A business intelligent supervision system and method based on digital information

Abstract

The present invention discloses a business intelligent supervision system and method based on digital information, belonging to the field of business supervision technology. The present invention includes a full-time supervision module, a business data storage module, a polymorphic data analysis module and a business status feedback module; the full-time supervision module performs security identification on the enterprise business data source and performs full-time monitoring and data collection; the business data storage module marks the multi-source data, classifies and stores according to the marks and performs explicit operations on abnormal data; the polymorphic data analysis module performs value assessment, abnormal data analysis and business status analysis on the business according to the collected data; the business status feedback module performs visualization operations and comprehensive report feedback on the business information according to the data analysis results; the present invention aims to achieve full-process information transparency and real-time visualization of business development and status through the capture and comprehensive analysis of business dynamic data.

Description

Technical Field

[0001] The present invention relates to the technical field of business supervision, and in particular to a business intelligent supervision system and method based on digital information. Background Art

[0002] Business data refers to various data related to business activities, including financial statements, customer information, business orders and inventory data. These data are the basis for business data analysis and can help companies understand information such as time requirements, competition and customer preferences, so as to formulate more effective business strategies and improve business efficiency and competitiveness.

[0003] At present, the traditional business data supervision system used by most enterprises still manually enters business data into the database, and splits business data for storage and independent data analysis for different departments or fields; this model can improve business processing efficiency by splitting the business and independently processing and analyzing it, but at the same time, this model will also have the problem of business data not being shared between departments and business processes not being transparent, which will lead to a lag in business data feedback on business status. This will result in that if business data problems cannot be discovered manually, the abnormal status of the corresponding business cannot be discovered, which will affect the judgment and value assessment of the real-time business status; for decision makers, this model will also lead to a low degree of business data visualization and the inability to dynamically regulate business data based on actual conditions; at the same time, due to the existing means of data encryption, managers only need to set verification passwords for encryption protection, which is not enough to protect data security. This is easy to be invaded by external networks or to be arbitrarily called by internal personnel, and there is a risk of data leakage. Summary of the invention

[0004] The purpose of the present invention is to provide a business intelligent supervision system and method based on digital information to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A business intelligent supervision method based on digital information, the method comprising the following steps:

[0007] S100, before receiving business data, multiple data sources are securely identified, business data from each source is captured after identification, and the data source is monitored all the time;

[0008] S200, marking the captured business data as a data source and business tag, classifying and storing the tags, and performing abnormal data visualization operations on various types of business data;

[0009] S300, retrieve the stored business data, and perform business value assessment analysis, abnormal data analysis, and business status analysis on each data;

[0010] S400. Perform data visualization on the development process of the corresponding business based on the analysis results, and make a comprehensive report feedback for each business.

[0011] In S100, before receiving the business data, multiple data sources are securely identified, each source business data is captured after identification, and the data source is monitored all the time. The specific steps are as follows:

[0012] S101, before receiving data, securely identify the access path of each data source port, and after confirming the data source port, capture the output data of each business data port through Apache NiFi;

[0013] S102. Use Prometheus to implement real-time monitoring of each data source and capture dynamic changes in data from each data source.

[0014] The specific steps of performing data source and business tagging on the captured business data in S200, classifying and storing the tags, and performing abnormal data visualization operations on various types of business data are as follows:

[0015] S201, identify specific business information of captured data, determine the subject information of the current business and make subject first-level labels for business data according to the specific information; make field second-level labels for business data according to data source information of each field of business data;

[0016] S202, the marked business data is processed into a database, and a spatial level division operation is performed in the database according to the business division level; the primary spatial positioning of the business in the database is determined according to the primary label of the business, and the secondary spatial positioning of the data in each field of the business is performed in the primary space according to the secondary label of the business;

[0017] S203. After the storage space is located, the stored data is encrypted by using the same-position common secret and heterogeneous private key method; the same-position common secret is to generate a pair of identical same-position keys for the data in the secondary space and the corresponding secondary space; the heterogeneous private key is to generate corresponding heterogeneous keys between the primary space and each secondary space, and generate a corresponding heterogeneous key list; when classifying and storing business data, firstly, the identity of the authorized personnel is verified to determine whether the staff member has obtained permission to retrieve the current business data; if permission is obtained, the heterogeneous key list of the primary space after the data is located is obtained; secondly, the secondary space required for the current data is located, and the private key between the corresponding primary space and each secondary space recorded in the heterogeneous private key list is used to perform the first-level space verification; after verification, the data and the same-position key generated by the corresponding secondary space are used to perform the second-level space verification; if not obtained, the current database page is automatically exited and the database management terminal is warned;

[0018] S204: traverse the business data stored in the secondary space, and perform explicit marking operations on the data with abnormal values ​​or data with changed business information.

[0019] The specific steps of retrieving the stored business data in S300 and performing business value assessment analysis, abnormal data analysis and business status analysis on each data are as follows:

[0020] S301, determining the primary storage location of the business in the database through the business subject tag, and obtaining detailed business information by calling the corresponding business;

[0021] S302, obtaining the real-time input material resources f, estimated input material resources f′, number of business responsible personnel m, real-time business resource feedback g, estimated business resource feedback g′, real-time business development time h, and estimated business development time h′ in the retrieved information; according to the formula Calculate the real-time per capita resource feedback rate; according to the formula Calculate the estimated real-time per capita resource feedback rate; if p>p′, the business is in a high-value state; if p=p′, the business is in an average-value state; if p<p′, the business is in a low-value state; compare the per capita rate of real-time business development with the estimated value before the business is launched, and determine the value change in the current business development process through the comparison results;

[0022] S303, obtain abnormal data in the business data by calling the explicit data in the secondary space; the corresponding business data set e=[e1,e2,e3...e n ], by using historical data to construct a time trend relationship curve; where n∈N *; On the curve, with period T as the unit interval, the two intervals before and after the interval where the abnormal data is located are searched to see if there is abnormal data. If there is abnormal data, the interval with abnormal data is merged to form a new period interval T b , then search the intervals before and after the new interval again until the abnormal data interval is followed by a normal data interval; where T∈N * , T b ∈N * ;

[0023] Take the maximum value e of the curve e value on the normal data interval and the abnormal data interval respectively max and the minimum value e min According to the formula Calculate the value of e at the median point of each interval; take e>e in each interval mid The time period t corresponding to the value up , take e<e mid The time period t corresponding to the value down According to the formula Calculate the influence coefficient of the part of the curve above the midpoint on the development of the curve within the cycle; according to the formula Calculate the influence coefficient of the part of the curve below the midpoint on the development of the curve within the cycle; according to the formula k z =k up *k down Calculate the development influence coefficient of the curve within the period; according to the formula Calculate the influence of the part of the curve above the midpoint on the development of the curve within the cycle; according to the formula Calculate the influence of the part of the curve below the median point on the development of the curve within the period; within the interval, determine the influence coefficient of the corresponding part on the development trend of the curve within the interval by calculating the time proportion of the upper and lower parts of the median point respectively, and determine the overall development trend coefficient of the interval by calculating the average of the upper and lower coefficients; obtain the influence of different parts on the development of the business data curve by comparing the product of the corresponding coefficient and the value of the business data occupied by the corresponding part with the interval coefficient and the value of the business data occupied by the interval; then the development trend degree of the curve within the period w 总 According to the formula w 总 =w up +w down -w up *w down Calculate the curve trend within the periodic interval by subtracting the combined influence of the upper and lower parts from the sum of the influence of the upper and lower parts, so that the curve development trend within the interval can be accurately combined by the two parts; calculate the average difference between the curve trend of the abnormal data interval and the normal data interval, and the calculation formula is: Among them, w 异总is the development trend of the abnormal data interval curve, w 常1总 is the development trend of the previous normal data interval curve, w 常2总 is the development trend of the post-normal data interval curve; if u≤|w 常2总 -w 常1总 |, it indicates that the abnormal data interval is correct data; otherwise, it indicates that the abnormal data interval is wrong data;

[0024] S304. Qualitatively characterize the real-time status of the business based on the business value assessment results and abnormal data analysis results; if the business is of average value or high value and the data is normal, the current business is in a high-quality business state; if the business is of low value and the data is normal or erroneous, the current business is in an abnormal business state.

[0025] The specific steps of performing data visualization operation on the development process of the corresponding business according to the analysis results and making a comprehensive report feedback for each business in S400 are as follows:

[0026] S401, by performing multi-threaded mixed display of trend development curves of various business data, the real-time development progress of the business is visualized;

[0027] S402: Provide a status feedback report of the current business on the side of the visual display, and display the current business status in detail.

[0028] A business intelligent supervision system based on digital information, the business intelligent supervision system based on digital information includes a full-time supervision module, a business data transmission module, a polymorphic data analysis module, and a business status feedback module;

[0029] The full-time monitoring module is used to identify the data source of the enterprise's real-time business information, monitor each data source full-time and collect business data; the business data storage module marks multi-source data, classifies and stores the multi-source data according to the data marks, and performs abnormal data visualization operations on the business data; the polymorphic data analysis module evaluates the value of the business according to the business data, and analyzes the business status of the business's manifested abnormal data; the business status feedback module performs multi-precision visualization operations on the data in various fields of the business according to the business analysis results, and makes feedback reports on the comprehensive business analysis data;

[0030] The full-time supervision module is connected to the business data storage module; the business data storage module is connected to the polymorphic data analysis module; the polymorphic data analysis module is connected to the business status feedback module.

[0031] The full-time supervision module includes a data source identification unit, a full-time monitoring unit and a business data capture unit; the data source identification unit securely identifies the data source through the data source access port path, and stores the identified source data; the full-time monitoring unit monitors the data of each data source full-time through Prometheus to sense the dynamic changes of business data; the business data capture unit is used to capture the business data generated by the successfully identified data source through Apache NiFi.

[0032] The business data storage module includes a multi-source data labeling unit, a same-label classification storage unit and an abnormal data visualization unit; the multi-source data labeling unit performs primary labeling on the captured business data according to different businesses and secondary labeling on the data according to different data sources; the same-label classification storage unit divides the storage space and performs hierarchical storage according to the label level of the business data; the storage space of the data is determined by the primary label of the business data, and then the data type is divided and stored in the corresponding data storage space according to the secondary label of the business data; the abnormal data visualization unit extracts abnormal data from the stored business data and marks this part of the data as abnormal.

[0033] The polymorphic data analysis module includes a business value assessment unit, a business data anomaly analysis unit and a business status analysis unit; the business value assessment unit determines the value index of the current business by analyzing the required personnel resources, the required time resources, the required costs and the profits earned, and classifies different businesses according to the business value assessment results; the business data anomaly analysis unit performs data context analysis on the abnormal point data in different categories of business data to determine whether the abnormal data is erroneous data; the business status analysis unit analyzes the status of the business in combination with the business value assessment results and the business anomaly data analysis results, and characterizes the business according to the analysis results.

[0034] The business status feedback module includes a business data visualization unit and a business comprehensive report feedback unit; the business data visualization unit displays the overall trend development trend diagram of different businesses based on the analysis results of the business data, and draws a high-precision trend diagram for the data of the same business in different fields; the business comprehensive report feedback unit provides comprehensive report feedback based on the current status and value of the business.

[0035] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention includes multiple modules to realize real-time data collection, inspection, storage, analysis and feedback functions throughout the business process; the polymorphic data analysis module can realize real-time value assessment of the business, so that business personnel can accurately judge the business progress and value status; at the same time, the analysis of abnormal data can facilitate the intuitive visibility of business data for business personnel through comparative analysis of the trend development degree of the curve interval, reduce the data review tasks of business personnel, and ensure the accuracy and effectiveness of business data; the present invention aims to realize the transparency of information throughout the business process and the timely judgment and processing of real-time value and abnormal data in the process of business development by capturing and comprehensively analyzing business dynamic data, so as to ensure delayed processing and error occurrence in the process of business development. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0037] Figure 1 It is a structural schematic diagram of a business intelligent supervision system based on digital information of the present invention;

[0038] Figure 2 It is a schematic diagram of the steps of a business intelligent supervision method based on digital information of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] See also Figure 1-Figure 2 , the present invention provides a technical solution:

[0041] A business intelligent supervision method based on digital information, the method comprising the following steps:

[0042] S100, before receiving business data, multiple data sources are securely identified, business data from each source is captured after identification, and the data source is monitored all the time;

[0043] S200, marking the captured business data as a data source and business tag, classifying and storing the tags, and performing abnormal data visualization operations on various types of business data;

[0044] S300, retrieve the stored business data, and perform business value assessment analysis, abnormal data analysis, and business status analysis on each data;

[0045] S400. Perform data visualization on the development process of the corresponding business based on the analysis results, and make a comprehensive report feedback for each business.

[0046] In S100, before receiving the business data, multiple data sources are securely identified, each source business data is captured after identification, and the data source is monitored all the time. The specific steps are as follows:

[0047] S101, before receiving data, securely identify the access path of each data source port, and after confirming the data source port, capture the output data of each business data port through Apache NiFi;

[0048] S102. Use Prometheus to implement real-time monitoring of each data source and capture dynamic changes in data from each data source.

[0049] The specific steps of performing data source and business tagging on the captured business data in S200, classifying and storing the tags, and performing abnormal data visualization operations on various types of business data are as follows:

[0050] S201, identify specific business information of captured data, determine the subject information of the current business and make subject first-level labels for business data according to the specific information; make field second-level labels for business data according to data source information of each field of business data;

[0051] S202, the marked business data is processed into a database, and a spatial level division operation is performed in the database according to the business division level; the primary spatial positioning of the business in the database is determined according to the primary label of the business, and the secondary spatial positioning of the data in each field of the business is performed in the primary space according to the secondary label of the business;

[0052] S203. After the storage space is located, the stored data is encrypted by using the same-position common secret and heterogeneous private key method; the same-position common secret is to generate a pair of identical same-position keys for the data in the secondary space and the corresponding secondary space; the heterogeneous private key is to generate corresponding heterogeneous keys between the primary space and each secondary space, and generate a corresponding heterogeneous key list; when classifying and storing business data, firstly, the identity of the authorized personnel is verified to determine whether the staff member has obtained permission to retrieve the current business data; if permission is obtained, the heterogeneous key list of the primary space after the data is located is obtained; secondly, the secondary space required for the current data is located, and the private key between the corresponding primary space and each secondary space recorded in the heterogeneous private key list is used to perform the first-level space verification; after verification, the data and the same-position key generated by the corresponding secondary space are used to perform the second-level space verification; if not obtained, the current database page is automatically exited and the database management terminal is warned;

[0053] S204: traverse the business data stored in the secondary space, and perform explicit marking operations on the data with abnormal values ​​or data with changed business information.

[0054] The specific steps of retrieving the stored business data in S300 and performing business value assessment analysis, abnormal data analysis and business status analysis on each data are as follows:

[0055] S301, determining the primary storage location of the business in the database through the business subject tag, and obtaining detailed business information by calling the corresponding business;

[0056] S302, obtaining the real-time input material resources f, estimated input material resources f′, number of business responsible personnel m, real-time business resource feedback g, estimated business resource feedback g′, real-time business development time h, and estimated business development time h′ in the retrieved information; according to the formula Calculate the real-time per capita resource feedback rate; according to the formula Calculate the estimated real-time per capita resource feedback rate; if p>p′, the business is in a high-value state; if p=p′, the business is in an average-value state; if p<p′, the business is in a low-value state;

[0057] S303, obtain abnormal data in the business data by calling the explicit data in the secondary space; the corresponding business data set e=[e1,e2,e3...e n ], by using historical data to construct a time trend relationship curve; where n∈N *; On the curve, with period T as the unit interval, the two intervals before and after the interval where the abnormal data is located are searched to see if there is abnormal data. If there is abnormal data, the interval with abnormal data is merged to form a new period interval T b , then search the intervals before and after the new interval again until the abnormal data interval is followed by a normal data interval; where T∈N * , T b ∈N * ;

[0058] Take the maximum value e of the curve e value on the normal data interval and the abnormal data interval respectively max and the minimum value e min According to the formula Calculate the value of e at the median point of each interval; take e>e in each interval mid The time period t corresponding to the value up , take e<e mid The time period t corresponding to the value down According to the formula Calculate the influence coefficient of the part of the curve above the midpoint on the development of the curve within the cycle; according to the formula Calculate the influence coefficient of the part of the curve below the midpoint on the development of the curve within the cycle; according to the formula k z =k up *k down Calculate the development influence coefficient of the curve within the period; according to the formula Calculate the influence of the part of the curve above the midpoint on the development of the curve within the cycle; according to the formula Calculate the influence of the part of the curve below the midpoint on the development of the curve within the cycle; then the development trend of the curve within the cycle w 总 According to the formula w 总 =w up +w down -w up *w down Calculate the average difference between the abnormal data interval and the normal data interval, and the calculation formula is: Among them, w 异总 is the development trend of the abnormal data interval curve, w 常1总 is the development trend of the previous normal data interval curve, w 常2总 is the development trend of the post-normal data interval curve; if u≤|w 常2总 -w 常1总 |, it indicates that the abnormal data interval is correct data; otherwise, it indicates that the abnormal data interval is wrong data;

[0059] S304. Qualitatively characterize the real-time status of the business based on the business value assessment results and abnormal data analysis results; if the business is of average value or high value and the data is normal, the current business is in a high-quality business state; if the business is of low value and the data is normal or erroneous, the current business is in an abnormal business state.

[0060] The specific steps of performing data visualization operation on the development process of the corresponding business according to the analysis results and making a comprehensive report feedback for each business in S400 are as follows:

[0061] S401, by performing multi-threaded mixed display of trend development curves of various business data, the real-time development progress of the business is visualized;

[0062] S402: Provide a status feedback report of the current business on the side of the visual display, and display the current business status in detail.

[0063] A business intelligent supervision system based on digital information, the business intelligent supervision system based on digital information includes a full-time supervision module, a business data transmission module, a polymorphic data analysis module, and a business status feedback module;

[0064] The full-time monitoring module is used to identify the data source of the enterprise's real-time business information, monitor each data source full-time and collect business data; the business data storage module marks multi-source data, classifies and stores the multi-source data according to the data marks, and performs abnormal data visualization operations on the business data; the polymorphic data analysis module evaluates the value of the business according to the business data, and analyzes the business status of the business's manifested abnormal data; the business status feedback module performs multi-precision visualization operations on the data in various fields of the business according to the business analysis results, and makes feedback reports on the comprehensive business analysis data;

[0065] The full-time supervision module is connected to the business data storage module; the business data storage module is connected to the polymorphic data analysis module; the polymorphic data analysis module is connected to the business status feedback module.

[0066] The full-time supervision module includes a data source identification unit, a full-time monitoring unit and a business data capture unit; the data source identification unit securely identifies the data source through the data source access port path, and stores the identified source data; the full-time monitoring unit monitors the data of each data source full-time through Prometheus to sense the dynamic changes of business data; the business data capture unit is used to capture the business data generated by the successfully identified data source through Apache NiFi.

[0067] The business data storage module includes a multi-source data marking unit, a same-mark classification storage unit and an abnormal data visualization unit; the multi-source data marking unit performs primary labeling on the captured business data according to different businesses and performs secondary labeling on the data according to different data sources; the same-mark classification storage unit divides the storage space and performs hierarchical storage according to the label level of the business data; the abnormal data visualization unit extracts abnormal data from the stored business data and marks this part of the data as abnormal.

[0068] The polymorphic data analysis module includes a business value assessment unit, a business data anomaly analysis unit and a business status analysis unit; the business value assessment unit determines the value index of the current business by analyzing the required personnel resources, the required time resources, the required costs and the profits earned, and classifies different businesses according to the business value assessment results; the business data anomaly analysis unit performs data context analysis on the abnormal point data in different categories of business data to determine whether the abnormal data is erroneous data; the business status analysis unit analyzes the status of the business in combination with the business value assessment results and the business anomaly data analysis results, and characterizes the business according to the analysis results.

[0069] The business status feedback module includes a business data visualization unit and a business comprehensive report feedback unit; the business data visualization unit displays the overall trend development trend diagram of different businesses based on the analysis results of the business data, and draws a high-precision trend diagram for the data of the same business in different fields; the business comprehensive report feedback unit provides comprehensive report feedback based on the current status and value of the business.

[0070] In the example:

[0071] In practice, a certain enterprise adopts a business intelligent supervision system based on digital information. After the data source is securely identified, Prometheus is used to realize real-time monitoring of each data source, and Apache NiFi is used to capture the output data of each business data port. At present, a business J data is captured by the system, and the business data is labeled as the subject at the first level with H as the subject, and the field secondary label is made according to the specific data of the business, such as financial data, customer data and time data. The marked business data is put into the database for data storage, and the space level division operation is performed in the database according to the business division level; the primary space positioning of the business in the database is determined according to the business primary label, and the secondary space positioning of the business field data in the primary space is performed according to the business secondary label; after completing the storage space positioning, the business data is classified and stored; the business data in the stored secondary space is traversed, and the data with abnormal values ​​or changed business information is marked for explicit marking;

[0072] Determine the primary storage location of the business in the database through the business subject tag, obtain detailed business information by calling the corresponding business, and obtain the real-time investment cost of the business of 2,000 yuan, the estimated investment cost of 5,000 yuan, the number of business responsible persons of 3 people, the real-time profit of the business of 3,000 yuan, the estimated business profit of 10,000 yuan, the real-time development time of the business of 3 days, and the estimated time of the business of 7 days; according to the formula The real-time average profit rate per capita is calculated to be 0.05; according to the formula The estimated real-time per capita profit rate is 0.11; since p<p′, the current business is in a low-value state;

[0073] By calling explicit data in the secondary space, abnormal data in the business data is obtained, among which the profit data e of the business has abnormal data; by using historical data to construct a time trend relationship curve, on the curve, with a period of 5 hours as a unit interval, the two intervals before and after the interval where the abnormal data is located are searched for abnormal data. If there is no abnormal data before and after the abnormal data interval, the maximum value e of the curve e value on the normal data interval and the abnormal data interval is taken respectively. max and the minimum value e min , where the maximum and minimum values ​​of the previous normal interval are 2100, 2000; the maximum and minimum values ​​of the later normal interval are 2700, 2500; the maximum and minimum values ​​of the abnormal interval are 2800, 2400; according to the formula The median point of the normal interval before calculation is 2050, the median point of the normal interval after calculation is 2600, and the median point of the abnormal interval is 2600; respectively, e>e is taken in the normal data interval mid The time period t corresponding to the value up , take e<e mid The time period t corresponding to the value down ,; the previous normal data interval t up =2, t down is 3; the normal data interval t up is 2.5, t down is 2.5; abnormal data interval t up =3, t down is 2; according to the formula Calculate the influence coefficient of the part of the curve above the midpoint on the development of the curve within the cycle, then the previous normal data interval k up is 0.4, and the normal data interval k up is 0.5, the abnormal data interval k up is 0.6; according to the formula Calculate the influence coefficient of the part of the curve below the midpoint on the development of the curve within the cycle, then the previous normal data interval k downis 0.6, and the normal data interval k down is 0.5; abnormal data interval k down is 0.4; according to the formula k z =k up *k down Calculate the development influence coefficient of the curve in the period, then the previous normal data interval k z is 0.24, and the normal data interval k z is 0.25, the abnormal data interval k z is 0.24; according to the formula Calculate the influence of the part of the curve above the midpoint on the development of the curve within the cycle, then the previous normal data interval w up is 0.83, and the normal data interval w up is 1, abnormal interval w up is 1.25; according to the formula Calculate the influence of the part of the curve below the midpoint on the development of the curve within the cycle, then the previous normal data interval w down is 1.25, and the normal data interval w down is 1, abnormal interval w down is 0.83; then the development trend of the curve within the cycle is w 总 According to the formula w 总 =w up +w down -w up *w down Calculate the normal data interval w before obtaining 常1总 is 1.04, and the normal data interval w 常2总 is 1, abnormal interval w 异总 is 1.04; the average difference between the curve trend of the abnormal data interval and the normal data interval is calculated, and the calculation formula is: u is 0.02; since u≤|w 常2总 -w 常1总 |=0.04, then the abnormal data interval is normal data; in summary, the business is currently of low value and the data is normal, that is, it is an abnormal business state; the corresponding data is visualized and the abnormal state of the current business is fed back.

[0074] 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.

[0075] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A business intelligent supervision method based on digital information, characterized in that: The method comprises the following steps: S100, before receiving business data, multiple data sources are securely identified, business data from each source is captured after identification, and the data source is monitored all the time; S200, marking the captured business data as a data source and business tag, classifying and storing the tags, and performing abnormal data visualization operations on various types of business data; The specific steps of performing data source and business tagging on the captured business data in S200, classifying and storing the tags, and performing abnormal data visualization operations on various types of business data are as follows: S201, identify specific business information of captured data, determine the subject information of the current business and make subject first-level labels for business data according to the specific information; make field second-level labels for business data according to data source information of each field of business data; S202, the marked business data is processed into a database, and a spatial level division operation is performed in the database according to the business division level; the primary spatial positioning of the business in the database is determined according to the primary label of the business, and the secondary spatial positioning of the data in each field of the business is performed in the primary space according to the secondary label of the business; S203. After the storage space is located, the stored data is encrypted by using the same-position common secret and heterogeneous private key methods; the same-position common secret is to generate a pair of identical same-position keys for the data in the secondary space and the corresponding secondary space; the heterogeneous private key is to generate corresponding heterogeneous keys between the primary space and each secondary space, and generate a corresponding heterogeneous key list; when classifying and storing business data, firstly, the identity of the authorized personnel is verified to determine whether the staff has obtained permission to retrieve the current business data; if permission is obtained, the heterogeneous key list of the primary space after the data is located is obtained; secondly, the secondary space required for the current data is located, and the private key between the corresponding primary space and each secondary space recorded in the heterogeneous private key list is used to perform the first-level space verification; after verification, the data and the same-position key generated by the corresponding secondary space are used to perform the second-level space verification; if not obtained, the current database page is automatically exited and the database management terminal is warned; S204, traversing the business data stored in the secondary space, and performing a visible marking operation on the data with abnormal values ​​or the data with changed business information; S300, retrieve the stored business data, and perform business value assessment analysis, abnormal data analysis, and business status analysis on each data; The specific steps of retrieving the stored business data in S300 and performing business value assessment analysis, abnormal data analysis and business status analysis on each data are as follows: S301, determining the primary storage location of the business in the database through the business subject tag, and obtaining detailed business information by calling the corresponding business; S302, obtaining the real-time input material resources f, estimated input material resources f′, number of business responsible personnel m, real-time business resource feedback g, estimated business resource feedback g′, real-time business development time h, and estimated business development time h′ in the retrieved information; according to the formula Calculate the real-time per capita resource feedback rate; according to the formula Calculate the estimated real-time per capita resource feedback rate; if p>p′, the business is in a high-value state; if p=p′, the business is in an average-value state; if p<p′, the business is in a low-value state; S303, obtain abnormal data in the business data by calling the explicit data in the secondary space; the corresponding business data set e=[e1,e2,e3...e n ], by using historical data to construct a time trend relationship curve; where n∈N * ; On the curve, with period T as the unit interval, the two intervals before and after the interval where the abnormal data is located are searched to see if there is abnormal data. If there is abnormal data, the interval with abnormal data is merged to form a new period interval T b , then search the intervals before and after the new interval again until the abnormal data interval is followed by a normal data interval; where T∈N * , T b ∈N * ; Take the maximum value e of the curve e value on the normal data interval and the abnormal data interval respectively max and the minimum value e min According to the formula Calculate the value of e at the median point of each interval; take e>e in each interval mid The time period t corresponding to the value up , take e<e mid The time period t corresponding to the value down According to the formula Calculate the influence coefficient of the part of the curve above the midpoint on the development of the curve within the cycle; according to the formula Calculate the influence coefficient of the part of the curve below the midpoint on the development of the curve within the cycle; according to the formula k z =k up *k down Calculate the development influence coefficient of the curve within the period; according to the formula Calculate the influence of the part of the curve above the midpoint on the development of the curve within the cycle; according to the formula Calculate the influence of the part of the curve below the midpoint on the development of the curve within the cycle; then the development trend of the curve within the cycle w 总 According to the formula w 总 =w up +w down -w up *w down Calculate the average difference between the abnormal data interval and the normal data interval, and the calculation formula is: Among them, w 异总 is the development trend of the abnormal data interval curve, w 常1总 is the development trend of the previous normal data interval curve, w 常2总 is the development trend of the post-normal data interval curve; if u≤|w 常2总 -w 常1总 |, it indicates that the abnormal data interval is correct data; otherwise, it indicates that the abnormal data interval is wrong data; S304. Qualitatively characterize the real-time status of the business according to the business value assessment result and the abnormal data analysis result; if the business is of average value or high value and the data is normal, the current business is in a high-quality business state; if the business is of low value and the data is normal or wrong, the current business is in an abnormal business state; S400. Perform data visualization on the development process of the corresponding business based on the analysis results, and make a comprehensive report feedback for each business.

2. A business intelligent supervision method based on digital information according to claim 1, characterized in that: In S100, before receiving the business data, multiple data sources are securely identified, each source business data is captured after identification, and the data source is monitored all the time. The specific steps are as follows: S101, before receiving data, securely identify the access path of each data source port, and after confirming the data source port, capture the output data of each business data port through Apache NiFi; S102. Use Prometheus to implement real-time monitoring of each data source and capture dynamic changes in data from each data source.

3. A business intelligent supervision method based on digital information according to claim 2, characterized in that: The specific steps of performing data visualization operation on the development process of the corresponding business according to the analysis results and making a comprehensive report feedback for each business in S400 are as follows: S401, by performing multi-threaded mixed display of trend development curves of various business data, the real-time development progress of the business is visualized; S402: Provide a status feedback report of the current business on the side of the visual display, and display the current business status in detail.

4. A business intelligent supervision system based on digital information, using a business intelligent supervision method based on digital information as claimed in any one of claims 1 to 3, characterized in that: The business intelligent supervision system based on digital information includes a full-time supervision module, a business data transmission module, a polymorphic data analysis module, and a business status feedback module; The full-time monitoring module is used to identify the data source of the enterprise's real-time business information, monitor each data source full-time and collect business data; the business data storage module marks multi-source data, classifies and stores the multi-source data according to the data marks, and performs abnormal data visualization operations on the business data; the polymorphic data analysis module evaluates the value of the business according to the business data, and analyzes the business status of the business's manifested abnormal data; the business status feedback module performs multi-precision visualization operations on the data in various fields of the business according to the business analysis results, and makes feedback reports on the comprehensive business analysis data; The full-time supervision module is connected to the business data storage module; the business data storage module is connected to the polymorphic data analysis module; the polymorphic data analysis module is connected to the business status feedback module.

5. The business intelligent supervision system based on digital information according to claim 4 is characterized in that: The full-time supervision module includes a data source identification unit, a full-time monitoring unit and a business data capture unit; The data source identification unit securely identifies the data source through the data source access port path, and stores the identified source data in the warehouse; the full-time monitoring unit monitors the data of each data source full-time through Prometheus to sense the dynamic changes of business data; The business data capturing unit is used to capture the business data generated by the successfully identified data source through Apache NiFi.

6. The business intelligent supervision system based on digital information according to claim 5 is characterized by: The business data storage module includes a multi-source data labeling unit, a same-label classification storage unit and an abnormal data visualization unit; the multi-source data labeling unit labels the captured business data first according to different businesses and labels the data second according to different data sources; the same-label classification storage unit divides the storage space and performs hierarchical progressive storage according to the label level of the business data; The abnormal data visualization unit extracts abnormal data from the stored business data and marks the data as abnormal.

7. The business intelligent supervision system based on digital information according to claim 6 is characterized by: The polymorphic data analysis module includes a business value assessment unit, a business data anomaly analysis unit and a business status analysis unit; the business value assessment unit analyzes the required personnel resources, time resources, costs and profits to determine the value index of the current business, and classifies different businesses according to the business value assessment results; the business data anomaly analysis unit performs data context analysis on abnormal point data in different categories of business data to determine whether the abnormal data is erroneous data; The business status analysis unit analyzes the business status in combination with the evaluation result of the business value and the analysis result of the business abnormal data, and characterizes the business according to the analysis result.

8. The business intelligent supervision system based on digital information according to claim 7 is characterized by: The business status feedback module includes a business data visualization unit and a business comprehensive report feedback unit; the business data visualization unit displays the overall trend development trend diagram of different businesses based on the analysis results of the business data, and draws a high-precision trend diagram for the data of the same business in different fields; The business comprehensive report feedback unit performs comprehensive report feedback according to the current status and value of the business.

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