Business economy operation monitoring analysis display construction system

Abstract

The invention provides a business economy operation monitoring analysis display construction system, which belongs to the field of big data acquisition and comprises a data collection module, a data cleaning module, a business economy operation index system construction module, a business economy analysis model construction module and a visual display module. A data resource pool is formed by converging and fusing multi-source data through a big data technology, and a business economy operation monitoring analysis display system is constructed by designing a series of topic models, so that scenes such as business economy operation situation awareness, prediction and early warning, analysis, research and judgment and work coordination are supported, and the business data governance capability is improved.

Description

Technical Field

[0001] The present invention relates to the fields of big data collection, big data processing and analysis, and big data mining, and in particular to a construction system for monitoring, analyzing and displaying business and economic operations. Background Art

[0002] At present, the economic environment is complex and changeable, instability and uncertainty have significantly increased, and the timeliness and complexity of economic regulation have increased.

[0003] There are many internal information systems in the competent departments, and the traditional line-based working method prevents the effective mining and utilization of data value, hinders decision-making analysis and cross-departmental work collaboration, and is no longer adapted to the new situation and new requirements of digital development.

[0004] like:

[0005] (1) Information islands: The island phenomenon is prominent, business systems are "fighting independently", and data is scattered

[0006] (2) Inconsistent standards: No unified data standards have been established, and the business scope and technical definitions of each system vary greatly.

[0007] (3) Low data quality: The original business system data is of mixed quality, low quality, and inconsistent in data format. A large amount of semi-structured and unstructured data has not been fully mined.

[0008] (4) Data sharing is difficult: Data islands are more obvious, which restricts the integration of resources and the comprehensive integration of application systems.

[0009] (5) Data value is not reflected: Some core businesses rely mainly on manual data collation and analysis, and lack mobile collaborative applications, which seriously restricts the improvement of work efficiency and business collaboration capabilities.

[0010] (6) In terms of data presentation, the degree of visualization is low, the information presentation is not intuitive enough, and the interactivity is poor, which is not conducive to decision makers to quickly obtain key information and make accurate judgments. Summary of the Invention

[0011] In order to solve the above technical problems, the present invention provides a construction system for monitoring, analyzing and displaying the operation of business economy, which aims to gather and integrate multi-source data through big data technology to form a data resource pool, and construct a business economic operation monitoring, analysis and display system by designing a series of theme models to support business economic operation situation awareness, prediction and early warning, analysis and judgment, work collaboration and other scenarios, and improve business data governance capabilities.

[0012] The technical solution of the present invention is:

[0013] A construction system for monitoring, analyzing and displaying business and economic operations, including

[0014] Data collection module, access to various systems, collect various data;

[0015] The data cleaning module extracts, cleans, processes, converts, and loads data based on data technology and business rules, achieving data unification and standardization to form a data resource pool;

[0016] The module for building the business and economic operation indicator system determines key indicators based on the characteristics and needs of business and economic operation;

[0017] The business and economic analysis model construction module, based on the business and economic operation monitoring and analysis scenarios, constructs themes such as consumer market, market operation, goods trade, service trade, foreign investment, foreign economic cooperation, and economic parks. Based on the key indicators in each field, it forms corresponding monitoring models, forecasting models, and early warning models.

[0018] The visualization display module uses visualization methods to intuitively display business operations in a graphical and dynamic form, combining big data ecosystem components and rich front-end chart display technology to provide a panoramic and intuitive display of business operation status.

[0019] Further,

[0020] Through big data technology, multi-source data is aggregated and integrated to form a data resource pool, and through the design of theme models, business and economic operation monitoring and analysis are carried out.

[0021] in,

[0022] The data collection module is connected to various systems, including Internet data access, department internal data access, enterprise reporting data access, and offline data access.

[0023] The data cleaning module functions include:

[0024] (1) Data extraction: Regularly synchronize business data resources from different sources, configure data extraction tasks based on the metadata information of the data source, the configured extraction rules, and the field information to be extracted, and regularly execute full or incremental data extraction tasks. After the data extraction is completed, it is imported into the cleaning library;

[0025] (2) Data verification: Verify data according to the agreed data format and content. If data does not meet the requirements, it will be output to the error library and a detailed error record will be generated. The error data and error log will be returned to the data provider to assist the data provider in analyzing and modifying the data.

[0026] (3) Data transformation: processing incomplete data, erroneous data, missing data, and duplicate data;

[0027] (4) Theme library construction

[0028] Build a multi-level data resource system, establish a business original library, business summary library, subject analysis library, and shared exchange library to support data services for subsequent data query and data analysis.

[0029] in,

[0030] Data conversion, including:

[0031] Data filling: Fill in the gaps in empty and missing data, and mark those that cannot be processed;

[0032] Data replacement: replace invalid data;

[0033] Format normalization: convert the data format extracted from the source data into a target data format that is convenient for entering the warehouse for processing;

[0034] Primary and foreign key constraints: By establishing primary and foreign key constraints, illegal data can be replaced or exported to an error file for reprocessing

[0035] The module for constructing a commercial economic performance indicator system layers and categorizes indicators, establishing logical relationships and weighting systems between them. Using the analytic hierarchy process, it determines the relative importance of each indicator in assessing commercial economic performance. These indicators include total retail sales of consumer goods, import and export volume, actual foreign investment, actual outbound investment, completed overseas contracted projects, and the scale and growth rate of labor dispatched for overseas cooperation.

[0036] Business economic analysis model construction module,

[0037] (1) Monitoring model: Achieve situational awareness of key indicators in various fields through overall scale analysis, time series analysis, and structural analysis models;

[0038] (2) Prediction model: Use ARIMA model, SARIMA model, and artificial neural network model to predict key indicators in the business and economic fields;

[0039] (3) Early warning model: Build an early warning model based on the annual plan achievement gap of key indicators, the year-on-year growth rate range of key indicators, and the year-on-year growth rate fluctuation of the main structure of key indicators, and issue reminders to support timely scheduling of business work.

[0040] The beneficial effects of the present invention are

[0041] (1) Strengthen the integration and sharing of information resources, integrate and aggregate multi-source data to build data infrastructure capabilities, and improve business decision-making capabilities.

[0042] (2) Support scenarios such as business and economic operation situation awareness, forecasting and early warning, analysis and judgment, and work collaboration, and improve the digital and intelligent level of business governance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is the overall structural diagram of the present invention;

[0044] Figure 2 This is a flowchart of the workflow of the present invention

[0045] Figure 3 This is a flowchart of the data cleaning workflow. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0047] The present invention provides a system for building a business economic operation monitoring, analysis and display system, including:

[0048] The first step is the data collection module.

[0049] In view of the multi-source and heterogeneous characteristics of business data, a data collection module is constructed, including modules for accessing data collected from the Internet, internal government data, enterprise-reported data, and offline data.

[0050] The second step is data cleaning module.

[0051] Based on data technology and business rules, data is extracted, cleaned, processed, converted and loaded to achieve data unification and standardization, and form a high-quality data resource pool.

[0052] (1) Data extraction: Regularly synchronize business data resources from different sources, configure data extraction tasks based on the metadata information of the data source, the configured extraction rules and the field information to be extracted, and regularly execute full or incremental data extraction tasks. After the data extraction is completed, it is imported into the cleaning library.

[0053] (2) Data verification: Verify data according to the agreed data format and content. For data that does not meet the requirements, it will be output to the error library and a detailed error record will be generated. The error data and error log will be returned to the data provider to assist the data provider in analyzing and modifying the data.

[0054] (3) Data conversion: processing incomplete data, erroneous data, missing data, and duplicate data. Specifically including:

[0055] Data filling: Fill in the gaps in empty data and missing data, and mark those that cannot be processed.

[0056] Data replacement: Replace invalid data.

[0057] Format normalization: Convert the data format extracted from the source data into a target data format that is convenient for entering the warehouse for processing.

[0058] Primary and foreign key constraints: By establishing primary and foreign key constraints, illegal data can be replaced or exported to an error file for reprocessing.

[0059] (4) Theme library construction

[0060] Build a multi-level data resource system and establish four libraries including business original library, business summary library, subject analysis library, and shared exchange library to support subsequent data query, data analysis and other data services.

[0061] The third step is to build a module for the business and economic operation indicator system.

[0062] Determine key indicators based on the characteristics and needs of business and economic operations. Layer and categorize key indicators, establishing logical relationships and weighting systems between them. Use methods such as the Analytic Hierarchy Process to determine the relative importance of each indicator in assessing business and economic operations.

[0063] The main indicators include the total retail sales of consumer goods, import and export volume of goods, actual utilization of foreign capital, actual overseas investment, completed turnover of overseas contracting projects, number of people sent for overseas labor cooperation, and other scale and growth rate indicators.

[0064] The fourth step is to build the business economic analysis model module.

[0065] Based on the business and economic operation monitoring and analysis scenarios, we construct themes such as consumer market, market operation, goods trade, service trade, foreign investment, foreign economic cooperation, and economic parks, and form corresponding monitoring models, forecasting models, and early warning models around the key indicators in each field.

[0066] (1) Monitoring model: Through overall scale analysis, time series analysis, and structural analysis models, situational awareness of key indicators in various fields can be achieved.

[0067] (2) Prediction model: Use ARIMA model, SARIMA model, and artificial neural network model to predict key indicators in the business and economic fields

[0068] (3) Early warning model: Build an early warning model based on the annual plan achievement gap of key indicators, the year-on-year growth rate range of key indicators, and the year-on-year growth rate fluctuation of the main structure of key indicators, and issue reminders to support timely scheduling of business work.

[0069] Step 5: Visual display module.

[0070] It uses visualization methods to directly display business operations in the form of charts and dynamics, combining big data ecosystem components and rich front-end chart display technology to provide a panoramic and intuitive display of business operation status.

[0071] The above description is only a preferred embodiment of the present invention and is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention are included in the scope of protection of the present invention.

Claims

1. A system for monitoring, analyzing and displaying business and economic operations, characterized by: Data collection module, access to various systems, collect various data; The data cleaning module extracts, cleans, processes, converts, and loads data based on data technology and business rules, achieving data unification and standardization to form a data resource pool; The module for building the business and economic operation indicator system determines key indicators based on the characteristics and needs of business and economic operation; The business and economic analysis model construction module, based on the business and economic operation monitoring and analysis scenarios, constructs themes such as consumer market, market operation, goods trade, service trade, foreign investment, foreign economic cooperation, and economic parks. Based on the key indicators in each field, it forms corresponding monitoring models, forecasting models, and early warning models. The visualization display module uses visualization methods to intuitively display business operations in a graphical and dynamic form, combining big data ecosystem components and rich front-end chart display technology to provide a panoramic and intuitive display of business operation status.

2. The system according to claim 1, wherein: Through big data technology, multi-source data is aggregated and integrated to form a data resource pool, and through the design of theme models, business and economic operation monitoring and analysis are carried out.

3. The system according to claim 1, wherein: It includes data access collected from the Internet, data access within departments, data access reported by enterprises, and offline data access.

4. The system according to claim 1, wherein: The data cleaning module functions include: (1) Data extraction: Regularly synchronize business data resources from different sources, configure data extraction tasks based on the metadata information of the data source, the configured extraction rules, and the field information to be extracted, and regularly execute full or incremental data extraction tasks. After the data extraction is completed, it is imported into the cleaning library; (2) Data verification: Verify data according to the agreed data format and content. If data does not meet the requirements, it will be output to the error library and a detailed error record will be generated. The error data and error log will be returned to the data provider to assist the data provider in analyzing and modifying the data. (3) Data transformation: processing incomplete data, erroneous data, missing data, and duplicate data; (4) Theme library construction Build a multi-level data resource system, establish a business original library, business summary library, subject analysis library, and shared exchange library to support data services for subsequent data query and data analysis.

5. The system according to claim 4, characterized in that Data conversion, including: Data filling: Fill in the gaps in empty and missing data, and mark those that cannot be processed; Data replacement: replace invalid data; Format normalization: convert the data format extracted from the source data into a target data format that is convenient for entering the warehouse for processing; Primary and foreign key constraints: By establishing primary and foreign key constraints, illegal data can be replaced or exported to an error file for reprocessing.

6. The system according to claim 1, wherein: The module for building the business and economic operation indicator system stratifies and classifies the indicators, establishes the logical relationship and weight system between the indicators; and determines the relative importance of each indicator in evaluating the business and economic operation status through the hierarchical analysis method.

7. The system according to claim 6, characterized in that The indicators mentioned include the total retail sales of consumer goods, import and export volume of goods, actual utilization of foreign capital, actual overseas investment, completed turnover of overseas contracting projects, and the scale and growth rate of the number of people sent for overseas labor cooperation.

8. The system according to claim 1, wherein: Business economic analysis model construction module, (1) Monitoring model: Achieve situational awareness of key indicators in various fields through overall scale analysis, time series analysis, and structural analysis models; (2) Prediction model: Use ARIMA model, SARIMA model, and artificial neural network model to predict key indicators in the business and economic fields; (3) Early warning model: Build an early warning model based on the annual plan achievement gap of key indicators, the year-on-year growth rate range of key indicators, and the year-on-year growth rate fluctuation of the main structure of key indicators, and issue reminders to support timely scheduling of business work.

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