CN116955458A - Method and device for collaborative analysis of data and computer readable storage medium - Google Patents

Method and device for collaborative analysis of data and computer readable storage medium Download PDF

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Publication number
CN116955458A
CN116955458A CN202310952744.2A CN202310952744A CN116955458A CN 116955458 A CN116955458 A CN 116955458A CN 202310952744 A CN202310952744 A CN 202310952744A CN 116955458 A CN116955458 A CN 116955458A
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China
Prior art keywords
data
collaborative
analysis
analyzed
collaborative analysis
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CN202310952744.2A
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Chinese (zh)
Inventor
罗静
敦建征
张培
陈绪福
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CRSC Institute of Smart City Research and Design Co Ltd
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CRSC Institute of Smart City Research and Design Co Ltd
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Priority to CN202310952744.2A priority Critical patent/CN116955458A/en
Publication of CN116955458A publication Critical patent/CN116955458A/en
Pending legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/258—Data format conversion from or to a database
    • 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
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9536—Search customisation based on social or collaborative filtering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • 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
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/242—Query formulation
    • G06F16/2433—Query languages
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The invention provides a method, a device and a computer readable storage medium for collaborative analysis of data, wherein the method comprises the following steps: acquiring a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse; acquiring a service model corresponding to the data source; and carrying out collaborative analysis on the data to be collaborative analyzed through the business model. The method, the device and the computer readable storage medium can solve the problem that the existing data analysis method cannot carry out collaborative analysis on multiple data sources.

Description

Method and device for collaborative analysis of data and computer readable storage medium
Technical Field
The invention relates to a method, a device and a computer readable storage medium for collaborative analysis of data.
Background
Along with the continuous progress of science and information technology, the rapid development of interconnection technology has obvious influence of big data on enterprises, the ubiquitous data enables the business of the enterprises to be diversified, refined and personalized, the cost is saved for the enterprises, the market share can be improved, and huge opportunities are brought, but the existing data analysis method is usually aimed at data analysis of a single data source, and cannot meet the requirement of enterprise business on collaborative analysis of data of multiple data sources.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method, a device and a computer readable storage medium for collaborative analysis of data, wherein the method, the device and the computer readable storage medium are used for collaborative analysis of data by using a business model corresponding to a data source after the data source is acquired through a data warehouse, so as to solve the problem that collaborative analysis of multiple data sources cannot be performed in the existing data analysis method.
In a first aspect, the present invention provides a method of collaborative analysis of data, comprising:
acquiring a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse;
acquiring a service model corresponding to the data source;
and carrying out collaborative analysis on the data to be collaborative analyzed through the business model.
Preferably, dimensions and metrics required by the collaborative analysis, and relationships between the dimensions and metrics, are defined in the business model, wherein the dimensions include a base dimension and a formula dimension, and the metrics include a base metric and a formula metric.
Preferably, before the collaborative analysis is performed on the data to be collaborative analyzed through the service model, the method further includes:
constructing a target query statement according to the measurement and/or the dimension and/or the relation between the dimension and the measurement and/or the preset condition;
the collaborative analysis of the data to be collaborative analyzed through the business model specifically comprises the following steps:
and inquiring the data to be cooperatively analyzed through the service model according to the target inquiry statement so as to obtain a cooperatively analyzed result.
Preferably, the target query comprises a single query, a multi-query, a joint query, and a multi-dimensional data query;
the multidimensional data query includes at least one of block filtering, grouping, ranking, and alerting.
Preferably, before the data sources corresponding to the data to be collaborative analyzed are obtained from the pre-established collaborative analysis data warehouse, the method further comprises:
acquiring a service requirement corresponding to a target service;
generating a logic model according to the service demand;
and converting each parameter in the logic model into a corresponding service parameter so as to convert the logic model into the service model.
Preferably, after the query is performed on the data to be cooperatively analyzed through the service model according to the target query statement to obtain a result of cooperative analysis, the method further includes:
and displaying the result of the collaborative analysis in a report form.
In a second aspect, the present invention provides an apparatus for collaborative analysis of data, comprising:
the acquisition module is used for acquiring a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse;
the model module is connected with the acquisition module and is used for acquiring a service model corresponding to the data source;
and the analysis module is connected with the warehouse module and is used for carrying out collaborative analysis on the data to be collaborative analyzed through the business model.
In a third aspect, the present invention provides an apparatus for collaborative analysis of data, comprising a memory having stored therein a computer program and a processor arranged to run the computer program to implement the method of collaborative analysis of data described in the first aspect above.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the method of collaborative analysis of data according to the first aspect described above.
The invention provides a method, a device and a computer readable storage medium for collaborative analysis of data, wherein a data source corresponding to the data to be collaborative analyzed is firstly obtained from a pre-established collaborative analysis data warehouse; then obtaining a service model corresponding to the data source; and then carrying out collaborative analysis on the data to be collaborative analyzed through the service model, wherein the data is collaborative analyzed by using the service model corresponding to the data source after the data source is acquired from the data warehouse, so that the problem that collaborative analysis on multiple data sources cannot be carried out in the existing data analysis method is solved.
Drawings
FIG. 1 is a flow chart of a method for collaborative analysis of data according to embodiment 1 of the present invention;
FIG. 2 is a schematic structural diagram of a device for collaborative analysis of data according to embodiment 2 of the present invention;
fig. 3 is a schematic structural diagram of an apparatus for collaborative analysis of data according to embodiment 3 of the present invention.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the following detailed description of the embodiments of the present invention will be given with reference to the accompanying drawings.
It is to be understood that the specific embodiments and figures described herein are merely illustrative of the invention, and are not limiting of the invention.
It is to be understood that the various embodiments of the invention and the features of the embodiments may be combined with each other without conflict.
It is to be understood that only the portions relevant to the present invention are shown in the drawings for convenience of description, and the portions irrelevant to the present invention are not shown in the drawings.
It should be understood that each unit and module in the embodiments of the present invention may correspond to only one physical structure, may be formed by a plurality of physical structures, or may be integrated into one physical structure.
It will be appreciated that, without conflict, the functions and steps noted in the flowcharts and block diagrams of the present invention may occur out of the order noted in the figures.
It is to be understood that the flowcharts and block diagrams of the present invention illustrate the architecture, functionality, and operation of possible implementations of systems, devices, nodes, methods according to various embodiments of the present invention. Where each block in the flowchart or block diagrams may represent a unit, module, segment, code, or the like, which comprises executable instructions for implementing the specified functions. Moreover, each block or combination of blocks in the block diagrams and flowchart illustrations can be implemented by hardware-based systems that perform the specified functions, or by combinations of hardware and computer instructions.
It should be understood that the units and modules related in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, for example, the units and modules may be located in a processor.
Example 1:
the present embodiment provides a method for collaborative analysis of data, as shown in fig. 1, the method includes:
step S1: and acquiring a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse.
In this embodiment, all data to be incorporated into collaborative analysis may be defined as a data source, for example, may be data of a user information management system, or may be any other third party data, including Excel tables, log files, and even socialized unstructured data, where the database type of the data source may support three databases, namely SQL Server, oracle, and Mysql.
The data in the data source may be transformed, sorted, and restored to the collaborative analysis data warehouse as necessary before entering the collaborative analysis data warehouse, for example, the data may be subjected to ETL (Extract-Transform-Load), and extraction-transformation-loading) to form data that is beneficial to analysis.
It should be noted that, the collaborative analysis data warehouse can manage the data of each heterogeneous data source database together, and can finish the rejection and format conversion of the data with poor quality, and finally finish the conversion of the source data organization form according to the modeling mode, so as to better support the visual analysis to the front end. The input mode of the collaborative analysis data warehouse is various data sources, and the final output is used for the directions of data analysis, data mining, data report and the like of enterprises.
Step S2: and acquiring a service model corresponding to the data source.
In this embodiment, each data source corresponds to a corresponding database, each service model corresponds to a database connection, and before generating a service model, it is necessary to confirm that a database connection is created, and support management of database connections, including adding new connections, modifying existing connections, removing existing connections, and testing connections.
Optionally, before the data source corresponding to the data to be cooperatively analyzed is obtained from the pre-established cooperative analysis data warehouse, the method further includes:
acquiring a service requirement corresponding to a target service;
generating a logic model according to the service demand;
and converting each parameter in the logic model into a corresponding service parameter so as to convert the logic model into the service model.
In this embodiment, the service requirement is the actual requirement of the user service department and the planning of the service, and before the service model is created, the service requirement of the service department needs to be fully known.
In this embodiment, after the service requirement is obtained, the relevant attribute of the logic model is configured according to the service requirement, the data definition in the data source is transferred to the logic model, the many-to-many relationship is decomposed, and the logic model can be audited by the user. The construction of the logic model is most important in the implementation of the collaborative analysis data warehouse, is a bridge and a platform for communication between service demand personnel and technical personnel, can directly reflect the actual demands of service departments and the planning of the services, and outlines the data blueprint and the planning of the whole service departments through the relation between entities.
In this embodiment, after the logic model is generated, a suitable physical structure (i.e., converting the logic model into a service model) is selected for the application environment, including a suitable storage structure and a suitable storage method. The conversion of a logical model into a physical model (i.e. business model) mainly comprises: converting the entity name into a table name; converting the attribute name into a column name, and determining the attribute of the column; in the creation of the physical model, the attributes of the columns must be specified, including column name, data type, whether they are null, length, etc. After the physical model is determined, planning is also required for storage locations of data, allocation of storage space, and the like.
It should be noted that, after the service model is generated, the service model is also supported to be managed, including modifying the existing service model, opening the existing service model to edit and remove the existing service model.
Optionally, dimensions and metrics required by the collaborative analysis, and relationships between the dimensions and metrics are defined in the business model, wherein the dimensions include a base dimension and a formula dimension, and the metrics include a base metric and a formula metric.
In this embodiment, the metrics include a basic metric and a formula metric, where the basic metric is a metric preset by the service model, such as an inventory-in quantity, a debit occurrence quantity, a receivables amount, and an end-of-period inventory quantity; the formula metrics are formulas defined by the user in the report by metrics, dimensions, aggregation functions, operators, etc., such as user-defined unit price, net profit, number of days to forecast delivery, number of orders not shipped.
The dimensions comprise basic dimensions and formula dimensions, wherein the basic dimensions are metrics preset by a service model, such as years, months and customer names; the formula dimension is a formula defined by a user in a report through measurement, dimension, aggregation function, operator and the like, such as month defined by the user.
Step S3: and carrying out collaborative analysis on the data to be collaborative analyzed through the business model.
In this embodiment, the business model may reflect the granularity and angle of the analysis data in the data analysis process through dimensions, such as commonly used clients and products, and the selectable types include characters, dates, boolean and numerical values, and for the commonly used dimensions are the types of characters or dates, the definition of the dimensions conforms to the expression of the SQL (Structured Query Language ) grammar; the business model may also describe data information such as the number, amount, number of transactions, etc. by metrics, such as the number of orders and amount of orders that are frequently used, and the expression may use an aggregation function, where the aggregation function may be: summing sum, counting count, averaging avg, minimum value min, maximum value max.
Optionally, before the collaborative analysis is performed on the data to be collaborative analyzed through the service model, the method further includes:
constructing a target query statement according to the measurement and/or the dimension and/or the relation between the dimension and the measurement and/or the preset condition;
the collaborative analysis of the data to be collaborative analyzed through the business model specifically comprises the following steps:
and inquiring the data to be cooperatively analyzed through the service model according to the target inquiry statement so as to obtain a cooperatively analyzed result.
Optionally, the target query includes a single query, a multi-query, a joint query, and a multi-dimensional data query;
the multidimensional data query includes at least one of block filtering, grouping, ranking, and alerting.
In this embodiment, metrics, dimensions, and conditions required for collaborative analysis may be selected in a collaborative analysis data warehouse to perform a single query; multiple queries can be built for the same business model, and multiple queries can also be built across business models; a federated query is a set of queries that work together to return a single result, and all queries in the set can be based on the same business model, with the federated query resulting in a data set that would otherwise be undefined or unavailable.
In multidimensional queries, block filtering is to filter data in a collaborative analysis data warehouse, including data of interest in block elements, so as to focus on analyzing particular values of interest, e.g., a filter may be defined to let a report display only values of particular customers or sales periods; grouping allows the user to split the report information into smaller, easier to understand portions and to count the data for each portion, e.g., grouping warehouses to analyze inventory ingress and egress for each warehouse; ranking can find out a plurality of pieces of data before or after the report form based on the specified condition, for example, the report form analysis shows the income data situation based on the client classification, and then the ranking function can rank the data in the report form according to the ranking; ordering, namely ordering objects displayed in a report, directly influencing the order of the objects displayed in the analysis, applying the ordering to any object displayed in the report, organizing results according to time sequence for dimension ordering, and rapidly looking up the largest and smallest results for measurement ordering; the alarm can send out early warning signals in the report form by means of various display forms for the operation risks which occur or possibly occur in each link of the enterprise, and provides decision basis for users.
Optionally, after the query is performed on the data to be cooperatively analyzed through the service model according to the target query statement to obtain a result of cooperative analysis, the method further includes:
and displaying the result of the collaborative analysis in a report form.
In this embodiment, a report may be customized by using a business model according to different data, so as to implement multiple expression modes such as a table, a line graph, a pie chart, a funnel graph, a thermodynamic diagram, and the like, and may interface with a BI (Business Intelligence ), and display the data on a tool selected by a user, so as to implement a purpose of performing collaborative analysis on the data in the collaborative analysis data warehouse.
According to the method, the system and the equipment, the digital accurate marketing is realized by utilizing the data collaborative analysis, the user image can be depicted by deeply analyzing the purchase behavior, the consumption habit and the like of the user, the data collaborative analysis result is converted into the client management strategy which can be operated and executed, so that the increase of sales income is realized, the management of finance and manpower can be realized by the data collaborative analysis, the expenditure of various costs and expenses is controlled, the effect of reducing the cost is realized, the real-time monitoring of enterprises can be helped, the active early warning can be carried out on the part deviating from the budget and the numerical value deviating from the normal range, and the enterprise risk is reduced.
The method for collaborative analysis of data provided in embodiment 1 includes first obtaining a data source corresponding to data to be collaborative analyzed from a pre-established collaborative analysis data warehouse; then obtaining a service model corresponding to the data source; and then carrying out collaborative analysis on the data to be collaborative analyzed through the service model, wherein the data is collaborative analyzed by using the service model corresponding to the data source after the data source is acquired from the data warehouse, so that the problem that collaborative analysis on multiple data sources cannot be carried out in the existing data analysis method is solved.
Example 2:
as shown in fig. 2, the present embodiment provides an apparatus for collaborative analysis of data, which is configured to perform the method for collaborative analysis of data, including:
an obtaining module 11, configured to obtain a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse;
the model module 12 is connected with the acquisition module 11 and is used for acquiring a service model corresponding to the data source;
and the analysis module 13 is connected with the warehouse module 12 and is used for carrying out collaborative analysis on the data to be collaborative analyzed through the business model.
Preferably, dimensions and metrics required by the collaborative analysis, and relationships between the dimensions and metrics, are defined in the business model, wherein the dimensions include a base dimension and a formula dimension, and the metrics include a base metric and a formula metric.
Preferably, the apparatus further comprises:
the construction module is used for constructing a target query statement according to the measurement and/or the dimension and/or the relation between the dimension and the measurement and/or the preset condition;
the analysis module 13 specifically includes:
and the query unit is used for querying the data to be cooperatively analyzed through the service model according to the target query statement so as to obtain a cooperative analysis result.
Preferably, the target query comprises a single query, a multi-query, a joint query, and a multi-dimensional data query;
the multidimensional data query includes at least one of block filtering, grouping, ranking, and alerting.
Preferably, the apparatus further comprises:
the demand module is used for acquiring the service demand corresponding to the target service;
the logic module is used for generating a logic model according to the service requirements;
and the service module is used for converting each parameter in the logic model into a corresponding service parameter so as to convert the logic model into the service model.
Preferably, the apparatus further comprises:
and the report module is used for displaying the collaborative analysis result in a report form.
Example 3:
as shown in fig. 3, the present embodiment provides an apparatus for collaborative analysis of data, which is configured to perform the above-described collaborative analysis data method, and includes a memory 21 and a processor 22, wherein the memory 21 stores a computer program, and the processor 22 is configured to execute the computer program to perform the collaborative analysis data method in embodiment 1.
The memory 21 is connected to the processor 22, the memory 21 may be a flash memory, a read-only memory, or other memories, and the processor 22 may be a central processing unit or a single chip microcomputer.
Example 4:
the present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of collaborative analysis of data in embodiment 1 described above.
Computer-readable storage media include volatile or nonvolatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program modules or other data. Computer-readable storage media includes, but is not limited to, RAM (Random Access Memory ), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory, charged erasable programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact Disc Read-Only Memory), digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
The apparatus and computer-readable storage medium for collaborative analysis of data provided in embodiments 2 to 4 first obtain a data source corresponding to data to be collaborative analyzed from a pre-established collaborative analysis data warehouse; then obtaining a service model corresponding to the data source; and then carrying out collaborative analysis on the data to be collaborative analyzed through the service model, wherein the data is collaborative analyzed by using the service model corresponding to the data source after the data source is acquired from the data warehouse, so that the problem that collaborative analysis on multiple data sources cannot be carried out in the existing data analysis method is solved.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.

Claims (9)

1. A method of collaborative analysis of data, comprising:
acquiring a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse;
acquiring a service model corresponding to the data source;
and carrying out collaborative analysis on the data to be collaborative analyzed through the business model.
2. The method of collaborative analysis data according to claim 1, wherein dimensions and metrics required for the collaborative analysis, and relationships between dimensions and metrics, are defined in the business model, wherein the dimensions include a base dimension and a formula dimension, and the metrics include a base metric and a formula metric.
3. The method of collaborative analysis data according to claim 2, wherein prior to collaborative analysis of the data to be collaborative analyzed by the business model, the method further comprises:
constructing a target query statement according to the measurement and/or the dimension and/or the relation between the dimension and the measurement and/or the preset condition;
the collaborative analysis of the data to be collaborative analyzed through the business model specifically comprises the following steps:
and inquiring the data to be cooperatively analyzed through the service model according to the target inquiry statement so as to obtain a cooperatively analyzed result.
4. The method of collaborative analysis of data according to claim 3, wherein the targeted queries include single queries, multi-queries, federated queries, and multi-dimensional data queries;
the multidimensional data query includes at least one of block filtering, grouping, ranking, and alerting.
5. The method of collaborative analysis data according to claim 1, wherein prior to obtaining a data source corresponding to the data to be collaborative analyzed from a pre-established collaborative analysis data warehouse, further comprising:
acquiring a service requirement corresponding to a target service;
generating a logic model according to the service demand;
and converting each parameter in the logic model into a corresponding service parameter so as to convert the logic model into the service model.
6. The method for collaborative analysis of data according to claim 3, wherein after the query is performed on the data to be collaborative analyzed through the business model according to the target query statement to obtain a collaborative analysis result, the method further comprises:
and displaying the result of the collaborative analysis in a report form.
7. An apparatus for collaborative analysis of data, comprising:
the acquisition module is used for acquiring a data source corresponding to the data to be cooperatively analyzed from a pre-established cooperative analysis data warehouse;
the model module is connected with the acquisition module and is used for acquiring a service model corresponding to the data source;
and the analysis module is connected with the warehouse module and is used for carrying out collaborative analysis on the data to be collaborative analyzed through the business model.
8. An apparatus for collaborative analysis of data comprising a memory and a processor, the memory having stored therein a computer program, the processor being arranged to run the computer program to implement a method of collaborative analysis of data as claimed in any one of claims 1 to 6.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements a method of collaborative analysis of data according to any of claims 1-6.
CN202310952744.2A 2023-07-31 2023-07-31 Method and device for collaborative analysis of data and computer readable storage medium Pending CN116955458A (en)

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