Enterprise-level index management system, method and equipment based on big data and medium

Abstract

The invention discloses an enterprise-level index management system, method and device based on big data and a medium, and the system comprises a system operation interface which is used for obtaining table configuration; the data acquisition interface is used for acquiring initial data; the data table management platform is used for constructing a business theme table and a dimension table according to the business original table based on table configuration and initial data and determining an association relationship; the index management platform is used for creating business indexes according to the business theme table and the dimension table, constructing a corresponding first structured query statement according to the association relationship, determining a target index to be subjected to association analysis from the business indexes, and constructing a corresponding second structured query statement based on the target index; and the system operation interface is also used for constructing a visual graph for display according to the business indexes and a preset analysis model. Through centralized environment definition, storage and management of business indexes, the uniformity of index definition is ensured, the conversion process of index data can be recorded and displayed, and troubleshooting and compliance auditing are facilitated.

Description

Technical Field

[0001] The present invention relates to the field of big data, and in particular to an enterprise-level indicator management system, method, device and medium based on big data. Background Art

[0002] In the modern society under the background of big data, the amount of information is growing exponentially, and the sources of data are diversified, including social media, sensors, transaction records, etc., forming a data-intensive environment. This has brought unprecedented opportunities to all walks of life, but also huge challenges. Therefore, building an effective indicator management system has become the key to corporate success.

[0003] When faced with the massive amount of data generated by the business, enterprises or organizations may encounter a variety of problems and pain points. First, it may be impossible to extract core indicators from the massive amount of data, resulting in unclear strategic direction and no basis for resource allocation. Second, decision makers lack data support and rely solely on intuitive judgment, which can easily lead to waste of resources and slow market response. Third, without clear performance measurement standards, team members are hindered from working together, and inefficiency becomes prominent.

[0004] However, currently, enterprises mainly rely on a series of traditional and manual methods to maintain key business indicators, including: manual statistics in Excel, regular reporting system, direct database query, customized report development, manual early warning monitoring, etc. However, these methods are often inefficient and inflexible, prone to errors, untimely data updates, and easily lead to information transmission delays. It is difficult for decision-makers to obtain immediate business insights and respond quickly. Therefore, how to manage enterprise indicators more intuitively and efficiently is a problem to be solved in this field. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide an enterprise-level indicator management system, method, device and medium based on big data, which can define, store and manage business indicators in a centralized environment, ensure the uniformity of indicator definitions, and record and display the conversion process of indicator data, so as to facilitate problem troubleshooting and compliance auditing. The specific scheme is as follows:

[0006] In a first aspect, the present application provides an enterprise-level indicator management system based on big data, comprising:

[0007] System operation interface, used to obtain table configuration input by users;

[0008] Data collection interface, used to obtain initial data from each source database;

[0009] A data table management platform, used to construct a corresponding business subject table and a dimension table according to the business original table in the enterprise-level indicator management system based on the table configuration and the initial data, and determine the association relationship between the business subject table and the dimension table;

[0010] An indicator management platform, used to create corresponding business indicators according to the business subject table and the dimension table, and construct a first structured query statement corresponding to the business indicator according to the association relationship, and determine a target indicator to be associated and analyzed from the business indicators according to a preset indicator analysis rule based on a preset analysis model, and construct a second structured query statement corresponding to the preset analysis model based on the target indicator;

[0011] The system operation interface is also used to construct a corresponding visual graph based on the first structured query statement and the second structured query statement according to the business indicator and the preset analysis model, and display the visual graph.

[0012] Optionally, the data collection interface is also used to obtain offline data in a preset relational database and to capture open data on the Internet;

[0013] Correspondingly, the data table management platform is used to construct the corresponding business subject table and the dimension table according to the business original table based on the table configuration, the initial data, the offline data and the Internet open data.

[0014] Optionally, the data table management platform is further used to update the business subject table and the dimension table according to the updated initial data when the initial data is updated;

[0015] Correspondingly, the indicator management platform is also used to update the business indicators corresponding to the updated initial data using the updated business subject table and dimension table.

[0016] Optionally, the enterprise-level indicator management system based on big data further includes:

[0017] The task manager is used to create a synchronization task according to preset synchronization task strategy information, save the synchronization task based on a preset data integration model, and execute the synchronization task to synchronize the updated business subject table and the dimension table to the enterprise-level indicator management system when the business subject table and the dimension table are updated.

[0018] Optionally, the data table management platform is further used for:

[0019] The third structured query statement input by the user through the system operation interface is directly obtained, and the variable setting corresponding to the third structured query statement is determined, so as to construct the corresponding business subject table and the dimension table according to the business original table according to the variable setting.

[0020] Optionally, the indicator management platform is specifically used for:

[0021] Determine a corresponding aggregation method based on the metric fields in the business subject table, and construct a corresponding atomic indicator according to the aggregation method;

[0022] Determine the defined field corresponding to the atomic indicator according to the business subject table and the dimension table, and construct the corresponding derived indicator according to the defined field;

[0023] A corresponding composite indicator is created according to the atomic indicator and the derived indicator based on a preset calculation formula.

[0024] Optionally, the indicator management platform is specifically used for:

[0025] Obtaining an indicator definition form input by the user through the system operation interface, and processing the business subject table and the dimension table according to a preset table processing rule based on the indicator definition form and the association relationship between the business subject table and the dimension table;

[0026] The first structured query statements corresponding to the atomic index, the derived index and the composite index are constructed based on the processed business subject table and the dimension table.

[0027] In the second aspect, the present application provides an enterprise-level indicator management method based on big data, including:

[0028] Obtain table configuration entered by the user and initial data of each source database;

[0029] Based on the table configuration and the initial data, a corresponding business subject table and a dimension table are constructed according to the business original table in the enterprise-level indicator management system, and an association relationship between the business subject table and the dimension table is determined;

[0030] Creating corresponding business indicators according to the business subject table and the dimension table, and constructing a first structured query statement corresponding to the business indicator according to the association relationship;

[0031] Determining a target indicator to be associated analyzed from the business indicators based on a preset analysis model according to preset indicator analysis rules, and constructing a second structured query statement corresponding to the preset analysis model based on the target indicator;

[0032] Based on the first structured query statement and the second structured query statement, a corresponding visual graph is constructed according to the business indicator and the preset analysis model, and the visual graph is displayed using the operation interface.

[0033] In a third aspect, the present application provides an electronic device, comprising a processor and a memory; wherein the memory is used to store a computer program, and the computer program is loaded and executed by the processor to implement the aforementioned enterprise-level indicator management system based on big data.

[0034] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the aforementioned enterprise-level indicator management system based on big data.

[0035] The enterprise-level indicator management system based on big data in the present application obtains the table configuration input by the user through the system operation interface, and obtains the initial data of each source database through the data acquisition interface, so as to use the data table management platform to build the corresponding business subject table and dimension table according to the business original table in the enterprise-level indicator management system based on the table configuration and the initial data, and determine the association relationship between the business subject table and the dimension table, and use the indicator management platform to create corresponding business indicators according to the business subject table and the dimension table, and build a first structured query statement corresponding to the business indicator according to the association relationship, determine the target indicator to be associated with the business indicator based on the preset analysis model and the preset indicator analysis rules, and build the second structured query statement corresponding to the preset analysis model based on the target indicator, and then build the corresponding visual map based on the first structured query statement and the second structured query statement according to the business indicator and the preset analysis model through the system operation interface, and display the visual map. In this way, this application provides a centralized environment to define, store and manage all business indicators through the indicator management system, ensuring the uniformity and standardization of indicator definitions, avoiding indicator confusion caused by differences in personal understanding, and providing an intuitive interface for business users, allowing them to query and analyze indicators by themselves according to their needs, and recording and displaying the source, conversion process and flow of indicator data, helping users understand the story behind the data, facilitating problem troubleshooting and compliance audits, while reducing dependence on the IT department and speeding up decision-making.

[0036] In addition, the present application also provides an enterprise-level indicator management method based on big data, which has the same technical effect as the above-mentioned enterprise-level indicator management system based on big data. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0038] Figure 1 A schematic diagram of an enterprise-level indicator management system based on big data provided for this application;

[0039] Figure 2 A schematic diagram of a data connection and synchronization method provided for this application;

[0040] Figure 3 A schematic diagram of the relationship between a subject table, dimension table, indicators and analysis model provided for this application;

[0041] Figure 4 A flow chart for creating a subject table and dimension table provided for this application;

[0042] Figure 5 A flowchart for creating and executing synchronization tasks provided for this application;

[0043] Figure 6 A flow chart for constructing a structured query statement provided for this application;

[0044] Figure 7 A flow chart for creating atomic, derived and composite indicators provided for this application;

[0045] Figure 8 A flow chart for creating an analysis model provided for this application;

[0046] Fig. 9 A visualization diagram of indicator management provided for this application;

[0047] Fig.10 A flow chart of an enterprise-level indicator management method based on big data provided for this application;

[0048] Fig.11 A structural diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] When faced with massive amounts of data generated by the business, enterprises or organizations may encounter a variety of problems and pain points. However, currently enterprises mainly rely on a series of more traditional and manual methods to maintain key business indicators, which are often inefficient and prone to errors, or data is not updated in a timely manner, resulting in delayed information transmission. This application provides a centralized environment to manage all business indicators through an indicator management system, ensuring the uniformity and standardization of indicator definitions, avoiding indicator confusion due to personal reasons, and providing an intuitive interface that can query and analyze indicators by self-service according to needs, record and display the indicator data conversion process, and facilitate problem troubleshooting.

[0051] See also Figure 1 As shown, the embodiment of the present invention discloses an enterprise-level indicator management system based on big data, including:

[0052] The system operation interface 11 is used to obtain the table configuration input by the user.

[0053] In this embodiment, the table configuration input by the user can first be obtained through the system operation interface of the above-mentioned indicator management system. That is to say, before performing data table management, the user can complete the addition and setting of table fields and the setting of multi-table association relationships through intuitive interface operations (table view).

[0054] The data acquisition interface 12 is used to obtain the initial data of each source database.

[0055] In this embodiment, the table configuration input by the user is obtained through the system operation interface through the built-in data source management function in the above-mentioned indicator management system, such as Figure 2 As shown, the data source management function can support flexible and diverse data access methods to meet the needs of different scenarios. Specifically, for structured data storage, the platform is based on a large number of database drivers to achieve direct connection with various mainstream databases, ensuring direct access and in-depth analysis of the core data of the enterprise. In addition, offline data in the preset relational database can be obtained through the data acquisition interface, as well as Internet open data can be captured. Specifically, based on the data processing capabilities of the H2 database in the system memory, it can upload Excel or CSV (comma-separated values) files to import offline data, realize rapid prototyping or historical data analysis, and facilitate real-time capture of Internet open data by connecting to the HTTP (Hypertext Transfer Protocol) data interface. In this way, by integrating with various system databases within the enterprise, data can be automatically extracted, the workload of manual collection and entry can be reduced, the efficiency and accuracy of data processing can be improved, and real-time or scheduled updates can be supported to ensure the freshness of data.

[0056] The data table management platform 13 is used to construct corresponding business subject tables and dimension tables according to the business original tables in the enterprise-level indicator management system based on the table configuration and the initial data, and determine the association relationship between the business subject table and the dimension table.

[0057] In this embodiment, the data table management platform can construct corresponding business subject tables and dimension tables according to the business original tables in the enterprise-level indicator management system based on the table configuration input by the user and the initial data obtained, and determine the association between the business subject table and the dimension table. The subject table is a data table, which is composed of several parts such as table name, table structure and table record (table data), and aims to integrate related data scattered in different source systems of the enterprise to form a comprehensive, consistent and analysis-oriented data set. The main purpose of the dimension table is to provide descriptive information for the measurement data in the subject table, so that data analysis is richer and more meaningful. Accordingly, when constructing the business subject table and dimension table, based on the offline data and Internet open data obtained in the above steps, the data table management platform can construct corresponding business subject tables and dimension tables according to the business original tables based on the table configuration, initial data, offline data and Internet open data.

[0058] Specifically, Figure 3 As shown, this embodiment supports the division of business areas according to the needs of statistics and analysis. After the user completes the addition and setting of table fields and the setting of multi-table associations through intuitive interface operations, the system will build SQL (Structured Query Language) statements for querying from the original business database table according to the various configurations made by the user. The data structure of the subject table and dimension table can be confirmed through the pre-query of the interface, so as to conveniently build the original business table into the business subject table and dimension table. Specifically, it can be divided into table view operation and SQL view operation. The corresponding pre-query can be performed after selecting the corresponding business database table and field and setting the table connection, or after writing SQL and setting the corresponding variables, the pre-query can be performed.

[0059] It is understandable that the data table management platform can also directly obtain the third structured query statement input by the user through the system operation interface, and determine the variable setting corresponding to the third structured query statement, so as to construct the corresponding business subject table and dimension table according to the business original table according to the variable setting. At this time, the user sets the construction parameters (SQL view) of the subject table and dimension table by directly writing the SQL statement to query the business library table. The SQL statement supports the setting of variables, and the system will parse the variables through FreeMarker to achieve a more flexible query strategy.

[0060] It should be pointed out that if Figure 2 , Figure 4 As shown, in this embodiment, the data synchronization function is also implemented based on Flink, and the created subject table and dimension table are synchronized to the system, and the synchronization task is managed through the self-developed synchronization task management function. At the same time, it can also synchronize the changes of the source database in real time and synchronize them to the indicator system in real time, so as to maintain the timeliness and consistency of the data. Specifically, the synchronization task can be created according to the preset synchronization task strategy information through the preset task manager, and the synchronization task can be saved based on the preset data integration model. When the business subject table and dimension table are updated, the synchronization task is executed to synchronize the updated business subject table and dimension table to the enterprise-level indicator management system. The above-mentioned Flink, namely Apache Flink, is a distributed stream processing framework that can not only process real-time data streams, but also support batch processing, which helps to realize data synchronization tasks. Specifically, for the above-mentioned synchronization task, after creating the synchronization task, fill in the corresponding execution strategy information, and determine whether the current synchronization task already exists. If not, create the corresponding task model, and after the workflow definition and task definition, save the synchronization task, and after determining to execute the above-mentioned synchronization task, create the corresponding workflow instance and task instance to execute the above-mentioned synchronization task to perform the corresponding data synchronization process. In this way, the synchronization tasks are managed through Flink-based data synchronization technology and combined with the self-developed synchronization task management function to achieve regular and periodic business data synchronization.

[0061] The indicator management platform 14 is used to create corresponding business indicators based on the business subject table and the dimension table, and construct a first structured query statement corresponding to the business indicator based on the association relationship, and determine the target indicator to be associated with the business indicator based on the preset analysis model and preset indicator analysis rules, and construct a second structured query statement corresponding to the preset analysis model based on the target indicator.

[0062] In this embodiment, after the subject table and the dimension table are created, corresponding business indicators can be created according to the business subject table and the dimension table, and Figure 5 as well as Figure 6 As shown, according to the indicator definition form filled in by the user, combined with the logical association between the subject table and the dimension table, the table connection, conditional filtering, grouping aggregation and sorting of the relevant subject table and dimension table are performed, and the SQL statement corresponding to the indicator is dynamically constructed.

[0063] The indicators in this embodiment are specific numerical values ​​that quantify the performance of a business or process, and are used to evaluate and track specific goals or results. They are usually some kind of calculation or summary of data. In a specific embodiment, the indicator management platform can determine the corresponding aggregation method based on the metric fields in the business subject table, and build corresponding atomic indicators (Atomic Metrics) based on the aggregation method; determine the limited fields corresponding to the atomic indicators based on the business subject table and the dimension table, and build corresponding derived indicators (Derived Metrics) based on the limited fields; and create corresponding composite indicators (Composite Metrics) based on the atomic indicators and derived indicators based on preset calculation formulas. Figure 7 As shown, in this embodiment, the indicators include three types: atomic indicators, derived indicators and composite indicators. Atomic indicators, also known as basic indicators, are the most basic and indivisible units for measuring business. They specify an aggregation method for a certain metric field in a subject table. The core is to select an aggregation method (total, maximum value, minimum value, average value, count, etc.) for a metric field in a subject table; derived indicators are new indicators formed on the basis of atomic indicators or composite indicators by combining dimensions, time periods, statistical attributes, or adding additional conditions such as business restrictions (business field conditions) and time restrictions (query time range). They support derivative statistical methods such as year-on-year and proportion to express more specific or in-depth business scenarios or trend changes. The above dimensions are used to describe the category information of data features or attributes. They are different angles or perspectives for observing data, which can add context to the data and make the data meaningful and interpretable; composite indicators are composed of two or more basic indicators through certain operation rules to measure more comprehensive business performance. Composite indicators integrate different atomic indicators or derived indicators through mathematical operations (such as addition, subtraction, multiplication, and division) to obtain a more comprehensive evaluation perspective. Based on the above steps, the indicator management platform can obtain the indicator definition form entered by the user through the system operation interface, and process the business subject table and dimension table according to the preset table processing rules based on the indicator definition form and the association between the business subject table and the dimension table, and then construct the first structured query statement corresponding to the atomic indicator, derived indicator and composite indicator based on the processed business subject table and dimension table. In this way, all business indicators are defined, stored and managed through a centralized environment, ensuring the uniformity and standardization of indicator definitions, avoiding indicator confusion caused by differences in personal understanding, and being able to record and display the source, conversion process and flow of indicator data, that is, data lineage, to help users understand the story behind the data and facilitate problem troubleshooting and compliance audits.

[0064] It is understandable that, based on the above steps, the data table management platform can also update the business subject table and dimension table according to the updated initial data when the initial data is updated; correspondingly, the updated business subject table and dimension table can be used to update the business indicators corresponding to the updated initial data through the indicator management platform, thereby supporting real-time or scheduled updates to ensure the freshness of the data, and can also monitor key business indicators in real time, automatically triggering early warnings when indicators deviate from preset thresholds, allowing enterprises to quickly respond to market changes or business anomalies.

[0065] It should be pointed out that if Figure 8 As shown, the indicator management system in this embodiment also includes an analysis model, which can be a business analysis view created for a fixed scenario. Specifically, multiple indicators that need to be analyzed can be connected to tables, and the common dimensions that need to be associated can be selected. The system will also dynamically generate SQL statements for the analysis model and create synchronization tasks to synchronize the data of the analysis model to the system. In this way, users can easily compare the current value of the quantitative data with the historical same period and month-on-month growth values, intuitively identify trends and change speeds, quickly capture business pulses, and compared to comparing through multiple indicator data tables and then analyzing the factors of indicator data changes, this embodiment can support aggregating multiple indicators together, combining different dimensions, and building a more targeted analysis model. At the same time, it supports attribution analysis of indicator data, and unravels and refines the cause-effect relationship.

[0066] And, if Fig. 9 As shown, the indicator management system in this embodiment can construct a corresponding visual graph based on the first structured query statement and the second structured query statement according to the business indicators and the preset analysis model through the system operation interface, and display the visual graph. That is to say, this embodiment also supports presenting the created indicators and analysis models to the user in the form of charts, etc., to improve the efficiency of users in discovering data quality problems. Specifically, a variety of charts can be used to display data quality problems through the data visualization module, such as bar charts, line charts, pie charts, etc., so that users can deeply understand the details of data quality problems through interactive operations, and provide an intuitive interface for business users, which can query and analyze indicators by themselves according to needs, generate charts and reports, and speed up decision-making. In addition, business personnel build and maintain business indicators through a visual interface, realizing real-time synchronization of various business indicator data and building a comprehensive indicator system.

[0067] Through the above technical solutions, in this embodiment, the real-time processing capability of Apache Flink is used to connect the original data stream of the business system to achieve high-speed synchronization and integration of data, and the synchronization tasks are finely controlled through the independently developed task management model to ensure the accuracy and stability of the data. Secondly, on the basis of the subject table, the dimension table is further constructed, various business indicators and complex data models are defined, and the data query efficiency is greatly improved through technical means such as caching strategies, so that users can quickly obtain the required information, which helps to simplify the data analysis path and accelerate the decision-making process. Thirdly, through the built-in real-time monitoring mechanism, the changes in indicator data are continuously tracked. Once abnormal fluctuations outside the preset range are detected, the alarm system is immediately triggered to notify the relevant responsible persons in time to ensure that the problem is quickly responded to and handled, and business risks are effectively prevented. Finally, the data visualization function converts abstract indicator values ​​into intuitive charts, so that business personnel can grasp the operating status at a glance, identify trends and anomalies, and provide intuitive basis for business optimization and strategic decision-making. At the same time, through flexible dashboard configuration, the view can be customized as needed to deeply explore the story behind the data, drive the actual application of data intelligence in the business, and achieve seamless connection from data to insight and then to action.

[0068] Based on the previous embodiment, it can be seen that the present application can use an enterprise-level indicator management system based on big data to provide a centralized environment to manage all business indicators to ensure the uniformity and standardization of indicator definitions. Next, see Fig.10 As shown, the embodiment of the present application also discloses an enterprise-level indicator management method based on big data, including:

[0069] Step S11: Acquire the table configuration input by the user and the initial data of each source database.

[0070] Step S12: construct corresponding business subject tables and dimension tables according to the business original tables in the enterprise-level indicator management system based on the table configuration and the initial data, and determine the association relationship between the business subject tables and the dimension tables.

[0071] Step S13: Create corresponding business indicators according to the business subject table and the dimension table, and construct a first structured query statement corresponding to the business indicator according to the association relationship.

[0072] Step S14: determining a target indicator to be associated analyzed from the business indicators based on a preset analysis model according to preset indicator analysis rules, and constructing a second structured query statement corresponding to the preset analysis model based on the target indicator.

[0073] Step S15 constructs a corresponding visual graph based on the first structured query statement and the second structured query statement according to the business indicator and the preset analysis model, and displays the visual graph using the operation interface.

[0074] The above-mentioned enterprise-level indicator management method based on big data has the same beneficial effects as the above-mentioned enterprise-level indicator management system based on big data, which will not be repeated here.

[0075] Furthermore, the present application also discloses an electronic device. Fig.11 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0076] Fig.11 A schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the enterprise-level indicator management method based on big data disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0077] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0078] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0079] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, which can be Windows Server, Netware, Unix, Linux, etc. In addition to including computer programs that can be used to complete the enterprise-level indicator management method based on big data performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks.

[0080] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the enterprise-level indicator management method based on big data disclosed above is implemented. For the specific steps of the method, reference may be made to the corresponding contents disclosed in the aforementioned embodiments, and no further description will be given here.

[0081] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0082] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0083] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0084] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0085] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An enterprise-level indicator management system based on big data, characterized in that: include: System operation interface, used to obtain table configuration input by users; Data collection interface, used to obtain initial data from each source database; A data table management platform, used to construct a corresponding business subject table and a dimension table according to the business original table in the enterprise-level indicator management system based on the table configuration and the initial data, and determine the association relationship between the business subject table and the dimension table; An indicator management platform, used to create corresponding business indicators according to the business subject table and the dimension table, and construct a first structured query statement corresponding to the business indicator according to the association relationship, and determine a target indicator to be associated and analyzed from the business indicators based on a preset analysis model and preset indicator analysis rules, and construct a second structured query statement corresponding to the preset analysis model based on the target indicator; The system operation interface is also used to construct a corresponding visual graph based on the first structured query statement and the second structured query statement according to the business indicator and the preset analysis model, and display the visual graph.

2. The enterprise-level indicator management system based on big data according to claim 1 is characterized in that: The data collection interface is also used to obtain offline data in a preset relational database and to capture open data on the Internet; Correspondingly, the data table management platform is used to construct the corresponding business subject table and the dimension table according to the business original table based on the table configuration, the initial data, the offline data and the Internet open data.

3. The enterprise-level indicator management system based on big data according to claim 1 is characterized in that: The data table management platform is further used to update the business subject table and the dimension table according to the updated initial data when the initial data is updated; Correspondingly, the indicator management platform is also used to update the business indicators corresponding to the updated initial data using the updated business subject table and dimension table.

4. The enterprise-level indicator management system based on big data according to claim 3 is characterized in that: Also includes: The task manager is used to create a synchronization task according to preset synchronization task strategy information, save the synchronization task based on a preset data integration model, and execute the synchronization task to synchronize the updated business subject table and the dimension table to the enterprise-level indicator management system when the business subject table and the dimension table are updated.

5. The enterprise-level indicator management system based on big data according to claim 1 is characterized in that: The data table management platform is also used for: The third structured query statement input by the user through the system operation interface is directly obtained, and the variable setting corresponding to the third structured query statement is determined, so as to construct the corresponding business subject table and the dimension table according to the business original table according to the variable setting.

6. The enterprise-level indicator management system based on big data according to any one of claims 1 to 5, characterized in that: The indicator management platform is specifically used for: Determine a corresponding aggregation method based on the metric fields in the business subject table, and construct a corresponding atomic indicator according to the aggregation method; Determine the defined field corresponding to the atomic indicator according to the business subject table and the dimension table, and construct the corresponding derived indicator according to the defined field; A corresponding composite indicator is created according to the atomic indicator and the derived indicator based on a preset calculation formula.

7. The enterprise-level indicator management system based on big data according to claim 6 is characterized in that: The indicator management platform is specifically used for: Obtaining an indicator definition form input by the user through the system operation interface, and processing the business subject table and the dimension table according to a preset table processing rule based on the indicator definition form and the association relationship between the business subject table and the dimension table; The first structured query statements corresponding to the atomic index, the derived index and the composite index are constructed based on the processed business subject table and the dimension table.

8. An enterprise-level indicator management method based on big data, characterized in that: include: Obtain table configuration entered by the user and initial data of each source database; Based on the table configuration and the initial data, a corresponding business subject table and a dimension table are constructed according to the business original table in the enterprise-level indicator management system, and an association relationship between the business subject table and the dimension table is determined; Creating corresponding business indicators according to the business subject table and the dimension table, and constructing a first structured query statement corresponding to the business indicator according to the association relationship; Determining a target indicator to be associated analyzed from the business indicators based on a preset analysis model according to preset indicator analysis rules, and constructing a second structured query statement corresponding to the preset analysis model based on the target indicator; Based on the first structured query statement and the second structured query statement, a corresponding visual graph is constructed according to the business indicator and the preset analysis model, and the visual graph is displayed using the operation interface.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory; wherein the memory is used to store a computer program, and the computer program is loaded and executed by the processor to implement the enterprise-level indicator management system based on big data as described in claim 8.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the enterprise-level indicator management system based on big data as described in claim 8.

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