Data analysis management system and method

Abstract

The invention discloses a data analysis management system and method, and the system comprises a data collection module which is used for collecting historical activity data, industry data and environment data, and is composed of a historical activity database, a market data collection module and an environment data collection module; the data processing module is used for cleaning and standardizing the data acquired by the data processing module; the activity prediction model is used for predicting activities according to historical activity data, industry data and environment data, and the prediction range comprises activity effect prediction, activity risk prediction and activity participant number prediction; and a collaborative management platform. According to the method, the scientificity and the accuracy of activity planning are improved, the planning risk is reduced, the resource utilization is optimized, the planning period is shortened, the working efficiency is improved, and the method is suitable for companies or individual users needing to frequently plan various activities.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis management, and more particularly, to a data analysis management system and method. BACKGROUND

[0002] Data analysis management refers to the whole process management of collecting, processing, analyzing and applying data through a systematic method.

[0003] Traditional activity planning relies heavily on personal experience and is difficult to standardize and replicate. The new employee training cycle is long, and the loss of talents leads to knowledge gaps. Historical activity data lacks systematic sedimentation. Market data and execution data are fragmented. Budget allocation lacks scientific basis. The efficiency of resource scheduling in emergency situations is low. SUMMARY

[0004] In view of the problems in the prior art, the purpose of the present application is to provide a data analysis management system and method to solve the problems in the background art.

[0005] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows: a data analysis management system, comprising:

[0006] A data acquisition module is configured to acquire historical activity data, industry data and environmental data. The data acquisition module is composed of a historical activity database, a market data acquisition module and an environmental data acquisition module.

[0007] A data processing module is configured to clean and standardize the data collected by the data processing module.

[0008] An activity prediction model is configured to predict activities based on historical activity data, industry data and environmental data. The prediction range includes activity effect prediction, activity risk prediction and activity participant number prediction.

[0009] A collaborative management platform is configured to integrate, manage and process resources, time and processes according to the prediction results of the activity prediction model.

[0010] The collaborative management platform includes a permission matrix management model, a task allocation module and a data conflict detection module. The permission matrix management model assigns each manager an activity role, and each role corresponds to the permissions of the role. The task allocation module allocates tasks to each role according to the prediction results of the activity prediction model and historical activity data. The data conflict detection module detects the modification content, application content and task completion degree of each manager to determine whether a conflict occurs between each role.

[0011] Further description of the above technical scheme:

[0012] The historical activity database is used for storing basic information, participation data and effect indicators of previous activities; the market data collection module is used for collecting industry trends, competitor activity data and audience portraits of the industry corresponding to the activity; and the environment data collection module is used for obtaining weather, surrounding traffic state data and holding time of the activity holding place.

[0013] As a further description of the above technical solution:

[0014] The activity prediction model comprises a participation prediction module, a financial prediction module, an effect prediction module and a risk prediction module, the participation prediction module is used for predicting the range of the number of participants according to the activity publicity mode; the financial prediction module is used for predicting the activity cost and the income, wherein the activity cost comprises the site cost, the personnel configuration cost and the material demand cost, and the activity income comprises the ticket income, the sponsorship income and the derivative income; the effect prediction module is used for predicting the activity influence and the activity satisfaction; and the risk prediction module is used for predicting the resource conflict, the external risk and the activity expected underperformance.

[0015] As a further description of the above technical solution:

[0016] In the financial prediction module, the ticket income is predicted based on the prediction result of the participation prediction module, the sponsorship income is predicted based on the prediction result of the effect prediction module, and the derivative income is predicted based on the surrounding sales environment of the holding place.

[0017] As a further description of the above technical solution:

[0018] The data conflict detection module provides a solution according to a resource conflict resolution formula, and the specific formula is as follows:

[0019] When a new task tn is added, the following is calculated:

[0020]

[0021] Wherein, A j (t) is the available amount at time t, q j is the total available amount, d n is the duration of the new task tn, m j is the resource, and R n is the required resource type.

[0022] As a further description of the above technical solution:

[0023] The prediction input of the activity prediction model is real-time input, which changes with the data collected by the data collection module.

[0024] The application also adopts:

[0025] A management method of a data analysis management system, including a data analysis management system, the specific steps are as follows:

[0026] Step one, through the historical activity database, the market data acquisition module and the environment data acquisition module constitute the data acquisition module to collect the data of the past activities, the industry data and the environment data, and then the data processing module is cleaned and standardized to the collected data;

[0027] Step two, the activity prediction model receives the data processed by the data processing module, and the data is used as real-time input data, which is completed by the participation prediction module, the financial prediction module, the effect prediction module and the risk prediction module, and the activity prediction result is obtained;

[0028] Step three, according to the prediction result of the activity prediction model, the task allocation module is allocated to each role, the management right and the task of each role are allocated to the management personnel by the right matrix management model, and the data conflict detection module is used to calculate and judge the task conflict in the activity arrangement implementation process.

[0029] Compared with the prior art, the advantages of the present application are:

[0030] (1) the scheme, intuitively reduce the data analysis threshold, flexible modular design adapts to different types of activity demand, improves the scientific nature and precision of activity planning, reduces the planning risk, optimizes the resource utilization, shortens the planning cycle, improves the work efficiency, and is suitable for the company or individual user who needs to plan various activities frequently.

[0031] (2) the scheme, under the change of activity requirements, the resources are redistributed by recalculating the resources to meet the smooth progress of each node task, and the management personnel of each project can quickly understand the resource change and reasonably control. DETAILED DESCRIPTION

[0032] Figure 1 The principle diagram of the activity data analysis management of the present application;

[0033] Figure 2 The principle diagram of the data acquisition module of the present application;

[0034] Figure 3 The principle diagram of the activity prediction model of the present application;

[0035] Figure 4 The principle diagram of the collaborative management platform of the present application;

[0036] Figure 5 The principle diagram of the activity data analysis management of the present application.

[0037] Explanation of reference numerals in the drawings:

[0038] 1, data collection module; 11, historical activity database; 12, market data collection module; 13, environmental data collection module; 2, data processing module; 3, activity prediction model; 31, participation prediction module; 32, financial prediction module; 33, effect prediction module; 34, risk prediction module; 4, collaborative management platform; 41, permission matrix management model; 42, task allocation module; 43, data conflict detection module. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application;

[0040] Please refer to Figures 1-5 , the present application provides example 1:

[0041] A data analysis management system, comprising: a data collection module 1, the data collection module 1 is used for collecting historical activity data, industry data and environmental data, the data collection module 1 is composed of a historical activity database 11, a market data collection module 12 and an environmental data collection module 13, the historical activity database 11 is used for storing the basic information, participation data and effect index of the previous activities; the market data collection module 12 is used for collecting the industry trend, competitor activity data and audience portrait of the corresponding industry of the activity; the environmental data collection module 13 is used for obtaining the weather, surrounding traffic state data and holding time of the activity holding place; a data processing module 2, the data processing module 2 is used for cleaning and standardizing the data collected by the data processing module 2; an activity prediction model 3, the activity prediction model 3 is used for predicting the activity according to the historical activity data, industry data and environmental data, the prediction range includes activity effect prediction, activity risk prediction and activity participant number prediction; a collaborative management platform 4, the collaborative management platform 4 integrates activity resources, time management and process management according to the prediction results of the activity prediction model 3.

[0042] The collaborative management platform 4 includes a permission matrix management model 41, a task allocation module 42 and a data conflict detection module 43, the permission matrix management model 41 allocates each manager to an activity role, and each role corresponds to the permission of the role; the task allocation module 42 allocates tasks to each role according to the prediction results of the activity prediction model 3 and the historical activity data; the data conflict detection module 43 detects the modification content, application content and task completion degree of each manager, so as to judge whether the tasks between each role conflict.

[0043] The data acquisition module 1 collects multi-directional data related to activities, such as historical activity data and industry trend data, to accurately determine the activity range, and fully consider the influence of the activity location environment on the activity, then multi-source fusion data, the collected data is processed by the data processing module 2 and input into the activity prediction model 3, the activity prediction model 3 adopts traditional model multivariate linear regression, time series analysis model, and outputs the prediction result through the activity prediction model 3, then according to the prediction result, the activity planning direction is determined, then the collaborative management platform 4 classifies tasks, allocates tasks and solves implementation conflicts according to the prediction result to quickly promote the activity implementation progress, improve the scientificity and accuracy of activity planning, reduce planning risk, optimize resource utilization, shorten planning cycle and improve work efficiency, and is suitable for companies or individual users who need to frequently plan various activities.

[0044] The activity prediction model 3 includes a participation prediction module 31, a financial prediction module 32, an effect prediction module 33 and a risk prediction module 34, the participation prediction module 31 is used for predicting the number of activity participants according to the activity promotion method; the financial prediction module 32 is used for predicting the activity cost and the income, wherein the activity cost includes the site cost, the personnel configuration cost and the material demand cost, the activity income includes the ticket income, the sponsorship income and the derivative income; the effect prediction module 33 is used for predicting the activity influence and the activity satisfaction; the risk prediction module 34 is used for predicting the resource conflict, the external risk and the activity expected underperformance.

[0045] The systematic prediction model construction can make the activity planner more scientifically evaluate the potential effect of different schemes, optimize resource allocation, and identify potential risks in advance, significantly improve the success rate of activity planning and the return on investment.

[0046] Please refer to Figures 1-5 , the present application provides embodiment 2 on the basis of embodiment 1:

[0047] The data conflict detection module 43 provides a solution according to the resource conflict solving formula, and the specific formula is as follows:

[0048] When a new task tn is added, calculate

[0049]

[0050] Where, A j (τ) is the available amount at time t, q j is the total available amount, d n is the duration of the new task tn, m j is the type of resource, R n is the required resource type.

[0051] As activity requirements change, newly added tasks can easily cause resource allocation conflicts or over-specification. In this case, problems will arise if activity planning is managed according to the original plan. By recalculating resources and reallocating them, we can ensure the smooth progress of tasks at each node. This allows managers of each project to quickly understand resource changes and control them reasonably.

[0052] The prediction input of the activity prediction model 3 is a real-time input, which changes with the data collected by the data collection module 1 .

[0053] The data collected by the data collection module 1 changes, and the forecast is adjusted according to the real-time data during the activity implementation period.

[0054] See also Figures 1-5 , the present invention further provides Example 3 based on Example 1 and Example 2:

[0055] A management method for a data analysis management system, including a management method for a data analysis management system, wherein the specific steps are as follows:

[0056] Step 1: The data collection module 1 is composed of the historical activity database 11, the market data collection module 12 and the environmental data collection module 13 to collect the historical activity data, industry data and environmental data, and then the collected data is cleaned and standardized by the data processing module 2;

[0057] Step 2: The activity prediction model 3 receives the data processed by the data processing module 2 and uses this data as real-time input data to complete a multi-faceted prediction via the participation prediction module 31, the financial prediction module 32, the effect prediction module 33, and the risk prediction module 34 to obtain the activity prediction results.

[0058] Step 3. The collaborative management platform 4 assigns activity tasks to each role through the task allocation module 42 based on the prediction results of the activity prediction model 3. The authority matrix management model 41 distributes the management authority and tasks of each role to the management personnel. During the implementation of the activity arrangement, the data conflict detection module 43 calculates and determines task conflicts in real time to promote the progress of the activity arrangement implementation.

[0059] The above description is merely a preferred embodiment of the present invention; however, the scope of protection of the present invention is not limited thereto. Any person skilled in the art who, within the technical scope disclosed by the present invention, makes equivalent substitutions or modifications based on the technical solutions and improved concepts of the present invention shall be covered by the scope of protection of the present invention.

Claims

1. A data analysis and management system, characterized in that: include: A data acquisition module (1), wherein the data acquisition module (1) is used to collect historical activity data, industry data and environmental data, and the data acquisition module (1) is composed of a historical activity database (11), a market data acquisition module (12) and an environmental data acquisition module (13); A data processing module (2), the data processing module (2) is used to clean and standardize the data collected by the data processing module (2); An activity prediction model (3), wherein the activity prediction model (3) is used to predict activities based on historical activity data, industry data, and environmental data, and the prediction scope includes activity effect prediction, activity risk prediction, and activity participant number prediction; A collaborative management platform (4), wherein the collaborative management platform (4) coordinates activity resources, manages time and manages processes according to the prediction results of the activity prediction model (3); The collaborative management platform (4) includes an authority matrix management model (41), a task allocation module (42) and a data conflict detection module (43). The authority matrix management model (41) allocates an activity role to each manager, and each role corresponds to the authority of the role; the task allocation module (42) allocates tasks to each role based on the prediction results of the activity prediction model (3) and historical activity data; the data conflict detection module (43) detects the modification content, application content and task completion of each manager to determine whether there is a conflict between the tasks of each role.

2. A data analysis and management system according to claim 1, characterized in that: The historical activity database (11) is used to store basic information, participation data and effect indicators of previous activities; the market data collection module (12) is used to collect industry trends, competitor activity data and audience portraits of the industry corresponding to the activity; The environmental data acquisition module (13) is used to obtain the weather at the event venue, surrounding traffic status data and the event time.

3. The data analysis and management system according to claim 1, wherein: The activity prediction model (3) includes a participation prediction module (31), a financial prediction module (32), an effect prediction module (33) and a risk prediction module (34). The participation prediction module (31) is used to estimate the range of the number of participants in the activity based on the activity promotion method; the financial prediction module (32) is used to predict the activity cost and income, wherein the activity cost includes the venue cost, staffing cost and material demand cost, and the activity income includes ticketing income, sponsorship income and derivative income; the effect prediction module (33) is used to predict the activity influence and activity satisfaction; and the risk prediction module (34) is used to predict resource conflicts, external risks and activity expectations not being met.

4. A data analysis and management system according to claim 3, characterized in that: The financial forecast module (32) forecasts ticket revenue based on the forecast results of the participation forecast module (31), forecasts sponsorship revenue based on the forecast results of the effect forecast module (33), and forecasts derivative revenue based on the sales environment around the venue.

5. The data analysis and management system according to claim 1, characterized in that: The data conflict detection module (43) provides a solution according to a resource conflict resolution formula, the specific formula is as follows: When a new task tn is added, calculate Among them, A j (τ) is the available quantity at time t, qj is the total available quantity, d n is the duration of the new task tn, mj is the resource, R n The required resource type.

6. The data analysis and management system according to claim 1, characterized in that: The prediction input of the activity prediction model (3) is a real-time input, which changes with the data collected by the data collection module (1).

7. A management method for a data analysis management system, characterized in that: The management method includes the following steps: Step 1: The data collection module (1) is composed of a historical activity database (11), a market data collection module (12) and an environmental data collection module (13) to collect data from previous activities, industry data and environmental data, and then the collected data is cleaned and standardized by the data processing module (2); Step 2: The activity prediction model (3) receives the data processed by the data processing module (2), uses the data as real-time input data, and completes multi-faceted prediction via the participation prediction module (31), the financial prediction module (32), the effect prediction module (33), and the risk prediction module (34) to obtain the activity prediction results; Step 3: The collaborative management platform (4) assigns activity tasks to various roles through the task assignment module (42) based on the prediction results of the activity prediction model (3). The authority matrix management model (41) distributes the management authority and tasks of each role to the management personnel. During the implementation of the activity arrangement, the data conflict detection module (43) calculates and determines the conflicts of tasks in real time to promote the progress of the activity arrangement implementation.

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