purpose-made tree model, namely a target tree model, in the corresponding scene can be obtained, and the adaptability of the cash flow computing system in different scenes is enhanced. That is, on the basis of the initial tree model, a special tree model, namely a target tree model, under different scenes can be conveniently obtained by using the scene switch. The data set of the target tree model, namely the purpose-built tree model, refers to a group of data sets of the items and the basic sub-items, the basic sub-item data and the basic sub-item coefficients which correspond to each other. Specifically, the purpose-made tree-like model, namely the target tree-like model, is matched with the inductive item of the basic sub-item data set, and the data set of the target tree-like model, of which the inductive item and the basic sub-item are completely corresponding, can be obtained. After the data set of the target tree model is determined, the data set can be summarized according to the mathematical coefficient corresponding to each basic subitem, so that all cash flow project data can be calculated. Preferably, in the process of carding the balance, the data can be compared with the historical balance data, so that whether an adjustment space exists or not is further analyzed.
Through the technical scheme, the dependency list of the cash flow item is obtained, wherein the dependency list comprises a dependency relationship and a scene switch; establishing a dependency model of the cash flow project according to the dependency relationship; obtaining an initial tree model through drilling analysis according to the dependency model; determining a target tree model according to the scene switch and the initial tree model; determining a data set of the target tree model; and determining cash flow of the cash flow project according to the data set of the target tree model. The application passes through the algorithm of drilling analysis, so that a user can generate a calculation formula for each cash flow item only by configuring the dependency relationship among each cash flow item, the workload of the user for early service confirmation is reduced, the efficiency is higher, and the expansibility of the later cash flow item change work is increased.
In an embodiment of the present application, obtaining an initial tree model through drilling analysis according to the dependency model may include:
determining basic sub-items and inductive items of the dependency model;
drilling the inductive items layer by layer according to the dependency paths of the dependency models to obtain basic sub-items corresponding to the inductive items and coefficients of the basic sub-items;
and determining an initial tree model according to the inductive items and the basic sub-items corresponding to the inductive items and the coefficients of the basic sub-items.
In the embodiment of the application, the tree model refers to a mathematical operation set for downwards drilling all the inductive items according to the dependency relationship between the parent and child items of the dependency model, so as to divide all the inductive items into a series of basic child items. Specifically, first the underlying sub-items and summary items in the dependency model need to be determined. The basic sub-item refers to the most basic item which can not be segmented any more in the dependency model, the basic sub-item has no lower-layer sub-item, and the rest items which can be segmented into a plurality of sub-item mathematical calculation results are summary items. After the basic sub-items and the inductive items in the dependency model are determined, layer-by-layer drilling can be carried out downwards along the dependency path of the dependency model, and the inductive coefficients of the discovered sub-items are calculated mathematically with the inductive coefficients of the previous layer every time one layer is drilled. When the drill-down level is enough, each basic sub-item corresponding to the summary item and the coefficient corresponding to each basic sub-item can be obtained. And finally merging the basic sub-items with the equal corresponding relations of the basic sub-items, and obtaining the drill-down tree-shaped data model of the complete cash flow project, namely the initial tree-shaped model.
In an embodiment of the present application, the target tree model may include:
a group project tree model, a host tree project model, and an accessory project tree model.
In the embodiment of the application, the target tree model refers to a special tree model for matching different cash flow calculation requirements under different scenes. In the reworking industry, the target tree model, i.e., the purpose-made tree model, can be divided into three types, namely, a group project tree model, a host tree project model and an accessory project tree model. It should be noted that, in other industries, the purpose-built tree model may be a model other than the group project tree model, the host tree project model, and the accessory project tree model.
In an embodiment of the present application, determining the data set of the target tree model may include:
determining basic sub-item data of a basic sub-item;
and determining a data set of the target tree model according to the basic sub-items, the inductive items, the coefficients of the basic sub-items and the basic sub-item data.
In the embodiment of the application, the target tree model, namely the data set of the special tree model, refers to a group of data sets of which the element and the basic sub-element, the basic sub-element data and the basic sub-element coefficients correspond to each other. Specifically, the purpose-made tree-like model, namely the target tree-like model, is matched with the inductive item of the basic sub-item data set, and the data set of the target tree-like model, of which the inductive item and the basic sub-item are completely corresponding, can be obtained.
In an embodiment of the present application, the base sub-item may include:
an accounting document type basic sub-item, a refund type basic sub-item and a refund type basic sub-item.
In the embodiment of the application, the source of the basic sub item data is wider, and the expansibility is strong. The basic sub-items can be divided into three types of accounting document basic sub-items, refund basic sub-items and refund basic sub-items, and correspondingly, the basic sub-item data can comprise accounting document data, refund data and refund data. And collecting all the basic sub-item data to obtain a basic sub-item data set.
In an embodiment of the present application, the cash flow computing system is in communication with an SAP general ledger total database, and determining the base sub-item data for the base sub-item may include:
acquiring first historical data of an SAP general ledger total database and preset control conditions;
and according to preset control conditions, respectively summarizing the first historical data into the accounting document base sub-items to obtain the base sub-item data of the accounting document base sub-items.
In the embodiment of the application, the accounting document data comprises cash payment, tax payment, bill payment, asset outflow, external collection, tax return and the like, and the cash flow computing system of the embodiment of the application is communicated with the SAP general ledger total database, the accounting document data is derived from the historical data of the related document in the SAP general ledger total database, namely, the first historical data, and the first historical data is respectively summarized into accounting document base sub-items according to a plurality of preset management and control conditions, so that the base sub-item data of the accounting document base sub-items can be obtained. The preset control conditions include, but are not limited to, account sleeve control conditions, subject control conditions, reason code control, loan identification control, and the like.
In the embodiment of the present application, the cash flow computing system is further respectively in communication with the SAP ledger database and the first preset database, the basic sub-item data of the refund type basic sub-item includes first refund data and second refund data, and determining the basic sub-item data may further include:
acquiring second historical data of the SAP ledger database, and taking the second historical data as first refund data;
and acquiring first preset data of a first preset database in an ETL mode, and taking the first preset data as second refund data.
In the embodiment of the application, the refund type data comprises host refund, overseas refund, accessory refund and the like. The refund data can be divided into internal refund data and external refund data, namely first refund data and second refund data according to data sources, wherein the first refund data, namely the internal refund data, is derived from historical data of related refunds in an SAP (service agent) ledger database; in the embodiment of the present application, the second refund data, that is, the external data, is derived from a related external database, that is, a first preset database, and in the embodiment of the present application, related data may be obtained from the first preset database as the second refund data by using an ETL (Extract-Transform-Load) method.
In an embodiment of the present application, the cash flow computing system is further in communication with a second preset database, and determining the base sub-item data may further include:
and acquiring second preset data of a second preset database in an ETL mode, and taking the second preset data as basic sub-item data of the funding type basic sub-item.
In the embodiment of the present application, the payment data may include financing payment, mortgage payment, and three-party payment, and in the embodiment of the present application, the relevant data may be obtained from a second preset database by using an ETL (Extract-Transform-Load) method as the base sub-item data of the payment base sub-item. It should be noted that the second preset database is an external database.
Fig. 2 schematically illustrates a block diagram of a cash flow computing system in accordance with an embodiment of the present application. As shown in fig. 2, an embodiment of the present application provides a cash flow computing system, which may include:
a memory 210 configured to store instructions; and
the processor 220 is configured to invoke instructions from the memory 210 and to implement the above-described methods of cash flow calculation when the instructions are executed.
Specifically, in an embodiment of the present application, the processor 220 may be configured to:
acquiring a dependency table of cash flow items, wherein the dependency table comprises a dependency relationship and a scene switch;
establishing a dependency model of the cash flow project according to the dependency relationship;
obtaining an initial tree model through drilling analysis according to the dependency model;
determining a target tree model according to the scene switch and the initial tree model;
determining a data set of the target tree model;
and determining cash flow of the cash flow project according to the data set of the target tree model.
Further, the processor 220 may be further configured to:
determining basic sub-items and inductive items of the dependency model;
drilling the inductive items layer by layer according to the dependency paths of the dependency models to obtain basic sub-items corresponding to the inductive items and coefficients of the basic sub-items;
and determining an initial tree model according to the inductive items and the basic sub-items corresponding to the inductive items and the coefficients of the basic sub-items.
Further, the processor 220 may be further configured to:
determining basic sub-item data of a basic sub-item;
and determining a data set of the target tree model according to the basic sub-items, the inductive items, the coefficients of the basic sub-items and the basic sub-item data.
In an embodiment of the present application, the base sub-item includes:
an accounting document type basic sub-item, a refund type basic sub-item and a refund type basic sub-item.
Further, the processor 220 may be further configured to:
acquiring first historical data of an SAP general ledger total database and preset control conditions;
and according to preset control conditions, respectively summarizing the first historical data into the accounting document base sub-items to obtain the base sub-item data of the accounting document base sub-items.
Further, the processor 220 may be further configured to:
acquiring second historical data of the SAP ledger database, and taking the second historical data as first refund data;
and acquiring first preset data of a first preset database in an ETL mode, and taking the first preset data as second refund data.
Further, the processor 220 may be further configured to:
and acquiring second preset data of a second preset database in an ETL mode, and taking the second preset data as basic sub-item data of the funding type basic sub-item.
In an embodiment of the present application, the target tree model includes:
a group project tree model, a host tree project model, and an accessory project tree model.
Through the technical scheme, the dependency list of the cash flow item is obtained, wherein the dependency list comprises a dependency relationship and a scene switch; establishing a dependency model of the cash flow project according to the dependency relationship; obtaining an initial tree model through drilling analysis according to the dependency model; determining a target tree model according to the scene switch and the initial tree model; determining a data set of the target tree model; and determining cash flow of the cash flow project according to the data set of the target tree model. The application passes through the algorithm of drilling analysis, so that a user can generate a calculation formula for each cash flow item only by configuring the dependency relationship among each cash flow item, the workload of the user for early service confirmation is reduced, the efficiency is higher, and the expansibility of the later cash flow item change work is increased.
Embodiments of the present application also provide a machine-readable storage medium having stored thereon instructions for causing a machine to perform the above-described method of cash flow calculation.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that 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 one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (10)
1. A method of cash flow computing, characterized by being applied to a cash flow computing system, the method comprising:
acquiring a dependency table of cash flow items, wherein the dependency table comprises a dependency relationship and a scene switch;
establishing a dependency model of the cash flow project according to the dependency relationship;
obtaining an initial tree model through drilling analysis according to the dependency model;
determining a target tree model according to the scene switch and the initial tree model;
determining a dataset of the target tree model;
and determining the cash flow of the cash flow project according to the data set of the target tree model.
2. The method of claim 1, wherein obtaining an initial tree model from the dependency model via a drill-in analysis comprises:
determining basic sub-items and inductive items of the dependency model;
drilling the summary items layer by layer according to the dependency paths of the dependency models to obtain basic sub-items corresponding to the summary items and coefficients of the basic sub-items;
and determining an initial tree model according to the inductive item, the basic sub-item corresponding to the inductive item and the coefficient of the basic sub-item.
3. The method of claim 2, wherein the determining the dataset of the target tree model comprises:
determining base sub-item data of the base sub-item;
and determining a data set of the target tree model according to the basic sub-item, the inductive item, the coefficient of the basic sub-item and the basic sub-item data.
4. A method according to claim 3, wherein the base sub-item comprises:
an accounting document type basic sub-item, a refund type basic sub-item and a refund type basic sub-item.
5. The method of claim 4, wherein the cash flow computing system is in communication with an SAP general ledger database, the determining base sub-item data for the base sub-item comprising:
acquiring first historical data and preset control conditions of the SAP general ledger total database;
and according to the preset control conditions, respectively summarizing the first historical data into the accounting document base sub-items to obtain base sub-item data of the accounting document base sub-items.
6. The method of claim 4, wherein the cash flow computing system is further in communication with an SAP ledger database and a first preset database, respectively, the base sub-item data of the refund type base sub-item comprising first refund data and second refund data, the determining the base sub-item data further comprising:
acquiring second historical data of the SAP ledger database, and taking the second historical data as the first refund data;
and acquiring first preset data of the first preset database in an ETL mode, and taking the first preset data as the second refund data.
7. The method of claim 4, wherein the cash flow computing system is further in communication with a second preset database, the determining the base sub-item data further comprising:
and acquiring second preset data of the second preset database in an ETL mode, and taking the second preset data as basic sub-item data of the funding type basic sub-item.
8. The method of claim 1, wherein the target tree model comprises:
a group project tree model, a host tree project model, and an accessory project tree model.
9. A cash flow computing system, comprising:
a memory configured to store instructions; and
a processor configured to invoke the instructions from the memory and when executing the instructions is capable of implementing the method of cash flow calculation according to any one of claims 1 to 8.
10. A machine-readable storage medium having stored thereon instructions for causing a machine to perform the method of cash flow calculation according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310723024.9A CN116882916A (en) | 2023-06-16 | 2023-06-16 | Cash flow calculating method and cash flow calculating system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310723024.9A CN116882916A (en) | 2023-06-16 | 2023-06-16 | Cash flow calculating method and cash flow calculating system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116882916A true CN116882916A (en) | 2023-10-13 |
Family
ID=88255846
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310723024.9A Pending CN116882916A (en) | 2023-06-16 | 2023-06-16 | Cash flow calculating method and cash flow calculating system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116882916A (en) |
-
2023
- 2023-06-16 CN CN202310723024.9A patent/CN116882916A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110471949B (en) | Data blood margin analysis method, device, system, server and storage medium | |
| US20110196767A1 (en) | Hierarchical transaction filtering | |
| CN108256113B (en) | Data blood relationship mining method and device | |
| CN108959510B (en) | Partition level connection method and device for distributed database | |
| US10642838B2 (en) | Real-time or event-based analysis of process data | |
| CN110389989B (en) | Data processing method, device and equipment | |
| CN110442598A (en) | A kind of data query method and apparatus | |
| CN104050291A (en) | Parallel processing method and system for account balance data | |
| CN116882916A (en) | Cash flow calculating method and cash flow calculating system | |
| US20050137946A1 (en) | Use of separate rib ledgers in a computerized enterprise resource planning system | |
| CN110275798A (en) | Block chain data processing method, device, server and storage medium | |
| CN116468259A (en) | Workflow configuration method and device based on rule engine | |
| CN116167870A (en) | Cost management system for insurance business | |
| CN105678475A (en) | Early-warning method and device for risk | |
| CN114817209A (en) | Monitoring rule processing method and device, processor and electronic equipment | |
| US10453143B2 (en) | Computing architecture for managed-account transactions | |
| TWI630496B (en) | Data storage method and system thereof | |
| US10762568B2 (en) | Computing architecture for managed-account transactions | |
| US20190266526A1 (en) | Multi-dimensional organization of data for efficient analysis | |
| CN105893393B (en) | Data save method and device | |
| US20230342710A1 (en) | Intelligent manufacturing division system | |
| CN111192137B (en) | Multi-dimensional balance management method and system based on business scene | |
| CN113449005B (en) | Account management method and device | |
| US10475124B2 (en) | Computing architecture for managed-account transactions | |
| CN116797136A (en) | Data analysis method, processor and machine-readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |