CN117408826A

CN117408826A - Financial data processing method and device, electronic equipment and readable storage medium

Info

Publication number: CN117408826A
Application number: CN202311315001.0A
Authority: CN
Inventors: 刘小东
Original assignee: Yonyou Network Technology Co Ltd
Current assignee: Yonyou Network Technology Co Ltd
Priority date: 2023-10-11
Filing date: 2023-10-11
Publication date: 2024-01-16

Abstract

The application discloses a financial data processing method and device, electronic equipment and a readable storage medium, and relates to the technical field of data processing. Wherein, financial data processing method includes: data collection is performed on financial data of at least one management system. And (3) carrying out data cleaning on the acquired financial data, and carrying out data conversion on the data after data cleaning to obtain a data table. And calculating target financial indexes based on the data table, and summarizing the target financial indexes based on the target dimension to obtain target financial data. Visual presentation is performed based on the data sheet or the target financial data.

Description

Financial data processing method and device, electronic equipment and readable storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a financial data processing method and apparatus, an electronic device, and a readable storage medium.

Background

With the popularity of ERP (Enterprise Resource Planning ) systems, the need for data analysis by enterprises has increased. The supervision of the financial data of subordinate enterprises by large enterprise groups or industries and government supervision departments is the main work and means of management, and the financial indexes are reported by the subordinate enterprises in the past, and the indexes are summarized and analyzed at the monitoring end.

The current supervision requirements on subordinate enterprises are increased, the requirements on data are also more real-time and detailed, the requirements are directly accessed to the business systems of the subordinate enterprises, and the initial certificates can be summarized at the management end in real time and traced.

Meanwhile, the enterprise faces another difficulty, and subordinate enterprises of the group enterprise and the supervision department generally independently purchase the ERP system, so that the group enterprise and the supervision department face the requirement of integrating, merging, summarizing and analyzing financial data of a plurality of heterogeneous ERP systems.

Disclosure of Invention

An object of embodiments according to the present application is to provide a financial data processing method and apparatus, an electronic device, and a readable storage medium, which can solve the problem that in the related art, financial data of different management systems cannot be automatically identified and cannot be integrated, summarized, and analyzed.

In a first aspect, according to an embodiment of the present application, there is provided a financial data processing method, including: data collection is performed on financial data of at least one management system. And (3) carrying out data cleaning on the acquired financial data, and carrying out data conversion on the data after data cleaning to obtain a data table. And calculating target financial indexes based on the data table, and summarizing the target financial indexes based on the target dimension to obtain target financial data. Visual presentation is performed based on the data sheet or the target financial data.

In a second aspect, according to an embodiment of the present application, there is provided a financial data processing apparatus including an acquisition module, a merging module, a summarizing module, and a visualization module. The acquisition module is used for carrying out data acquisition on financial data of at least one management system. The merging module is used for cleaning the data of the acquired financial data, and converting the data after cleaning the data to obtain a data table. And the summarizing module is used for calculating the target financial index based on the data table, and summarizing the target financial index based on the target dimension to obtain the target financial data. The visualization module is used for performing visual display based on the data table or the target financial data.

In a third aspect, there is provided according to an embodiment of the present application an electronic device comprising a processor and a memory storing a program or instructions executable on the processor, the program or instructions implementing the steps of the financial data processing method as in the first aspect when executed by the processor.

In a fourth aspect, according to an embodiment of the present application there is provided a readable storage medium having stored thereon a program or instructions which when executed by a processor perform the steps of the financial data processing method as in the first aspect.

In some embodiments of the present application, the operations of collecting, data merging, summarizing, etc. of the financial data can be automatically completed only by accessing the management system through the processes of data collection, data cleaning, data conversion, calculation of the target financial data, and visual display, thereby saving manpower and material resources.

Drawings

FIG. 1 shows one of the flow diagrams of a financial data processing method provided in accordance with an embodiment of the present application;

FIG. 2 shows a second flow diagram of a financial data processing method provided in accordance with an embodiment of the present application;

FIG. 3 shows a block diagram of a financial data processing apparatus provided in accordance with an embodiment of the present application;

FIG. 4 shows a block diagram of an electronic device provided in accordance with an embodiment of the present application;

fig. 5 shows a schematic hardware structure of an electronic device according to an embodiment of the present application;

FIG. 6 illustrates an overall framework of financial data processing provided in accordance with embodiments of the present application;

FIG. 7 illustrates a service component schematic provided in accordance with an embodiment of the present application;

fig. 8 shows a data model schematic of a DWD layer provided according to an embodiment of the application.

The correspondence between the reference numerals and the component names in fig. 3 to 5 is:

100: a financial data processing device; 110: an acquisition module; 120: a merging module; 130: a summarizing module; 140: a visualization module; 1000: an electronic device; 1002: a processor; 1004: a memory; 1100: an electronic device; 1101: a radio frequency unit; 1102: a network module; 1103: an audio output unit; 1104: an input unit; 11041: a graphics processor; 11042: a microphone; 1105: a sensor; 1106: a display unit; 11061: a display panel; 1107: a user input unit; 11071: a touch panel; 11072: other input devices; 1108: an interface unit; 1109: a memory; 1110: a processor.

Detailed Description

Technical solutions according to embodiments of the present application will be clearly described below with reference to the drawings in embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application are within the scope of the protection of the present application.

The terms first, second and the like in the description and in the claims, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.

The following describes in detail, with reference to fig. 1 to 8, a financial data processing method and apparatus, an electronic device, and a readable storage medium according to embodiments of the present application through specific embodiments and application scenarios thereof.

According to an embodiment of the present application, there is provided a financial data processing method, fig. 1 shows one of flow charts of the financial data processing method provided according to an embodiment of the present application, as shown in fig. 1, including:

step S102, data acquisition is performed on financial data of at least one management system.

And step S104, data cleaning is carried out on the acquired financial data, and data conversion is carried out on the data after data cleaning to obtain a data table.

And S106, calculating target financial indexes based on the data table, and summarizing the target financial indexes based on the target dimension to obtain target financial data.

And S108, performing visual display based on the data table or the target financial data.

It can be appreciated that there are multiple ERP systems in the market, wherein the financial data among the multiple ERP systems are heterogeneous financial data, and the heterogeneous financial data cannot be directly subjected to statistics or visual display.

In some embodiments of the present application, the management system may include various ERP systems, and perform data collection on financial data of different ERP systems, where the collected financial data is heterogeneous data, and the data collection process is an automatic identification process, that is, automatically identifying the financial data of different ERP systems, specifically, linking to an ERP system database, and automatically finding a required table and data. And financial data of the ERP system is automatically acquired, so that a data basis can be provided for processing of subsequent heterogeneous financial data.

In some embodiments of the present application, the financial data collection of the management system supports incremental and full data updating, and the above manner can more flexibly collect data for a newly added management system or a management system after updating data.

In some embodiments of the present application, data collection is performed on financial data of at least one management system, and the financial data is automatically imported into a plurality of bins to complete data warehousing, where the plurality of bins includes a source pasting layer (ODS layer), a standard layer (DWD layer and DWS layer), and the ODS (Operational Data Store, operation data storage) layer implements data collection on financial data of at least one management system, and the ODS layer performs a backup on heterogeneous financial data in the plurality of bins (data warehouse), and typically, each heterogeneous data source is provided with an independent ODS layer data corresponding to the heterogeneous data source.

In some embodiments of the present application, data cleansing is performed on collected financial data, data after cleansing is performed on data to obtain a data table, the above process is implemented through a DWD layer, after cleansing and transforming the financial data collected by an ODS layer by the DWD (Data WareHouse Detail, data detail) layer, a set of data tables is obtained by merging, and unified transforming of the financial data can enable heterogeneous financial data of different units to be summarized. In some embodiments of the present application, the heterogeneous financial data is automatically cleaned and converted into a standardized modeling process, through which the heterogeneous financial data can be finally uniformly extracted into a standard data model, and the standard data model is a data table.

It is understood that the target financial index may be some financial index set based on the application scenario requirements. In some embodiments of the present application, for the data sheet obtained by the DWD layer, the target financial index is calculated, and then the target financial index is summarized according to the target dimension to obtain the target financial data. The DWS layer is a standard index aggregation layer, and stores target financial indexes and gathers data according to target dimensions.

In some embodiments of the present application, visual presentation is performed based on a data table or target financial data, wherein the visual presentation is created based on a standard layer data structure that is fixed even though the ODS layer changes, and the visual presentation of the upper layer remains unchanged. The standard layer is solidified, the data sources are automatically processed from the ODS layer to the standard layer, and the implementation of the enterprise heterogeneous financial data analysis can be highly automated, so that the implementation efficiency is greatly improved.

In the related art, in the method for collecting the report to realize the financial data summarization, the report implementation process needs to send down a report sample, and a large amount of manual participation processes such as manual check of periodic manual tabulation and the like have large resource consumption. In some embodiments of the application, through the processes of data acquisition, data cleaning, data conversion, calculation of target financial data and visual display, the operations of acquisition, data merging, summarization and the like of the financial data of the heterogeneous ERP system can be automatically completed only by accessing the ERP system of a subordinate enterprise, so that manpower and material resources are saved. In some embodiments of the present application, financial data analysis summary may be implemented, data may be drilled directly down to detail data, data may be extracted in timed increments, and data acquisition is more realistic, with detail data backtracking capabilities.

In some embodiments of the present application, a set of extraction enterprise ERP system financial data services is provided that model financial data in a standardized manner, preset target financial data and visually present. During practical application, the ERP system is directly accessed, financial data extraction, conversion, summarization and finally the financial visual instrument board is displayed.

In some embodiments of the present application, optionally, before the data acquisition of the financial data of the at least one management system, further comprises:

for different management systems, corresponding service components are constructed, and the service components are used for data acquisition, data cleaning and data conversion.

In some embodiments of the present application, for different management systems, it is necessary to build corresponding service components, which can be used for data collection, data cleansing and data conversion. Specifically, the data acquisition is designed by adopting a strategy mode, different ERP data acquisition services are packaged into independent service components, the difficulty of identifying and extracting heterogeneous data is packaged in the service components, the service components use a uniform interface, the different ERP data acquisition service components inherit the same interface, the external use of the data acquisition service components adopts the same method, the data acquisition service components can be dynamically expanded in the mode, and when the financial data acquisition of different management systems is needed to be added later, the data acquisition can be realized by adding the service components, and the financial data of more management systems can be automatically identified by adding the service components. For data cleaning and data conversion, specifically, the data cleaning and conversion are respectively packaged into service components according to ERP product types, interfaces are called uniformly, and later, service components can be added for new ERP product types, and calling methods remain unchanged.

For example, for the existing management system NCC (friend NC product), tide GS4 (tide GS4 product), SAP S/4 (tide GS4 product), and the like, as shown in fig. 7, appDataIuput is an data collection interface, absDataInput is a common virtual base class for data collection that encapsulates a common method, NCCDataInput is an interface implementation class for collecting NCC (friend NC product) data, SAPDataIuput is an interface implementation class for collecting SAP (tide GS4 product) data, GSDataIuput is an interface implementation class for collecting tide (tide GS4 product), and absDataInput implementation interfaces AppDataIuput, NCCDataInput, SAPDataIuput, GSDataIuput are respectively integrated from virtual classes absDataInput.

In some embodiments of the application, data acquisition, data cleaning and data conversion are realized by a service component, so that the application scene is wider, more management systems can be combined, and the user experience is improved.

In some embodiments of the present application, optionally, fig. 2 shows a second flow chart of a financial data processing method provided according to an embodiment of the present application, as shown in fig. 2, and performing data conversion on data after data cleaning, including:

step S202, uniformly converting the organization codes in the organization unit table, and replacing the organization codes in the dimension table and the fact table by using the converted organization codes.

Step S204, unified conversion is performed on the accounting period.

Step S206, unified conversion is carried out on the general dimension.

Step S208, the elastic dimensions are converted uniformly.

Step S210, performing unified conversion on the subject dimensions.

Step S212, uniformly converting the fact table.

Step S214, the statistical table is subjected to unified conversion.

In some embodiments of the present application, data cleaning is performed on the collected financial data, data conversion is performed on the data after data cleaning, and the process of obtaining the data table is implemented through a DWD layer, where the DWD layer is a relational database structure using a subject balance table and an auxiliary balance table as core fact tables, and the subject balance table stores the balance of each month of the subject in a fixed dimension according to organization, subject, item, product, department, current, period, and currency, and performs a calculation according to a month extension. Based on the fact that the enterprise accounting subject codes are uniformly coded and released by the country in the first stage, different enterprise financial data can be summarized according to subjects. The DWD layer performs summarization calculation on the certificates from different heterogeneous financial systems, and calculates the balance of the subject according to the dimensions of the subject, the organization, the year and the like.

In some embodiments of the present application, performing data conversion on the data after data cleansing may include:

(1) Organization table treatment: and uniformly converting the organization codes in the organization unit table, replacing the organization codes in the dimension table and the fact table by using the converted organization codes, and processing the organization table to ensure that the organization codes of the heterogeneous system are unique.

(2) Processing during accounting: and (3) uniformly converting the accounting periods, merging the accounting periods of different management systems, and carrying out the unique annual and month and large sorting.

(3) General dimension processing: the universal dimension is uniformly converted, for example, the currency, the objects to and from, departments, staff, stock and items are all stored by organization except the currency.

(4) Elastic dimension treatment: and uniformly converting the elastic dimensions, checking the certificates, reserving a plurality of elastic dimensions in a subject balance list, and setting the number according to the application scene.

(5) Performing subject dimension treatment: the dimension of the subjects is converted uniformly, the subjects are stored according to organization, the subject ID must be unique, and standard subject codes of each system need to be found.

(6) Facts table processing: and uniformly converting the fact list, wherein the fact list comprises a certificate main list, a certificate detail list and a cash flow list.

(7) And (3) statistical table processing: and uniformly converting the statistical tables, including an auxiliary balance table and a subject balance table. Calculating auxiliary subject balances from the vouchers month by month according to accounting periods, and generating a subject balance list from the auxiliary balance list according to organizations, periods, currencies and subject summaries.

In some embodiments of the present application, optionally, the data table includes: subject balance table, auxiliary balance table, subject table, item table, product table, customer table, cash flow table, voucher master table, voucher detail table, organization unit table, vendor table, department table, personnel table and currency table.

As shown in FIG. 8, the data model of the DWD layer includes a subject balance table, an auxiliary balance table, a subject table, a project table, a product table, a customer table, a cash flow table, a voucher master table, a voucher detail table, an organization unit table, a vendor table, a department table, a personnel table, and a currency table.

The subject balance list comprises: PKORG (organization Key), PKVouccher (credential Key), PKDetail (credential detail ID), year (Year), period (month), PKAccount (subject Key), PKCurrency (Main currencies), PKproduct (product Key), PKCurrency (currency Key), PKProject (project Key), DEBITAMOUNT (borrowing Period occurrence amount), DEBITQUANTATY (borrowing Period occurrence amount), CREDITTAMOUNTY (lending Period occurrence amount), LOCALDEBITAMOUNT (borrowing Period occurrence amount), CRTQUUANTITY (lending Period occurrence amount) localc refu, pdebitamountt, pdebitquant, plocaldebt, plocalalc refu, pcrendimontamountt, fdebitamountt, fcretamountt, flocaldbitamountt, caldbitamountt, and caderbitux.

The subject table includes: PKORG (organization key), PKACCOUNT (subject key), ACCOUNTCODE (subject code), accountame (subject name), ACCOUNTLEVEL (subject rank), sourctable (source table), sourcid (source record row ID).

The item table includes: PKORG (organization key), pkprocject (project key), proctcode (project code), procctname (project name).

The product table includes: PKORG (organization key), PKPRODUCT (product key), product code (product code), product name (product name).

The client table includes: PKORG (organization key), pkstomer (customer key), CUSTOMERCODE (customer code), CUSTOMERNAME (customer name).

The cash flow meter includes: PKORG (organization primary bond).

The credential master table includes: PKORG (organization key), PKVOUCHER (voucher key), vouchercule (voucher code), YEAR (YEAR), PERIOD (month), PREPAREDATE (billing date).

The credential details table includes: PKORG (organization key), PKVOUCHER (certificate key), PKDEFAIL (certificate line key), YEAR (YEAR), PERIOD (month), PKACCOUNTs (subject key), DETAILLINE (certificate line number), pkcurrencies (currency key), PKPRODUCT (product key), PKPRODUCT key, PRICE (unit PRICE), EXCRATE (exchange rate), debtq uantity (debit amount), debtq mobile (debit amount), creditor (credit amount), localdebttmobile (debit amount), localfudit (credit amount), direct (DIRECTION), oppossesbj (custom extended key) are added to the chinese meaning corresponding to each english in the table.

The organization unit table includes: PKORG (organization primary key), CODE (organization CODE), NAME (organization NAME).

The vendor table includes: PKORG (organization key), pksupport (vendor key), support code, support name.

The department table includes: PKORG (organization key), PKDEPARTMENT (department key), departmertcode (department code), DEPARTMENTNAME (department name).

The arrows point to the foreign key relationships between the tables:

(1) Voucher details table: the foreign key association organizes a unit table, a supplier table, a department table, a personnel table, a currency table, a subject table, a project table, a product table, and a customer table.

(2) Certificate master table: the foreign key is associated with an organization unit table.

(3) Subject balance table: the foreign key association organizes a unit table, a subject table, an item table, a product table, and a client table.

In some embodiments of the present application, optionally, calculating the target financial index based on the data table includes:

selecting at least one subject in the data table, acquiring data corresponding to the subject, and calculating a target financial index based on the data.

In some embodiments of the present application, the target financial index is set according to the requirement, the target financial index is obtained from the DWD subject balance table and calculated, and since the DWD layer structure is fixed, the calculation rule of the target financial index is unchanged, and as long as the DWD layer has data, the DWS layer can obtain the result according to the preset calculation rule.

In some embodiments of the present application, the DWS layer stores data that aggregates target financial metrics according to target dimensions, and because enterprise subject codes have nationally uniform specifications, target financial metrics calculated according to subject balance tables are consistent and can be aggregated and scaled between enterprises.

In some embodiments of the present application, the summary of data from the DWD layer to the DWS layer is mainly to calculate the target financial index, and the calculation of the target financial index may use a fixed-side SQL statement to obtain one or more data of the initial stage, the present stage lender, the present stage borrower, the present stage balance, and the like of a specific department from the subject balance table of the DWD layer, and summary the data according to the set of target dimensions, and store the data in the DWS index summary table, so as to obtain the target financial data.

The correspondence between field names and comments in the DWS layer data model is shown in table 1, where dws_englist_name is an index english name, dws_Chinese_name is an index chinese name, result_value is a calculation result, organization is an organization table, year is accounting year, period is accounting period, and dt is time.

Table 1 correspondence between field names and comments in DWS layer data model

Field name	Annotating
		dws_english_name	English name of index
dws_chinese_name	Index Chinese name
		result_value	Calculation result
Organinzation	Organization table
		year	Accounting years
period	During accounting
		dt	Time

The English name of the index and the Chinese name of the index uniquely define the dimension of the index, the organization table, the accounting year and the accounting period, the result_value is the calculation interface of the index under the three dimensions, and the time is defined as the execution time of the index calculation result.

In some embodiments of the present application, optionally, the target dimension includes at least one of:

organization dimension, year dimension, month dimension.

In some embodiments of the present application, the target financial indicators are aggregated according to the target dimensions to obtain target financial data, which may provide data for visual presentation.

In some embodiments of the present application, optionally, the visually displaying includes:

a financial instrument panel is generated. And/or

And generating a financial statement. And/or

A financial report is generated.

In some embodiments of the present application, the results of the visual presentation may generate a financial dashboard, financial statement, and/or financial report. Through visual display, the user can more intuitively know financial data, and user experience is improved.

In one exemplary embodiment, as shown in fig. 6, a financial data processing method is provided according to an embodiment of the present application, for example, for existing management systems NCC (using friend NC product), wave GS4 (wave GS4 product), SAP S/4 (si epsi S/4 product), etc., each management system is provided with financial data, the data source includes NCC, wave GS4, SAP S/4, the number of bins includes a data patch source layer (ODS layer), a number of bins standard layer. The data visualization comprises a financial analysis dashboard, a financial report and a financial report, the ODS layer backs up heterogeneous financial data in a plurality of bins, and generally each heterogeneous data source is provided with independent ODS data corresponding to the heterogeneous data, and the ODS layer comprises ODS NCC, ODS LC and ODS SAP, wherein the ODS NCC corresponds to NCC, the ODS LC corresponds to Langchao GS4, and the ODS SAP corresponds to SAP S/4. The ODS NCC includes a voucher master table, a subject table, a department profile, a voucher detail table, an account book setting, customer and vendor settings, general ledgers, auxiliary accounting settings, project profiles, cash flow tables, auxiliary accounting data, employee profiles, organizational tables, currency tables, inventory profiles, period tables, corporate tables, and custom profiles. The ODS LC includes a voucher master table, a subject table, a staff file, a voucher detail table, a currency table, an inventory file, a general ledger, a department file, a period table, an auxiliary check account, customer and vendor, an organization table and a project file. The ODS SAP includes a voucher master table, a department file, a voucher detail table, customer and vendor, an organization table, a project file, a period table, a employee file, a currency table, an inventory file, and a subject table. The financial standard layer includes a voucher master table, an organization table, a subject table, a department file, a staff file, a dictionary-table, a voucher detail table, a cash flow table, a currency table, a transaction table, an inventory file, a dictionary-field, a general ledger, an auxiliary ledger, a period table, a project file, a file extension table, and a dictionary-relationship. The index convergence layer comprises monetary funds, tax payables, management fees, research and development fees, receivables, investment benefits, main industry revenues, sales fees, financial fees, sales costs, accounts payables, fixed asset depreciation and the like, the system converts financial data from the ODS layer into financial data of the standard layer, performs data calculation of security subjects above the standard layer financial data to form a financial index layer, and the financial index layer provides presentation data for the visualization layer.

According to the financial data processing method provided by the embodiment of the application, the execution subject may be a financial data processing apparatus. The financial data processing apparatus provided according to the embodiments of the present application is described in the embodiments of the present application taking as an example a financial data processing apparatus performing a financial data processing method.

According to an embodiment of the present application, there is provided a financial data processing apparatus 100, and fig. 3 shows a block diagram of a structure of the financial data processing apparatus provided according to an embodiment of the present application, and as shown in fig. 3, the financial data processing apparatus 100 includes an acquisition module 110, a merging module 120, a summarizing module 130, and a visualization module 140. The acquisition module 110 is configured to perform data acquisition on financial data of at least one management system. The merging module 120 is configured to perform data cleansing on the collected financial data, and perform data conversion on the data after cleansing to obtain a data table. The summarizing module 130 is configured to calculate a target financial index based on the data table, and summarize the target financial index based on the target dimension, to obtain target financial data. The visualization module 140 is configured to perform a visual presentation based on the data table or the target financial data.

In some embodiments of the application, through the processes of data acquisition, data cleaning, data conversion, calculation of target financial data and visual display, the operations of acquisition, data merging, summarization and the like of the financial data of the heterogeneous ERP system can be automatically completed only by accessing the ERP system of a subordinate enterprise, so that manpower and material resources are saved. In some embodiments of the present application, financial data analysis summary may be implemented, data may be drilled directly down to detail data, data may be extracted in timed increments, and data acquisition is more realistic, with detail data backtracking capabilities.

The financial data processing apparatus 100 provided according to the embodiments of the present application may implement each process of the foregoing financial data processing method embodiment, and may achieve the same technical effects, and for avoiding repetition, a detailed description is omitted herein.

The financial data processing apparatus according to embodiments of the present application may be an electronic device or may be a component in an electronic device, such as an integrated circuit or chip. The electronic device may be a terminal, or may be other devices than a terminal. By way of example, the electronic device may be a cell phone, tablet computer, notebook computer, palm computer, vehicle mounted electronic device, mobile internet appliance (Mobile Internet Device, MID), augmented reality (augmented reality, AR)/Virtual Reality (VR) device, robot, wearable device, ultra-mobile personal computer, UMPC, netbook or personal digital assistant (personal digital assistant, PDA), etc., but may also be a server, network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (TV), teller machine or self-service machine, etc., without specific limitation according to embodiments of the present application.

The financial data processing apparatus in accordance with embodiments of the present application may be an apparatus having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited according to the embodiments of the present application.

The financial data processing device provided according to the embodiments of the present application can implement each process implemented by the embodiments of the foregoing financial data processing method, and in order to avoid repetition, a detailed description is omitted here.

Optionally, as shown in fig. 4, an electronic device 1000 is further provided according to an embodiment of the present application, where the electronic device 1000 includes a processor 1002 and a memory 1004, and a program or an instruction that can be executed on the processor 1002 is stored in the memory 1004, and when the program or the instruction is executed by the processor 1002, the steps of the foregoing financial data processing method embodiment are implemented, and the same technical effects can be achieved, so that repetition is avoided and no further description is provided herein.

It should be noted that, the electronic device in the embodiment according to the present application includes the mobile electronic device and the non-mobile electronic device described above.

Fig. 5 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.

The electronic device 1100 includes, but is not limited to: radio frequency unit 1101, network module 1102, audio output unit 1103, input unit 1104, sensor 1105, display unit 1106, user input unit 1107, interface unit 1108, memory 1109, and processor 1110.

Those skilled in the art will appreciate that the electronic device 1100 may further include a power source (e.g., a battery) for powering the various components, which may be logically connected to the processor 1110 by a power management system, such as to perform functions for managing charge, discharge, power consumption, etc., via the power management system. The electronic device structure shown in fig. 5 does not constitute a limitation of the electronic device, and the electronic device may include more or less components than shown, or may combine certain components, or may be arranged in different components, which are not described in detail herein.

Wherein the processor 1110 is configured to perform data collection on financial data of at least one management system.

And the processor 1110 is configured to perform data cleansing on the collected financial data, and perform data conversion on the data after cleansing to obtain a data table.

And a processor 1110, configured to calculate a target financial index based on the data table, and aggregate the target financial index based on the target dimension, to obtain target financial data.

A processor 1110 for visual presentation based on a data table or target financial data.

The processor 1110 provided according to the embodiments of the present application may implement each process of the foregoing embodiments of the financial data processing method, and may achieve the same technical effects, so that repetition is avoided and detailed description is omitted herein.

It should be appreciated that in accordance with embodiments of the present application, the input unit 1104 may include a graphics processor (Graphics Processing Unit, GPU) 11041 and a microphone 11042, the graphics processor 11041 processing image data of still pictures or video obtained by an image capture device (e.g., a camera) in a video capture mode or an image capture mode. The display unit 1106 may include a display panel 11061, and the display panel 11061 may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like. The user input unit 1107 includes at least one of a touch panel 11071 and other input devices 11072. The touch panel 11071 is also referred to as a touch screen. The touch panel 11071 may include two parts, a touch detection device and a touch controller. Other input devices 11072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and so forth, which are not described in detail herein.

The memory 1109 may be used to store software programs as well as various data. The memory 1109 may mainly include a first memory area storing programs or instructions and a second memory area storing data, wherein the first memory area may store an operating system, application programs or instructions (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like. Further, the memory 1109 may include volatile memory or nonvolatile memory, or the memory 1109 may include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM), static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (ddr SDRAM), enhanced SDRAM (Enhanced SDRAM), synchronous DRAM (SLDRAM), and Direct RAM (DRRAM). Memory 1109 in embodiments in accordance with the present application includes, but is not limited to, these and any other suitable types of memory.

Processor 1110 may include one or more processing units; optionally, the processor 1110 integrates an application processor that primarily processes operations involving an operating system, user interface, application programs, and the like, and a modem processor that primarily processes wireless communication signals, such as a baseband processor. It will be appreciated that the modem processor described above may not be integrated into the processor 1110.

According to the embodiment of the present application, a readable storage medium is further provided, and a program or an instruction is stored on the readable storage medium, where the program or the instruction realizes each process of the above financial data processing method embodiment when being executed by a processor, and the same technical effect can be achieved, so that repetition is avoided, and no description is repeated here.

The processor is a processor in the electronic device in the above embodiment. Readable storage media include computer readable storage media such as computer readable memory ROM, random access memory RAM, magnetic or optical disks, and the like.

According to the embodiment of the application, a chip is further provided, the chip includes a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running a program or instructions, the processes of the above financial data processing method embodiment can be realized, the same technical effects can be achieved, and in order to avoid repetition, the description is omitted here.

It should be understood that chips mentioned according to embodiments of the present application may also be referred to as system-on-chip, chip system, or system-on-chip chips, etc.

According to an embodiment of the present application, there is provided a computer program product stored in a storage medium, the program product being executed by at least one processor to implement the respective processes of the above-mentioned embodiments of the financial data processing method, and to achieve the same technical effects, and for avoiding repetition, a detailed description is omitted herein.

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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solutions of the present application may be embodied essentially or in a part contributing to the prior art in the form of a computer software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods of the embodiments of the present application.

The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those of ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are also within the protection of the present application.

Claims

1. A method of financial data processing comprising:

data acquisition is carried out on financial data of at least one management system;

data cleaning is carried out on the acquired financial data, and data conversion is carried out on the data after data cleaning to obtain a data table;

calculating a target financial index based on the data table, and summarizing the target financial index based on a target dimension to obtain target financial data;

and visually displaying based on the data table or the target financial data.

2. A method of processing financial data according to claim 1, comprising, prior to said data collection of financial data of at least one management system:

and constructing corresponding service components for different management systems, wherein the service components are used for data acquisition, data cleaning and data conversion.

3. A method of processing financial data according to claim 1, wherein said data conversion of the data after cleaning comprises:

uniformly converting the organization codes in the organization unit table, and replacing the organization codes in the dimension table and the fact table by using the converted organization codes;

performing unified conversion on accounting periods;

unified conversion is carried out on the general dimension;

the elastic dimension is uniformly converted;

uniformly converting the dimensions of subjects;

uniformly converting the fact table;

and uniformly converting the statistical table.

4. A method of processing financial data according to claim 1, wherein the data table comprises: subject balance table, auxiliary balance table, subject table, item table, product table, customer table, cash flow table, voucher master table, voucher detail table, organization unit table, vendor table, department table, personnel table and currency table.

5. A method of processing financial data according to claim 1, wherein said calculating a target financial index based on said data table comprises:

and selecting at least one subject from the data table, acquiring data corresponding to the subject, and calculating the target financial index based on the data.

6. A financial data processing method according to claim 1, wherein the target dimension comprises at least one of:

organization dimension, year dimension, month dimension.

7. A method of processing financial data according to any one of claims 1 to 6, wherein said visually displaying comprises:

generating a financial instrument panel; and/or

Generating a financial statement; and/or

A financial report is generated.

8. A financial data processing apparatus, comprising:

the acquisition module is used for carrying out data acquisition on financial data of at least one management system;

the merging module is used for carrying out data cleaning on the acquired financial data, and carrying out data conversion on the data after data cleaning to obtain a data table;

the summarizing module is used for calculating target financial indexes based on the data table, summarizing the target financial indexes based on target dimensions, and obtaining target financial data;

and the visualization module is used for performing visual display based on the data table or the target financial data.

9. An electronic device, comprising:

a memory having stored thereon programs or instructions;

a processor for implementing the steps of the financial data processing method as claimed in any one of claims 1 to 7 when said program or instructions are executed.

10. A readable storage medium having stored thereon a program or instructions which when executed by a processor carries out the steps of the financial data processing method as claimed in any one of claims 1 to 7.