CN115357623A - Intelligent organization method, system and medium for multidimensional cube data - Google Patents
Intelligent organization method, system and medium for multidimensional cube data Download PDFInfo
- Publication number
- CN115357623A CN115357623A CN202211056800.6A CN202211056800A CN115357623A CN 115357623 A CN115357623 A CN 115357623A CN 202211056800 A CN202211056800 A CN 202211056800A CN 115357623 A CN115357623 A CN 115357623A
- Authority
- CN
- China
- Prior art keywords
- data
- financial
- information
- dimension
- business
- 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
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2453—Query optimisation
-
- 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
- G06F16/26—Visual data mining; Browsing structured data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/12—Accounting
- G06Q40/125—Finance or payroll
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/14—Image acquisition
- G06V30/148—Segmentation of character regions
- G06V30/153—Segmentation of character regions using recognition of characters or words
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Computational Linguistics (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Mathematical Physics (AREA)
- Technology Law (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an intelligent organization method, a system and a medium of multidimensional cube data. In addition, the invention can improve the data fusion degree of the business finance data, enhance the collaboration degree of the business finance data and enable an enterprise decision maker to better organize and manage business and financial data by establishing the business finance cube data model, thereby improving the analysis efficiency of the decision maker on the enterprise data and further making an intelligent enterprise decision more effectively.
Description
Technical Field
The invention relates to the field of multidimensional data, in particular to an intelligent organization method, system and medium of multidimensional cube data.
Background
With the continuous maturity of big data related technologies, data is regarded as an asset and is valued by more and more enterprises, and in order to effectively utilize the data asset, data management becomes a problem of key attention of each enterprise at present. Data management is the process of formulating business-driven data policies, data ownership, data monitoring, data standards, and data guidance schemes throughout the life cycle of enterprise data. By implementing a data management scheme, more intelligent data-driven decisions can be made more efficiently.
In addition, with the development of enterprises, the data volume in various business systems in the enterprises is larger and larger, the data dimension is also increased, and various data organization scenes are also more and more complex. With the increase of product data dimensions of enterprises, the difficulty of comprehensive analysis of data is also increased, and for enterprise decision makers, how to efficiently and reasonably analyze enterprise data, how to further understand the current business state of the enterprise through data analysis, and make a better decision for subsequent enterprise development are problems to be solved urgently.
Disclosure of Invention
In order to solve at least one technical problem, the invention provides an intelligent organization of multi-dimensional cube data.
The invention provides a method for intelligently organizing multidimensional cube data in a first aspect, which comprises the following steps:
acquiring business document image data, and performing image character recognition according to the business document image data to obtain initial business data;
performing multi-dimensional data analysis according to the initial service data to generate service data dimension category information and service data caliber information;
performing multidimensional data model analysis and establishment according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and importing initial service data into the service data cube model;
performing corresponding financial data dimension analysis according to the business data cube model to obtain a financial data cube model;
and displaying the business data cube model and the financial data cube model according to a preset mode.
In this scheme, the acquiring of the image data of the service document, and performing image character recognition according to the image data of the service document to obtain initial service data specifically include:
acquiring business document image data, and performing character characteristic area identification according to the business document image data to obtain a character image area;
performing service data identification according to the text image area to obtain service description data and service numerical data;
and analyzing and sorting the service description data and the service numerical data to obtain initial service data.
In this scheme, the multidimensional data analysis is performed according to the initial service data to generate service data dimension category information and service data caliber information, and the method specifically includes:
performing data category analysis on the initial service data to generate a plurality of dimensional information;
according to the service logic, carrying out dimensionality priority ordering on the multiple dimensionality information to obtain service data dimensionality category information;
and obtaining standard information of the service data according to the service category of the initial service data, and obtaining specific caliber information of the service data according to the standard information.
In this scheme, the multidimensional data model analysis and establishment are performed according to the service data dimension category information and the service data aperture information to obtain a service data cube model, and the initial service data is imported into the service data cube model, specifically:
determining the number of dimensions and confirming the dimension relation according to the dimension category information of the service data to obtain a preliminary service data cube model;
establishing a data rule for each dimension in the preliminary business data cube model according to business data caliber information to obtain a business data cube model;
and filling the initial service data into the service data cube model according to the data rules in the service data cube model.
In this scheme, the corresponding financial data dimension analysis is performed according to the business data cube model to obtain a financial data cube model, which specifically comprises:
performing corresponding financial data dimension analysis according to the business data cube model to generate business and financial fusion dimension information;
acquiring financial document image data;
performing image character recognition according to the image data of the financial document to obtain initial financial data;
performing financial data dimension analysis and data standard analysis according to the initial financial data to obtain financial data dimension category information and financial data caliber information;
and according to the financial data dimension category information and the financial data caliber information, combining the industry and property fusion dimension information to obtain a financial data cube model.
In this scheme, carry out corresponding financial data dimension analysis according to business data cube model, obtain financial data cube model, still include:
importing the initial financial data into a financial data cube model;
acquiring a business data cube model;
according to the business and financial fusion dimension information, carrying out dimension query and fusion data acquisition on the business data cube model and the financial data cube model to obtain a business and financial cube data model;
acquiring user query dimension information;
if the query dimension information belongs to the industry and property fusion dimension information, performing data query in a industry and property cube data model according to the query dimension information to obtain multi-dimensional result data;
and carrying out cube data model conversion on the multi-dimensional result data to obtain a result cube model, and carrying out data display on the result cube model according to a preset mode.
In this scheme, carry out corresponding financial data dimension analysis according to business data cube model, obtain financial data cube model, still include:
performing product data analysis according to the initial service data and the initial financial data to obtain corresponding product data dimension information and product data caliber information;
constructing a product data cube model according to product data dimension information and product data caliber information;
performing data anomaly detection on the product data according to the product data caliber information to obtain anomalous data information;
performing data dimension positioning according to the abnormal data information to obtain abnormal data dimension information;
according to the abnormal data dimension information, performing dimension query from the business data cube model and the financial data cube model, and obtaining corresponding dimension data according to a query result;
and generating abnormal repairing data according to the dimension data, and repairing the abnormal data according to the repairing data.
The second aspect of the present invention also provides an intelligent organization system for multidimensional cube data, the system comprising: the intelligent organization method program of the multidimensional cube data is implemented by the following steps when the intelligent organization method program of the multidimensional cube data is executed by the processor:
acquiring business document image data, and performing image character recognition according to the business document image data to obtain initial business data;
performing multi-dimensional data analysis according to the initial service data to generate service data dimension category information and service data caliber information;
performing multidimensional data model analysis and establishment according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and importing initial service data into the service data cube model;
performing corresponding financial data dimension analysis according to the business data cube model to obtain a financial data cube model;
and displaying the business data cube model and the financial data cube model according to a preset mode.
In this scheme, the dimensional analysis of the corresponding financial data is performed according to the business data cube model to obtain a financial data cube model, which specifically comprises:
performing corresponding financial data dimension analysis according to the business data cube model to generate business and financial fusion dimension information;
acquiring financial document image data;
performing image character recognition according to the image data of the financial document to obtain initial financial data;
performing financial data dimension analysis and data standard analysis according to the initial financial data to obtain financial data dimension category information and financial data caliber information;
and according to the financial data dimension category information and the financial data caliber information, combining the industry and property fusion dimension information to obtain a financial data cube model.
The third aspect of the present invention further provides a computer-readable storage medium, which includes a program of an intelligent organization method for multidimensional cube data, and when the program of the intelligent organization method for multidimensional cube data is executed by a processor, the method of the intelligent organization method for multidimensional cube data as described in any one of the above is implemented.
The third aspect of the present invention further provides a computer-readable storage medium, which includes a program of an intelligent organization method for multidimensional cube data, and when the program of the intelligent organization method for multidimensional cube data is executed by a processor, the method of the intelligent organization method for multidimensional cube data as described in any one of the above is implemented.
The invention discloses an intelligent organization method, a system and a medium of multidimensional cube data. In addition, the invention can improve the data fusion degree of the business and financial data, enhance the collaboration degree of the business and financial data and enable an enterprise decision maker to better organize and manage business and financial data by establishing a business and financial cube data model, thereby improving the analysis efficiency of the decision maker on the enterprise data and further making a sensible enterprise decision more effectively.
Drawings
FIG. 1 is a flow chart of a method for intelligently organizing multidimensional cube data according to the invention;
FIG. 2 is a flow chart illustrating the process of acquiring initial service data according to the present invention;
FIG. 3 illustrates a flowchart of the present invention for obtaining a financial data cube model;
FIG. 4 is a block diagram of an intelligent organization system for multidimensional cube data in accordance with the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention, taken in conjunction with the accompanying drawings and detailed description, is set forth below. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
FIG. 1 is a flow chart of a method for intelligently organizing multidimensional cube data according to the invention.
As shown in FIG. 1, a first aspect of the present invention provides a method for intelligently organizing multidimensional cube data, including:
s102, acquiring image data of a business document, and performing image character recognition according to the image data of the business document to obtain initial business data;
s104, performing multi-dimensional data analysis according to the initial service data to generate service data dimension category information and service data caliber information;
s106, carrying out multi-dimensional data model analysis and establishment according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and importing initial service data into the service data cube model;
s108, performing corresponding financial data dimension analysis according to the business data cube model to obtain a financial data cube model;
and S110, displaying the business data cube model and the financial data cube model according to a preset mode.
It should be noted that the caliber information includes specific data types of multiple dimensions, data specifications, data rules, and the like.
Fig. 2 shows a flow chart of acquiring initial service data according to the present invention.
According to the embodiment of the invention, the acquiring of the image data of the business document, the image character recognition according to the image data of the business document, and the acquiring of the initial business data specifically comprise:
s202, acquiring business document image data, and performing character characteristic area identification according to the business document image data to obtain a character image area;
s204, performing service data identification according to the character image area to obtain service description data and service numerical value data;
and S206, carrying out data structure analysis and arrangement on the service description data and the service numerical value data to obtain initial service data.
According to the embodiment of the present invention, the generating of the service data dimension category information and the service data caliber information by performing the multidimensional data analysis according to the initial service data specifically includes:
performing data category analysis on the initial service data to generate a plurality of dimensional information;
according to the service logic, carrying out dimensionality priority ordering on the multiple dimensionality information to obtain service data dimensionality category information;
and obtaining standard information of the service data according to the service category of the initial service data, and obtaining specific caliber information of the service data according to the standard information.
According to the embodiment of the invention, the multidimensional data model analysis and establishment are carried out according to the service data dimension category information and the service data aperture information to obtain a service data cube model, and the initial service data is imported into the service data cube model, which specifically comprises the following steps:
determining the number of dimensions and confirming the dimension relation according to the dimension category information of the service data to obtain a preliminary service data cube model;
establishing a data rule for each dimension in the preliminary business data cube model according to business data caliber information to obtain a business data cube model;
and filling the initial service data into the service data cube model according to the data rules in the service data cube model.
FIG. 3 illustrates a flowchart for obtaining a financial data cube model according to the present invention.
According to the embodiment of the invention, the dimensional analysis of the corresponding financial data is carried out according to the business data cube model to obtain the financial data cube model, which specifically comprises the following steps:
s302, performing corresponding financial data dimension analysis according to the business data cube model to generate business and property fusion dimension information;
s304, acquiring image data of the financial document;
s306, performing image character recognition according to the financial document image data to obtain initial financial data;
s308, performing financial data dimension analysis and data standard analysis according to the initial financial data to obtain financial data dimension category information and financial data caliber information;
and S310, obtaining a financial data cube model by combining the industry and finance fusion dimension information according to the financial data dimension category information and the financial data caliber information.
It should be noted that the business and financial integration dimension information is common dimension data information of business data and financial data. In the financial document image data, the financial document is a financial document corresponding to a business document of the same item.
According to the embodiment of the invention, the performing corresponding financial data dimension analysis according to the business data cube model to obtain the financial data cube model further comprises:
importing the initial financial data into a financial data cube model;
acquiring a business data cube model;
according to the business and financial fusion dimension information, carrying out dimension query and fusion data acquisition on the business data cube model and the financial data cube model to obtain a business and financial cube data model;
acquiring user query dimension information;
if the query dimension information belongs to the industry and property fusion dimension information, performing data query in a industry and property cube data model according to the query dimension information to obtain multi-dimensional result data;
and carrying out cube data model conversion on the multi-dimensional result data to obtain a result cube model, and carrying out data display on the result cube model according to a preset mode.
It should be noted that, in the obtained business and financial cube data model, the business and financial cube data model includes common dimension information and data of business data and financial data, and the business data and the financial data can be more intuitively subjected to data fusion by generating the business and financial cube data model, and a more efficient query object is provided for subsequent query operations.
In addition, the query dimension information generally comprises multi-dimensional data query information, and the data display is performed in a preset mode that space division and conversion are performed according to the dimension of the result cube model, corresponding data are filled one by one, and display is performed through preset terminal equipment. The terminal equipment comprises computer terminal equipment and mobile terminal equipment.
According to the embodiment of the invention, the performing corresponding financial data dimension analysis according to the business data cube model to obtain the financial data cube model further comprises:
performing product data analysis according to the initial service data and the initial financial data to obtain corresponding product data dimension information and product data caliber information;
constructing a product data cube model according to the product data dimension information and the product data caliber information;
performing data anomaly detection on the product data according to the product data caliber information to obtain anomalous data information;
performing data dimension positioning according to the abnormal data information to obtain abnormal data dimension information;
according to the dimension information of the abnormal data, performing dimension query from the business data cube model and the financial data cube model, and obtaining corresponding dimension data according to a query result;
and generating abnormal repairing data according to the dimension data, and repairing the abnormal data according to the repairing data.
It should be noted that the product data cube model has a plurality of product dimension information, including dimension information such as product raw material, supply quantity, sales volume, sales place, sales quarter, etc. And performing data anomaly detection on the product data according to the caliber information of the product data to obtain anomalous data information, wherein due to the fact that abnormal conditions such as data loss, errors and the like can occur in the market of the product data in the storage process, the abnormal conditions can be reasonably repaired by obtaining corresponding business data and financial data.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring query information of different departments of an enterprise;
obtaining a query keyword according to the query information;
dividing the query keywords according to frequency to obtain high-frequency keywords and low-frequency keywords;
importing the high-frequency key words and the low-frequency key words into a cube model for data dimension query to obtain high-frequency dimension data and low-frequency dimension data;
performing dimension structure layering according to the high-frequency dimension data and the low-frequency dimension data to obtain main dimension information and secondary dimension information;
and performing dimension structure reintegration on the cube model according to the primary dimension information and the secondary dimension information to obtain a new cube model.
It should be noted that the cube model includes a product data cube model, a business data cube model, and a financial data cube model. In the method, the query information and the query emphasis of different departments are different in the query information of different departments of the enterprise, corresponding high-frequency and low-frequency dimension information is obtained according to the query high-frequency keywords in the different departments, and the dimension structure of the cube model is reformed according to the high-frequency and low-frequency dimension information, so that the query of the cube model data can be more efficiently carried out, and the data management efficiency of the enterprise is improved.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring a product data cube model;
searching dimension data of sales volume, sales places and sales quarters in the product data cube model to obtain result dimension data;
carrying out sales prediction according to the result dimension data to obtain prediction data based on three dimensions of sales volume, sales places and sales quarters;
cubic data conversion is carried out on the prediction data to obtain a prediction cubic model;
and displaying the prediction cube model according to a preset mode, and generating corresponding sales scheme information according to the prediction cube model.
FIG. 4 is a block diagram of an intelligent organization system for multidimensional cube data in accordance with the present invention.
The second aspect of the present invention also provides an intelligent organization system 4 for multidimensional cube data, which comprises: a memory 41 and a processor 42, wherein the memory includes an intelligent organization method program of multidimensional cube data, and when the intelligent organization method program of multidimensional cube data is executed by the processor, the following steps are implemented:
acquiring business document image data, and performing image character recognition according to the business document image data to obtain initial business data;
performing multi-dimensional data analysis according to the initial service data to generate service data dimension category information and service data caliber information;
performing multidimensional data model analysis and establishment according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and importing initial service data into the service data cube model;
performing corresponding financial data dimension analysis according to the business data cube model to obtain a financial data cube model;
and displaying the business data cube model and the financial data cube model according to a preset mode.
It should be noted that the caliber information includes specific data types of multiple dimensions, data specifications, data rules, and the like.
According to the embodiment of the invention, the acquiring of the image data of the business document, the image character recognition according to the image data of the business document, and the acquiring of the initial business data specifically comprise:
acquiring business document image data, and performing character characteristic area identification according to the business document image data to obtain a character image area;
performing service data identification according to the text image area to obtain service description data and service numerical data;
and analyzing and sorting the service description data and the service numerical data to obtain initial service data.
According to the embodiment of the present invention, the generating of the service data dimension category information and the service data caliber information by performing the multidimensional data analysis according to the initial service data specifically includes:
performing data category analysis on the initial service data to generate a plurality of dimensional information;
according to the service logic, carrying out dimensionality priority ordering on the multiple dimensionality information to obtain service data dimensionality category information;
and obtaining standard information of the service data according to the service category of the initial service data, and obtaining specific caliber information of the service data according to the standard information.
According to the embodiment of the invention, the multidimensional data model analysis and establishment are carried out according to the service data dimension category information and the service data aperture information to obtain a service data cube model, and the initial service data is imported into the service data cube model, which specifically comprises the following steps:
determining the dimension quantity and confirming the dimension relation according to the service data dimension category information to obtain a preliminary service data cube model;
establishing a data rule for each dimension in the preliminary business data cube model according to business data caliber information to obtain a business data cube model;
and filling the initial service data into the service data cube model according to the data rules in the service data cube model.
According to the embodiment of the invention, the dimensional analysis of the corresponding financial data is carried out according to the business data cube model to obtain the financial data cube model, which specifically comprises the following steps:
performing corresponding financial data dimension analysis according to the business data cube model to generate business and financial fusion dimension information;
acquiring financial document image data;
performing image character recognition according to the image data of the financial document to obtain initial financial data;
performing financial data dimension analysis and data standard analysis according to the initial financial data to obtain financial data dimension category information and financial data caliber information;
and according to the financial data dimension category information and the financial data caliber information, combining the industry and property fusion dimension information to obtain a financial data cube model.
It should be noted that the business and financial integration dimension information is common dimension data information of business data and financial data. In the financial document image data, the financial document is a financial document corresponding to a business document of the same item.
According to the embodiment of the invention, the performing corresponding financial data dimension analysis according to the business data cube model to obtain the financial data cube model further comprises:
importing the initial financial data into a financial data cube model;
acquiring a business data cube model;
according to the business and financial fusion dimension information, carrying out dimension query and fusion data acquisition on the business data cube model and the financial data cube model to obtain a business and financial cube data model;
acquiring user query dimension information;
if the query dimension information belongs to the industry and property fusion dimension information, performing data query in a industry and property cube data model according to the query dimension information to obtain multi-dimensional result data;
and carrying out cube data model conversion on the multi-dimensional result data to obtain a result cube model, and carrying out data display on the result cube model according to a preset mode.
It should be noted that, in the obtained industry and property cube data model, the industry and property cube data model includes common dimension information and data of business data and financial data, and the business data and the financial data can be more intuitively subjected to data fusion by generating the industry and property cube data model, and a more efficient query object is provided for subsequent query operations.
In addition, the query dimension information generally comprises multi-dimensional data query information, and the data display is performed in a preset mode that space division and conversion are performed according to the dimension of the result cube model, corresponding data are filled one by one, and display is performed through preset terminal equipment. The terminal equipment comprises computer terminal equipment and mobile terminal equipment.
According to the embodiment of the invention, the performing corresponding financial data dimension analysis according to the business data cube model to obtain the financial data cube model further comprises:
performing product data analysis according to the initial business data and the initial financial data to obtain corresponding product data dimension information and product data caliber information;
constructing a product data cube model according to the product data dimension information and the product data caliber information;
performing data anomaly detection on the product data according to the product data caliber information to obtain anomalous data information;
performing data dimension positioning according to the abnormal data information to obtain abnormal data dimension information;
according to the abnormal data dimension information, performing dimension query from the business data cube model and the financial data cube model, and obtaining corresponding dimension data according to a query result;
and generating abnormal repairing data according to the dimension data, and repairing the abnormal data according to the repairing data.
It should be noted that the product data cube model has a plurality of product dimension information, including dimension information such as product raw material, sales volume, supply volume, shipment volume, and the like. And performing data anomaly detection on the product data according to the caliber information of the product data to obtain anomalous data information, wherein due to the fact that abnormal conditions such as data loss, errors and the like can occur in the market of the product data in the storage process, the abnormal conditions can be reasonably repaired by obtaining corresponding business data and financial data.
The third aspect of the present invention further provides a computer-readable storage medium, which includes a program of an intelligent organization method for multidimensional cube data, and when the program of the intelligent organization method for multidimensional cube data is executed by a processor, the method of the intelligent organization method for multidimensional cube data as described in any one of the above is implemented.
The invention discloses an intelligent organization method, a system and a medium of multidimensional cube data. In addition, the invention can improve the data fusion degree of the business and financial data, enhance the collaboration degree of the business and financial data and enable an enterprise decision maker to better organize and manage business and financial data by establishing a business and financial cube data model, thereby improving the analysis efficiency of the decision maker on the enterprise data and further making a sensible enterprise decision more effectively.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps of implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer-readable storage medium, and when executed, executes the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for intelligently organizing multidimensional cube data is characterized by comprising the following steps:
acquiring business document image data, and performing image character recognition according to the business document image data to obtain initial business data;
performing multi-dimensional data analysis according to the initial service data to generate service data dimension category information and service data caliber information;
performing multidimensional data model analysis and establishment according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and importing initial service data into the service data cube model;
performing corresponding financial data dimension analysis according to the business data cube model to obtain a financial data cube model;
and displaying the business data cube model and the financial data cube model according to a preset mode.
2. The method for intelligently organizing multidimensional cube data according to claim 1, wherein the acquiring of the business document image data and the image character recognition according to the business document image data to obtain initial business data specifically comprise:
acquiring business document image data, and performing character characteristic area identification according to the business document image data to obtain a character image area;
performing service data identification according to the text image area to obtain service description data and service numerical data;
and analyzing and sorting the service description data and the service numerical data to obtain initial service data.
3. The method for intelligently organizing multidimensional cube data according to claim 1, wherein the multidimensional data analysis is performed according to initial business data to generate business data dimension category information and business data caliber information, and specifically comprises:
performing data category analysis on the initial service data to generate a plurality of dimensional information;
according to the service logic, carrying out dimensionality priority ordering on the multiple dimensionality information to obtain service data dimensionality category information;
and obtaining standard information of the service data according to the service category of the initial service data, and obtaining specific caliber information of the service data according to the standard information.
4. The method for intelligently organizing multidimensional cube data according to claim 1, wherein the multidimensional data model is analyzed and established according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and the initial service data is imported into the service data cube model, specifically:
determining the dimension quantity and confirming the dimension relation according to the service data dimension category information to obtain a preliminary service data cube model;
establishing a data rule for each dimension in the preliminary business data cube model according to business data caliber information to obtain a business data cube model;
and filling the initial service data into the service data cube model according to the data rules in the service data cube model.
5. The intelligent organization method of multidimensional cubic data according to claim 1, wherein the dimensional analysis of the corresponding financial data is performed according to the business data cubic model to obtain a financial data cubic model, specifically:
performing corresponding financial data dimension analysis according to the business data cube model to generate business and financial fusion dimension information;
acquiring financial document image data;
performing image character recognition according to the image data of the financial document to obtain initial financial data;
performing financial data dimension analysis and data standard analysis according to the initial financial data to obtain financial data dimension category information and financial data caliber information;
and according to the financial data dimension category information and the financial data caliber information, combining the industry and property fusion dimension information to obtain a financial data cube model.
6. The method of claim 5, wherein the performing a corresponding financial data dimensional analysis based on the business data cube model to obtain a financial data cube model, further comprises:
importing the initial financial data into a financial data cube model;
acquiring a business data cube model;
according to the business and financial fusion dimension information, carrying out dimension query and fusion data acquisition on the business data cube model and the financial data cube model to obtain a business and financial cube data model;
acquiring user query dimension information;
if the query dimension information belongs to the industry and property fusion dimension information, performing data query in a industry and property cube data model according to the query dimension information to obtain multi-dimensional result data;
and performing cube data model conversion on the multidimensional result data to obtain a result cube model, and displaying the result cube model according to a preset mode.
7. The method of claim 1, wherein the performing a corresponding financial data dimensional analysis based on the business data cube model to obtain a financial data cube model, further comprises:
performing product data analysis according to the initial business data and the initial financial data to obtain corresponding product data dimension information and product data caliber information;
constructing a product data cube model according to the product data dimension information and the product data caliber information;
performing data anomaly detection on the product data according to the product data caliber information to obtain anomalous data information;
performing data dimension positioning according to the abnormal data information to obtain abnormal data dimension information;
according to the abnormal data dimension information, performing dimension query from the business data cube model and the financial data cube model, and obtaining corresponding dimension data according to a query result;
and generating abnormal repairing data according to the dimension data, and repairing the abnormal data according to the repairing data.
8. An intelligent organization system for multidimensional cube data, the system comprising: the intelligent organization method program of the multidimensional cube data is executed by the processor to realize the following steps:
acquiring business document image data, and performing image character recognition according to the business document image data to obtain initial business data;
performing multi-dimensional data analysis according to the initial service data to generate service data dimension category information and service data caliber information;
performing multidimensional data model analysis and establishment according to the service data dimension category information and the service data caliber information to obtain a service data cube model, and importing initial service data into the service data cube model;
performing corresponding financial data dimension analysis according to the business data cube model to obtain a financial data cube model;
and displaying the business data cube model and the financial data cube model according to a preset mode.
9. The system according to claim 8, wherein the dimensional analysis of the financial data is performed according to a business data cube model to obtain a financial data cube model, and specifically comprises:
performing corresponding financial data dimension analysis according to the business data cube model to generate business and financial fusion dimension information;
acquiring financial document image data;
performing image character recognition according to the image data of the financial document to obtain initial financial data;
performing financial data dimension analysis and data standard analysis according to the initial financial data to obtain financial data dimension category information and financial data caliber information;
and according to the financial data dimension category information and the financial data caliber information, combining the industry and property fusion dimension information to obtain a financial data cube model.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium includes therein an intelligent organization method program of multidimensional cube data, which when executed by a processor, implements the steps of the intelligent organization method of multidimensional cube data according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211056800.6A CN115357623A (en) | 2022-08-31 | 2022-08-31 | Intelligent organization method, system and medium for multidimensional cube data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211056800.6A CN115357623A (en) | 2022-08-31 | 2022-08-31 | Intelligent organization method, system and medium for multidimensional cube data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115357623A true CN115357623A (en) | 2022-11-18 |
Family
ID=84005262
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211056800.6A Pending CN115357623A (en) | 2022-08-31 | 2022-08-31 | Intelligent organization method, system and medium for multidimensional cube data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115357623A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115952240A (en) * | 2023-03-15 | 2023-04-11 | 深圳市迪博企业风险管理技术有限公司 | Financial data compliance examination method and device based on block chain |
-
2022
- 2022-08-31 CN CN202211056800.6A patent/CN115357623A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115952240A (en) * | 2023-03-15 | 2023-04-11 | 深圳市迪博企业风险管理技术有限公司 | Financial data compliance examination method and device based on block chain |
| CN115952240B (en) * | 2023-03-15 | 2023-06-02 | 深圳市迪博企业风险管理技术有限公司 | Financial data compliance examination method and device based on blockchain |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103513983B (en) | method and system for predictive alert threshold determination tool | |
| CN110659282B (en) | Data route construction method, device, computer equipment and storage medium | |
| CN111178005A (en) | Data processing system, method and storage medium | |
| CN115357623A (en) | Intelligent organization method, system and medium for multidimensional cube data | |
| CN111428007B (en) | Cross-platform based synchronous push feedback method | |
| CN111600761A (en) | Risk alarm analysis merging method based on operation and maintenance service | |
| CN111177206A (en) | Method, device and system for processing pivot table | |
| CN112650816A (en) | Intelligent data analysis visualization system and method | |
| CN117035687A (en) | Power grid business fixed asset process configuration method, system and computer storage medium | |
| CN114461705A (en) | Data visualization generation method and device, electronic equipment and storage medium | |
| CN111611230A (en) | Method and device for establishing main data system, computer equipment and storage medium | |
| CN103092900A (en) | Single, mixed-view presentation of related products | |
| CN114862282B (en) | Business and financial cooperative management method and system based on data analysis | |
| CN112182021A (en) | User data query method, device and system | |
| CN116563028A (en) | AI-based report data verification method, system and storage medium | |
| CN116303628A (en) | Alarm data query method, system and equipment based on elastic search | |
| US20050216449A1 (en) | System for obtaining, managing and providing retrieved content and a system thereof | |
| CN113450142B (en) | Clustering analysis method and device for power consumption behaviors of power customers | |
| CN114860819A (en) | Method, device, equipment and storage medium for constructing business intelligent system | |
| CN101702731A (en) | Information display method, system and associated equipment | |
| CN111582799B (en) | Method and device for constructing object portrait | |
| CN115438036B (en) | Data redundancy processing system and method for unified index database of power grid | |
| CN117391715B (en) | Battery cell two-dimensional code identification and tracing method based on machine vision | |
| CN117785984A (en) | Data extraction method, device, electronic equipment and storage medium | |
| CN116991810A (en) | Report data compression method, device, equipment and 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 |