Data index statistical system construction method and system, storage medium and computer

Abstract

The invention provides a data index statistical system construction method and system, a storage medium and a computer, and the construction method comprises the steps: obtaining business data of different data sources in a government affair implementation process, carrying out the business and demand analysis of the business data, and constructing a business detail model; performing index specification definition according to the business detail model to obtain business indexes and technical indexes of the business data, combining the business indexes and the technical indexes of all the business data based on a preset statistical granularity to form a data set under the same theme, and obtaining index statistical data; and integrating and storing the index statistical data of different data sources into a target database, and displaying the index statistical data in a visual mode. According to the data index statistical system construction method provided by the invention, indexes and statistical calibers are unified, the visualization is strong, and the development and utilization efficiency of business data by users is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, system, storage medium and computer for constructing a data indicator statistical system. Background Art

[0002] In the era of big data, although the data scale is very large, most of the data has not been fully utilized and analyzed, and it is difficult to reflect the value of the data; through the construction of a data indicator statistical system, data can generate actual business value. At present, the use of data indicator statistics mainly includes: internal indicator statistical tools for enterprises, some enterprises customize and develop statistical tools for their own business scenarios to achieve business indicator statistical functions for specific needs, internally define statistical calibers and qualifiers, etc.; use database technology, including relational databases (such as MySQL, PostgreSQL, etc.) and NoSQL databases (such as MongoDB, Cassandra, etc.), combined with database technology, to complete the SQL logic formulation of related queries and statistical functions.

[0003] Due to the different channels for obtaining data or the different data storage formats, the current construction of the data indicator statistical system has the following main problems: the indicator name does not match the statistical caliber, the indicator name is inconsistent with the same statistical caliber; two indicators describing the same fact process have inconsistent calibers for the same facts; the indicator data source and calculation logic are unclear, the multi-data source expansion capability is not strong, and SQL statements cannot be applied for transformation, which affects users' further development and utilization of data. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a method, system, storage medium and computer for constructing a data indicator statistical system to solve the technical problems existing in the prior art.

[0005] The present invention proposes a method for constructing a data indicator statistical system, comprising:

[0006] Obtain business data from different data sources during the implementation of government affairs, conduct business and demand analysis on the business data, and build a business detail model;

[0007] Define the indicator specifications according to the business detail model to obtain the business indicators and technical indicators of the business data;

[0008] Summarize and develop the business data after the indicator specification is defined, combine the business indicators and technical indicators of all business data based on the preset statistical granularity, form a data set under the same theme, and obtain indicator statistical data;

[0009] The indicator statistical data of different data sources are integrated and stored in a target database, and displayed in a visual manner.

[0010] Optionally, the business detail model includes at least a dimension table, a fact table, and a summary table;

[0011] The dimension table is used to aggregate, drill, and slice the business data to reflect the attribute information of the business data;

[0012] The fact table is used to reflect the detailed information corresponding to the business data in a specific business process;

[0013] The summary table is used to integrate and display the results of the data indicators, which is convenient for viewing and analyzing the data.

[0014] Optionally, the step of defining indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data includes:

[0015] The business data is split based on the preset indicator granularity, the subject corresponding to each business data is obtained and classified, and the relationship between the business field and the business object of each business data is clarified;

[0016] Based on the dimensions and business processes of the classified business data, the statistical caliber of each business data is unified, the business indicators and technical indicators of each business data are obtained, and a unified and standardized indicator library is created based on the business indicators and the technical indicators.

[0017] Optionally, the step of obtaining the technical indicator of each business data includes:

[0018] Based on the dimensions and business processes of the business data, atomic indicators of the business data are obtained. The atomic indicators are indicators that cannot be further divided in the business definition, so as to unify the statistical caliber of various business data;

[0019] Based on the atomic indicators, dimensional attributes, statistical attributes, and management attributes of the business data are obtained, and derived indicators of the business data are obtained according to the atomic indicators, the dimensional attributes, the statistical attributes, and the management attributes;

[0020] Superimpose and calculate the derivative indicators of several business data to obtain composite indicators of business data;

[0021] Among them, the atomic indicators, the derived indicators, and the composite indicators together constitute the technical indicators of the business data.

[0022] Optionally, the step of aggregating and developing the business data after the indicator specification is defined, combining the business indicators and technical indicators of all business data based on a preset statistical granularity to form a data set under the same theme, and obtaining the indicator statistical data includes:

[0023] Creating a statistical scheduling job based on a preset statistical granularity, generating a job instance according to a statistical period, and periodically calculating the business indicator and the technical indicator;

[0024] Setting early warning scheduling information, solidifying the periodic calculation results into a summary logic table based on the early warning scheduling information, and establishing a logical mapping relationship between the summary logic table and the business data physical table;

[0025] A data set at the same statistical granularity is formed according to the mapping relationship, and the data set is reviewed according to the early warning scheduling information to obtain early warning indicator statistical data.

[0026] The present invention also proposes a data indicator statistical system construction system, including:

[0027] A construction module is used to obtain business data from different data sources during the implementation of government affairs, conduct business and demand analysis on the business data, and build a business detail model;

[0028] A definition module, used to define indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data;

[0029] The combination module is used to summarize and develop the business data after the indicator specification is defined, and combine the business indicators and technical indicators of all business data based on the preset statistical granularity to form a data set under the same theme and obtain indicator statistical data;

[0030] The display module is used to integrate and store the indicator statistical data from different data sources into a target database, and display them in a visual manner.

[0031] Optionally, the definition module includes:

[0032] A splitting unit is used to split the business data based on a preset indicator granularity, obtain the subject corresponding to each business data and classify it, and clarify the relationship between the business field and business object of each business data;

[0033] A creation unit is used to unify the statistical caliber of various business data based on the dimensions and business processes of the classified business data, obtain the business indicators and technical indicators of various business data, and create a unified and standardized indicator library based on the business indicators and the technical indicators.

[0034] Optionally, the creating unit includes:

[0035] A first acquisition subunit is used to acquire atomic indicators of the business data based on the dimensions and business processes of the business data, wherein the atomic indicators are indicators that cannot be further divided in the business definition, so as to unify the statistical caliber of various business data;

[0036] A second acquisition subunit is used to acquire dimensional attributes, statistical attributes, and management attributes of the business data based on the atomic indicators, and to acquire derived indicators of the business data according to the atomic indicators, the dimensional attributes, the statistical attributes, and the management attributes;

[0037] A third acquisition subunit is used to perform superposition calculation on a plurality of derivative indicators of the business data to obtain a composite indicator of the business data;

[0038] Among them, the atomic indicators, the derived indicators, and the composite indicators together constitute the technical indicators of the business data.

[0039] The present invention also proposes a storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned data indicator statistical system construction method is implemented.

[0040] The present invention also proposes a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for constructing a data indicator statistical system when executing the computer program.

[0041] Compared with the prior art, the present invention has the following beneficial effects: the data indicator statistical system construction method provided by the present application first obtains business data from different data sources, builds a custom business detail model after demand analysis, defines indicator specifications according to the business detail model, and obtains business indicators and technical indicators of the business data; unifies the statistical caliber of each business data, summarizes and develops the business data after the indicator specifications are defined, combines the business indicators and technical indicators of all business data based on a preset statistical granularity, forms a data set under the same theme, obtains indicator statistical data, and performs dynamic temporary storage after indicator calculation based on a preset statistical granularity, and finally solidifies it into a summary table, so that the reusability of the indicator is enhanced, and the efficiency of adding, deleting and modifying a single indicator is higher during aggregation, thereby improving the robustness of the entire system; finally, the data is integrated and stored in a target database, and displayed in a visual way, so as to help users better understand the trends and relationships behind the data, and enhance the user's experience in the development and utilization of business data, which is suitable for large-scale promotion.

[0042] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a flowchart of a method for constructing a data indicator statistical system in the first embodiment of the present invention;

[0044] Figure 2 FIG. 4 is a structural block diagram of a computer in a fourth embodiment of the present invention.

[0045] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0046] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0048] Embodiment 1

[0049] See also Figure 1 , which shows a method for constructing a data indicator statistical system in a first embodiment of the present invention, and the method for constructing a data indicator statistical system specifically includes steps S10 to S40:

[0050] S10, obtaining business data from different data sources during the implementation of government affairs, performing business and demand analysis on the business data, and building a business detail model;

[0051] Optionally, business data from different data sources in the process of government affairs implementation can be obtained. The business data obtained may be business data from multiple databases, such as relational databases such as MYSQL, ORACLE, Jincang, Dameng, Tencent TD, etc., or big data system libraries such as big data Hbase and Hive. The database is a data warehouse for data mining and a data source for indicator calculation; the business data obtained in this embodiment can process information from different data sources at the same time, improving the comprehensiveness and reliability of data information. By investigating business data, conducting business and demand analysis, a business model to be summarized and counted can be obtained, and a business detail model can be constructed by the business model.

[0052] Optionally, in this embodiment, the constructed business detail model includes at least a dimension table, a fact table, and a summary table;

[0053] The dimension table is used to aggregate, drill, and slice the business data to reflect the attribute information of the business data; the dimension table reflects a type of business attribute in a measurement environment based on the perspective of observing and analyzing business data. The collection of such attributes constitutes a dimension, which can also be called an entity object. The dimension belongs to a data domain; for example, the geographical dimension can include country, region, province, city, etc., and the time dimension can include year, quarter, month, week, day, etc.

[0054] The fact table is used to reflect the detailed information corresponding to the business data in a specific business process; the fact table is a logical table of fact data belonging to a certain business process, which can enrich the detailed information of the transactions corresponding to the specific business process, such as the transaction information table in the securities library, the personal tax table in the financial library, and the daily steel production table in the industrial library.

[0055] The summary table is used to integrate and display the results of data indicators after summary, which is convenient for viewing and analyzing data. The summary table can summarize data from multiple data sources or different data indicators and consolidate them in one table for easy viewing, comparison and analysis; the summary table stores statistical indicator data such as calculated sum, average, maximum, minimum, etc., which is the embodiment of the assets after the indicator calculation.

[0056] S20, defining indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data;

[0057] Optionally, the step of defining indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data includes:

[0058] The business data is split based on the preset indicator granularity, the subject corresponding to each business data is obtained and classified, and the relationship between the business field and the business object of each business data is clarified;

[0059] Based on the dimensions and business processes of the classified business data, the statistical caliber of each business data is unified, the business indicators and technical indicators of each business data are obtained, and a unified and standardized indicator library is created based on the business indicators and the technical indicators.

[0060] Optionally, the steps of obtaining technical indicators of each business data include:

[0061] Based on the dimensions and business processes of the business data, atomic indicators of the business data are obtained. The atomic indicators are indicators that cannot be further divided in the business definition, so as to unify the statistical caliber of various business data;

[0062] Based on the atomic indicators, dimensional attributes, statistical attributes, and management attributes of the business data are obtained, and derived indicators of the business data are obtained according to the atomic indicators, the dimensional attributes, the statistical attributes, and the management attributes;

[0063] Superimpose and calculate the derivative indicators of several business data to obtain composite indicators of the business data;

[0064] Among them, the atomic indicators, the derived indicators, and the composite indicators together constitute the technical indicators of the business data.

[0065] Optionally, the standardized definition of indicators is an important step in data fusion, which is used to clarify the business, unify the statistical caliber based on dimensions and business processes, and create a unified and standardized indicator library, wherein the business indicators are used to guide the technical indicators, and the technical indicators are the specific implementation of the business indicators; after investigation and analysis, an indicator library is created based on the constructed business detail model. Indicators are statistical values ​​that measure the overall characteristics of the target and are numerical indicators that can characterize the business status of a certain business activity of the enterprise; business indicators can be understood as purposes, and technical indicators can be understood as the specific process of how to achieve the purpose; indicators generally consist of two parts: indicator name and indicator value. The indicator name and its meaning embody the qualitative and quantitative characteristics of the indicator, and the indicator value reflects the quantitative performance of the indicator under specific time, place and conditions. This embodiment decouples and splits the statistical components of different types of business data by customizing the construction of a business detail model, forming multiple non-divisible metrics based on a certain business event behavior, and based on this metric, standardizes the statistical logic in the logic table under multiple data sources to generate atomic indicators. The atomic indicators solve the problem of inconsistent definitions and calibers from the root. The indicator definition clearly designs the statistical logic, and does not require ETL (extraction, transformation, loading) secondary or repeated research and development, thereby improving research and development efficiency and ensuring the consistency of statistical results; on the basis of atomic indicators, specific dimensional attributes, statistical attributes, management attributes, etc. are combined to form derived indicators, and expansion supports the superposition calculation of one or more derived indicators to form composite indicators; the statistical caliber of each business data is unified to facilitate the statistics and aggregation of subsequent data.

[0066] In some optional embodiments, the technical indicators also include direct-check indicators, which are used for the entire process from indicator definition to indicator calculation, provide a relatively complete indicator construction function, support SQL (Structured Query Language) custom dimensions and indicator configuration; help to quickly build indicators, and in some temporary, highly personalized indicators or data report scenarios, the required data can be quickly obtained based on direct-check indicators.

[0067] S30, summarize and develop the business data after the indicator specification is defined, combine the business indicators and technical indicators of all business data based on the preset statistical granularity, form a data set under the same theme, and obtain indicator statistical data;

[0068] Optionally, the step of aggregating and developing the business data after the indicator specification is defined, combining the business indicators and technical indicators of all business data based on a preset statistical granularity to form a data set under the same theme, and obtaining the indicator statistical data includes:

[0069] Creating a statistical scheduling job based on a preset statistical granularity, generating a job instance according to a statistical period, and periodically calculating the business indicator and the technical indicator;

[0070] Setting early warning scheduling information, solidifying the periodic calculation results into a summary logic table based on the early warning scheduling information, and establishing a logical mapping relationship between the summary logic table and the business data physical table;

[0071] A data set at the same statistical granularity is formed according to the mapping relationship, and the data set is reviewed according to the early warning scheduling information to obtain early warning indicator statistical data.

[0072] In the specific implementation, based on the preset statistical granularity, the business indicators and the technical indicators are calculated periodically. The indicator calculation can be implemented in the form of a dynamic table. After the indicator is calculated, the dynamic table is first used for storage. When the fact table data of the same indicator in the same period has not changed, the dynamic table data can be directly imported into the summary table, which reduces the number of indicator calculations, increases the reusability of the indicator, and improves the performance of summary statistics. Furthermore, a logical mapping relationship between the summary logical table and the business data physical table is established. The indicator summary process is a low-coupling and high-cohesion process. Based on the preset statistical granularity, the indicator is dynamically temporarily stored after calculation, and finally solidified into the summary table, thereby enhancing the reusability of the indicator. When summarizing, the efficiency of adding, deleting, and modifying a single indicator is higher, which improves the robustness of the entire system; a data set under the same theme is formed to obtain indicator statistical data, which can subsequently assist in decision-making and be output to the outside for use by business applications.

[0073] S40, integrating and storing the indicator statistical data from different data sources into a target database, and displaying them in a visual manner.

[0074] In specific implementation, the indicator statistics of different data sources can be integrated and stored in a target database, and a data map can be constructed; according to recursive query, the data source, solidification summary and application output of the indicator can be tracked in the data map; for some fixed and clear field information, static basic tables can be used, such as classification basic information, indicator basic information table, etc., to reduce computing IO consumption, improve query efficiency, and avoid performance problems; when data errors occur, they can be quickly traced to the source to avoid erroneous data from bringing negative impacts on users' decisions. Furthermore, the constructed data map can be displayed through the display platform to help users better understand the trends and relationships behind the data, and realize statistical analysis, guidance, and decision-making assistance in the government affairs field.

[0075] In summary, the data indicator statistical system construction method provided by the present application first obtains business data from different data sources, customizes and builds a business detail model after demand analysis, and defines the indicator specifications according to the business detail model to obtain the business indicators and technical indicators of the business data; decouples and splits the statistical components of different types of business data to form multiple non-divisible metrics based on a certain business event behavior, obtains the atomic indicators, derivative indicators, and composite indicators of the business data in turn, unifies the statistical caliber of each business data, summarizes and develops the business data after the indicator specification definition, combines the business indicators and technical indicators of all business data based on the preset statistical granularity, forms a data set under the same theme, obtains indicator statistical data, and dynamically and temporarily stores the indicators after calculation based on the preset statistical granularity, and finally solidifies them into a summary table, thereby enhancing the reusability of the indicators, making it more efficient to add, delete, and modify a single indicator during the summary, and improving the robustness of the entire system; finally, the integrated storage is put into a target database, and displayed in a visual way to help users better understand the trends and relationships behind the data, improve the user's development and utilization efficiency and experience of business data, and is suitable for large-scale promotion.

[0076] Embodiment 2

[0077] This embodiment provides a data indicator statistical system construction system, including:

[0078] A construction module is used to obtain business data from different data sources during the implementation of government affairs, conduct business and demand analysis on the business data, and build a business detail model;

[0079] A definition module, used to define indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data;

[0080] The combination module is used to summarize and develop the business data after the indicator specification is defined, and combine the business indicators and technical indicators of all business data based on the preset statistical granularity to form a data set under the same theme and obtain indicator statistical data;

[0081] The display module is used to integrate and store the indicator statistical data from different data sources into a target database, and display them in a visual manner.

[0082] The business detail model at least includes a dimension table, a fact table, and a summary table;

[0083] The dimension table is used to aggregate, drill, and slice the business data to reflect the attribute information of the business data;

[0084] The fact table is used to reflect the detailed information corresponding to the business data in a specific business process;

[0085] The summary table is used to integrate and display the results of the data indicators, which is convenient for viewing and analyzing the data.

[0086] The definition module includes:

[0087] A splitting unit is used to split the business data based on a preset indicator granularity, obtain the subject corresponding to each business data and classify it, and clarify the relationship between the business field and business object of each business data;

[0088] A creation unit is used to unify the statistical caliber of various business data based on the dimensions and business processes of the classified business data, obtain the business indicators and technical indicators of various business data, and create a unified and standardized indicator library based on the business indicators and the technical indicators.

[0089] The creation unit comprises:

[0090] A first acquisition subunit is used to acquire atomic indicators of the business data based on the dimensions and business processes of the business data, wherein the atomic indicators are indicators that cannot be further divided in the business definition, so as to unify the statistical caliber of various business data;

[0091] A second acquisition subunit is used to acquire dimensional attributes, statistical attributes, and management attributes of the business data based on the atomic indicators, and to acquire derived indicators of the business data according to the atomic indicators, the dimensional attributes, the statistical attributes, and the management attributes;

[0092] A third acquisition subunit is used to perform superposition calculation on a plurality of derivative indicators of the business data to obtain a composite indicator of the business data;

[0093] Among them, the atomic indicators, the derived indicators, and the composite indicators together constitute the technical indicators of the business data.

[0094] The combined module comprises:

[0095] A calculation unit, used to create a statistical scheduling job based on a preset statistical granularity, generate a job instance according to a statistical period, and periodically calculate the business indicator and the technical indicator;

[0096] A solidification unit, used to set early warning scheduling information, solidify the periodic calculation results into a summary logic table based on the early warning scheduling information, and establish a logical mapping relationship between the summary logic table and the business data physical table;

[0097] The audit unit is used to form a data set at the same statistical granularity according to the mapping relationship, and audit the data set according to the early warning scheduling information to obtain early warning indicator statistical data.

[0098] Embodiment 3

[0099] This embodiment proposes a storage medium on which a computer program is stored. When the program is executed by a processor, the method for constructing a data indicator statistical system as described above is implemented.

[0100] Embodiment 4

[0101] The present invention also provides a computer, see Figure 2 , shown is a computer in an embodiment of the present invention, including a memory 10, a processor 20, and a computer program 30 stored in the memory 10 and executable on the processor 20. When the processor 20 executes the computer program 30, the above-mentioned data indicator statistical system construction method is implemented.

[0102] The memory 10 includes at least one type of storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 10 may be an internal storage unit of a computer, such as a hard disk of the computer. In other embodiments, the memory 10 may also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card, etc. Further, the memory 10 may also include both an internal storage unit of a computer and an external storage device. The memory 10 may be used not only to store application software and various types of data installed in the computer, but also to temporarily store data that has been output or is to be output.

[0103] Among them, in some embodiments, the processor 20 can be an electronic control unit (Electronic Control Unit, abbreviated as ECU, also known as a vehicle computer), a central processing unit (Central Processing Unit, CPU), a controller, a microcontroller, a microprocessor or other data processing chip, used to run the program code stored in the memory 10 or process data, such as executing access restriction programs, etc.

[0104] It should be pointed out that Figure 2 The structure shown does not constitute a limitation on the computer. In other embodiments, the computer may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0105] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0106] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0107] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0108] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0109] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for constructing a data indicator statistical system, characterized in that: include: Obtain business data from different data sources during the implementation of government affairs, conduct business and demand analysis on the business data, and build a business detail model; Define the indicator specifications according to the business detail model to obtain the business indicators and technical indicators of the business data; Summarize and develop the business data after the indicator specification is defined, combine the business indicators and technical indicators of all business data based on the preset statistical granularity, form a data set under the same theme, and obtain indicator statistical data; The indicator statistical data of different data sources are integrated and stored in a target database, and displayed in a visual manner.

2. The method for constructing a data indicator statistical system according to claim 1, characterized in that: The business detail model at least includes a dimension table, a fact table, and a summary table; The dimension table is used to aggregate, drill, and slice the business data to reflect the attribute information of the business data; The fact table is used to reflect the detailed information corresponding to the business data in a specific business process; The summary table is used to integrate and display the results of the data indicators, which is convenient for viewing and analyzing the data.

3. The method for constructing a data indicator statistical system according to claim 2, characterized in that: The step of defining indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data includes: The business data is split based on the preset indicator granularity, the subject corresponding to each business data is obtained and classified, and the relationship between the business field and the business object of each business data is clarified; Based on the dimensions and business processes of the classified business data, the statistical caliber of each business data is unified, the business indicators and technical indicators of each business data are obtained, and a unified and standardized indicator library is created based on the business indicators and the technical indicators.

4. The method for constructing a data indicator statistical system according to claim 3, characterized in that: The steps to obtain technical indicators of each business data include: Based on the dimensions and business processes of the business data, atomic indicators of the business data are obtained. The atomic indicators are indicators that cannot be further divided in the business definition, so as to unify the statistical caliber of various business data; Based on the atomic indicators, dimensional attributes, statistical attributes, and management attributes of the business data are obtained, and derived indicators of the business data are obtained according to the atomic indicators, the dimensional attributes, the statistical attributes, and the management attributes; Superimpose and calculate the derivative indicators of several business data to obtain composite indicators of business data; Among them, the atomic indicators, the derived indicators, and the composite indicators together constitute the technical indicators of the business data.

5. The method for constructing a data indicator statistical system according to claim 3, characterized in that: The steps of aggregating and developing the business data after the indicator specification is defined, combining the business indicators and technical indicators of all business data based on the preset statistical granularity to form a data set under the same theme, and obtaining the indicator statistical data include: Creating a statistical scheduling job based on a preset statistical granularity, generating a job instance according to a statistical period, and periodically calculating the business indicator and the technical indicator; Setting early warning scheduling information, solidifying the periodic calculation results into a summary logic table based on the early warning scheduling information, and establishing a logical mapping relationship between the summary logic table and the business data physical table; A data set at the same statistical granularity is formed according to the mapping relationship, and the data set is reviewed according to the early warning scheduling information to obtain early warning indicator statistical data.

6. A data indicator statistical system construction system, characterized in that: include; A construction module is used to obtain business data from different data sources during the implementation of government affairs, conduct business and demand analysis on the business data, and build a business detail model; A definition module, used to define indicator specifications according to the business detail model to obtain business indicators and technical indicators of the business data; The combination module is used to summarize and develop the business data after the indicator specification is defined, and combine the business indicators and technical indicators of all business data based on the preset statistical granularity to form a data set under the same theme and obtain indicator statistical data; The display module is used to integrate and store the indicator statistical data from different data sources into a target database, and display them in a visual manner.

7. The data indicator statistical system construction system according to claim 6, characterized in that: The definition module includes: A splitting unit is used to split the business data based on a preset indicator granularity, obtain the subject corresponding to each business data and classify it, and clarify the relationship between the business field and business object of each business data; A creation unit is used to unify the statistical caliber of various business data based on the dimensions and business processes of the classified business data, obtain the business indicators and technical indicators of various business data, and create a unified and standardized indicator library based on the business indicators and the technical indicators.

8. The data indicator statistical system construction system according to claim 7 is characterized in that: The creation unit comprises: A first acquisition subunit is used to acquire atomic indicators of the business data based on the dimensions and business processes of the business data, wherein the atomic indicators are indicators that cannot be further divided in the business definition, so as to unify the statistical caliber of various business data; A second acquisition subunit is used to acquire dimensional attributes, statistical attributes, and management attributes of the business data based on the atomic indicators, and to acquire derived indicators of the business data according to the atomic indicators, the dimensional attributes, the statistical attributes, and the management attributes; A third acquisition subunit is used to perform superposition calculation on a plurality of derivative indicators of the business data to obtain a composite indicator of the business data; Among them, the atomic indicators, the derived indicators, and the composite indicators together constitute the technical indicators of the business data.

9. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for constructing a data indicator statistical system as described in any one of claims 1 to 5 is implemented.

10. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for constructing a data indicator statistical system as described in any one of claims 1 to 5 is implemented.

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