An enterprise data evaluation and analysis system based on big data

Abstract

The present invention belongs to the technical field of enterprise data analysis, and relates to an enterprise data evaluation and analysis system based on big data, which comprises a data cleaning module, a regional line analysis module, a customer line analysis module, a product line analysis module, a business report feedback module and a cloud database. By performing regional line, customer line and product line analysis on the archived business data sets within a preset historical period of a target enterprise after data cleaning, the business development potential of each business sub-region of the target enterprise and the business value potential of each effective business customer are evaluated, the current life cycle stage of each type of business product is determined, a regional business potential distribution map of the target enterprise, a customer business level arrangement map and a product business development suggestion report are constructed, a comprehensive business analysis report of the target enterprise is generated and feedback is given, and strong data support is provided for the enterprise to formulate long-term development plans and short-term business plans.

Description

Technical Field

[0001] The present invention belongs to the technical field of enterprise data analysis and relates to an enterprise data evaluation and analysis system based on big data. Background Art

[0002] In today's data-driven business environment, enterprise business data, as key information reflecting the company's operating conditions and market performance, is not only the cornerstone for measuring operational efficiency, but also a necessary basis for gaining insight into market trends, optimizing decision-making processes, and formulating development strategies. Therefore, in-depth analysis of enterprise business data is crucial for formulating accurate optimization strategies.

[0003] There are also some solutions related to enterprise business data analysis in the prior art. For example, a system for analyzing and processing enterprise business data with Chinese patent publication number CN116010579A receives communication voice data sent by a voice data recording module and communication step data sent by a communication step recording module, and uses a voice-to-text conversion module to convert the communication voice data into communication text data for business volume analysis, uses a communication type analysis module to perform communication type analysis based on distributed stored business data, and uses a communication keyword analysis module to perform communication keyword analysis on distributed stored business data. Although it helps to overcome the lack of effective analysis of enterprise business data and the inability to efficiently process enterprise business data, it still has the limitations of the prior art, which are specifically manifested as follows: 1. When processing enterprise business data analysis, the prior art ignores the effective data cleaning steps, which directly leads to a large amount of low-quality or low-customer-value data in the analysis process, which not only increases the complexity and time cost of the analysis, but also may introduce misleading information, affecting the accuracy and effectiveness of decision-making, thereby weakening the ability of enterprises to optimize their businesses and adjust their strategies based on data analysis.

[0004] 2. When processing enterprise business data analysis, existing technologies overly focus on client information and ignore in-depth joint analysis of the regional and product ends. On the one hand, the marginalization of regional data analysis may make it impossible for enterprises to accurately identify and seize growth opportunities in emerging markets, and to formulate differentiated market strategies for specific regions. On the other hand, ignoring the importance of product-end data analysis for understanding the health of the company's product portfolio, evaluating the product life cycle stage, and planning subsequent production arrangements makes it difficult for companies to accurately grasp product market performance, unable to adjust product strategies in a timely manner to cope with market changes, and may even face the risk of inventory backlogs or missed sales opportunities due to overproduction or underproduction. Summary of the invention

[0005] In view of this, in order to solve the problems raised in the above background technology, an enterprise data evaluation and analysis system based on big data is proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides an enterprise data evaluation and analysis system based on big data, including: a data cleaning module, a regional line analysis module, a customer line analysis module, a product line analysis module and a business report feedback module.

[0007] The data cleaning module is connected to the regional line analysis module, the customer line analysis module, and the product line analysis module respectively, and the regional line analysis module, the customer line analysis module, and the product line analysis module are all connected to the business report feedback module.

[0008] The data cleaning module is used to collect the business data sets that have been archived within the historical preset period of the target enterprise, and record them as the target data sets after data cleaning.

[0009] The regional line analysis module is used to conduct regional line analysis on the target data set, define the business sub-regions of the target enterprise, and evaluate the corresponding business development potential based on the number of effective business customers and business product sales performance.

[0010] The customer line analysis module is used to conduct customer line analysis on the target data set, and evaluate the business value potential of each effective business customer of the target enterprise based on the comprehensive business contribution coefficient and business stability coefficient.

[0011] The product line analysis module is used to conduct product line analysis on the target data set, and comprehensively analyze the year-on-year sales volume change rate, month-on-month sales volume change rate and market share change rate of the historical preset period to determine the current life cycle stage of various business products of the target enterprise.

[0012] The business report feedback module is used to summarize and generate a comprehensive business analysis report that includes a regional business potential distribution map of the target enterprise, a customer business level layout map, and a product business development suggestion report, and provide feedback.

[0013] Compared with the prior art, the present invention has the following beneficial effects: (1) By combining the basic data quality and basic data value, the present invention realizes data cleaning of the archived business data set within the historical preset period of the target enterprise, effectively improving the efficiency and accuracy of data cleaning, and avoiding the blindness and waste of resources that may exist in traditional methods. At the same time, the consideration of the value attributes of the data makes the cleaned data set closer to the actual needs of the enterprise, and can provide the enterprise with more accurate and insightful business analysis support.

[0014] (2) The present invention evaluates the business development potential of each business sub-region of the target enterprise by conducting a year-on-year analysis of the number of effective business customers, the cumulative sales and cumulative sales volume of various business products in each business sub-region within a historical preset period, so as to assist in obtaining the regional business potential distribution map of the target enterprise, provide a clear and comprehensive business perspective for the enterprise management, and help quickly identify business regions with high potential, so as to formulate targeted market strategies and resource allocation plans.

[0015] (3) The present invention evaluates the business value potential of each effective business customer of the target enterprise by combining the business contribution coefficient and the business stability coefficient to assist in obtaining the target enterprise customer business level layout diagram. It not only shows the relative position and value level of different customers in the enterprise business system, but also provides the enterprise with a clear customer management idea.

[0016] (4) The present invention determines the current life cycle stage of various business products of the target enterprise from three dimensions: the internal sales volume change rate, the month-on-month sales volume change rate and the market share change rate of various business products of the target enterprise in the historical preset cycle, so as to provide corresponding product business development suggestions, which helps the enterprise to better grasp the market dynamics and changes in consumer demand, formulate scientific and reasonable product strategies and business plans, and thus maintain product competitiveness and market leadership. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of module connection of the present invention. DETAILED DESCRIPTION

[0019] 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.

[0020] See also Figure 1 As shown, the present invention provides an enterprise data evaluation and analysis system based on big data, including: a data cleaning module, a regional line analysis module, a customer line analysis module, a product line analysis module and a business report feedback module.

[0021] The data cleaning module is connected to the regional line analysis module, the customer line analysis module, and the product line analysis module respectively, and the regional line analysis module, the customer line analysis module, and the product line analysis module are all connected to the business report feedback module.

[0022] The data cleaning module is used to collect the business data set archived within the historical preset period of the target enterprise, and record it as the target data set after data cleaning.

[0023] Specifically, the specific process of data cleaning includes: retrieving each independently coded business data in the business data set archived within the target enterprise's historical preset period, recording it as each independent business data, extracting the storage content in each data field in each independent business data, wherein each data field includes business transaction time, business contact personnel, name and geographical location of business customers, type of business products, sales volume and sales revenue, combining the storage specification format requirements and storage specification content requirements of each data field of the target enterprise's business data stored in the cloud database, analyzing the basic data quality of each independent business data and eliminating each independent business data whose basic data quality is less than the preset basic data quality specification threshold.

[0024] It should be noted that the analysis process of the basic data quality of the above-mentioned independent business data is: compare the storage content in each data field in the independent business data with the storage specification format requirements and storage specification content requirements in its corresponding data field respectively. If the storage content in a data field does not meet the corresponding storage specification format requirements or does not meet the corresponding storage specification content requirements, then the data quality index of the data field is set to 0, and the data field is used as an abnormal data field. Conversely, if the storage content in a data field meets the corresponding storage specification format requirements and storage specification content requirements, then the data quality index of the data field is set to 1, and the data field is used as a normal data field, so as to screen out the abnormal data fields and normal data fields in each independent business data, and take the proportion of the number of normal data fields as the basic data quality of the independent business data, thereby obtaining the basic data quality of each independent business data.

[0025] Summarize the independent business data retained after elimination according to the business customer name, obtain the business transaction time and business contact personnel of each business customer within the historical preset period, analyze the business wake-up times, business wake-up cycles and business contact personnel changes of each business customer within the historical preset period, and then evaluate the basic data value of each business customer. The relevant independent business data of each business customer shall be eliminated.

[0026] In summary, data cleaning of the target enterprise's archived business data sets within a preset historical period is achieved.

[0027] The embodiments of the present invention achieve data cleaning of the business data sets archived within the historical preset period of the target enterprise by combining the basic data quality and the basic data value, effectively improving the efficiency and accuracy of data cleaning, and avoiding the blindness and waste of resources that may exist in traditional methods. At the same time, the consideration of the value attributes of the data makes the cleaned data set closer to the actual needs of the enterprise, and can provide the enterprise with more accurate and insightful business analysis support.

[0028] Specifically, the evaluation of the basic data value of each business customer includes: taking the business wake-up times within the business customer's historical preset period as 0, the business wake-up period greater than the target enterprise business product preset license wake-up period threshold, and the ratio of the business docking personnel change times to the business wake-up times greater than the target enterprise business docking personnel preset license change ratio threshold as business customer basic data value evaluation judgment conditions 1, 2, and 3 respectively. If a business customer meets any of the basic data value evaluation judgment conditions, the basic data value of the business customer is set to On the contrary, if a business customer does not meet any of the basic data value assessment criteria, the basic data value of the business customer is set to , thereby evaluating the value of basic data of each business customer.

[0029] It should be noted that the above .

[0030] The regional line analysis module is used to carry out regional line analysis on the target data set, define the business sub-regions of the target enterprise and evaluate the corresponding business development potential based on the number of effective business customers and business product sales performance.

[0031] It should be noted that the above-mentioned definition of each business sub-region of the target enterprise is obtained by dividing the designated business coverage area of ​​the target enterprise according to the characteristics of the geographical area segment. Exemplarily, the designated business coverage area of ​​the target enterprise can be divided according to the preset geographical area, so as to define each business sub-region of the target enterprise.

[0032] Specifically, the business development potential of each business sub-region of the target enterprise is evaluated, including: recording the business customers of each independent business data record in the target data set as valid business customers, aggregating the independent business data of the same business sub-region of the target enterprise in the target data set according to the geographical location of the business customers, and obtaining the number of valid business customers in each business sub-region of the target enterprise within a historical preset period. , cumulative sales of various business products and cumulative sales ,in is the number of each business sub-area of ​​the target enterprise, , It is the number of various business products. .

[0033] Collect the number of effective business customers in each business sub-region of the target enterprise in the same historical preset period in each historical year , cumulative sales of various business products and cumulative sales ,in is the number of each historical year, .

[0034] It should be noted that the above , , Specifically, it can be obtained by extracting from the business database of the target enterprise.

[0035] Set the value weights of various business products of the target enterprise for enterprise development , according to the formula Obtain the business development potential evaluation indicators of each business sub-area of ​​the target enterprise, including The number is the historical year.

[0036] It should be noted that the setting of value weights for the various business products of the above-mentioned target enterprises in relation to enterprise development is a process that comprehensively considers multiple factors, including profit value, brand value, alignment with strategic objectives, market potential and competitive situation, as well as synergy and resource integration. For details, please refer to the market positioning of various business products within the target enterprise to refine the corresponding weight values.

[0037] The embodiment of the present invention evaluates the business development potential of each business sub-region of the target enterprise by performing a year-on-year analysis on the number of effective business customers, the cumulative sales volume and the cumulative sales volume of various business products in each business sub-region of the target enterprise within a historical preset period, so as to assist in obtaining the regional business potential distribution map of the target enterprise, provide a clear and comprehensive business perspective for the enterprise management, and help quickly identify business regions with high potential, so as to formulate targeted market strategies and resource allocation plans.

[0038] The customer line analysis module is used to conduct customer line analysis on the target data set, and evaluate the business value potential of each effective business customer of the target enterprise by comprehensively considering the business contribution coefficient and the business stability coefficient.

[0039] Specifically, the business value potential of each effective business customer of the target enterprise is evaluated, including: summarizing the cumulative sales contribution of each effective business customer in the target data set to various business products within the historical preset period; and cumulative sales contribution , is the number of each valid business customer, , analyze the business contribution coefficient of each effective business customer of the target enterprise , .

[0040] Summarize the interval period of each business transaction of each valid business customer in the target data set within the preset historical period , It is the number of each business transaction within the historical preset period. , analyze the business stability coefficient of each effective business customer of the target enterprise , , The number of business transactions within a preset historical period.

[0041] The business contribution coefficient and the business stability coefficient are added up to obtain the business value potential assessment index of each effective business customer of the target enterprise.

[0042] The embodiment of the present invention combines the business contribution coefficient and the business stability coefficient to evaluate the business value potential of each effective business customer of the target enterprise to assist in obtaining the target enterprise customer business level layout diagram, which not only shows the relative position and value level of different customers in the enterprise business system, but also provides the enterprise with a clear customer management idea.

[0043] The product line analysis module is used to conduct product line analysis on the target data set, and determine the current life cycle stage of various business products of the target enterprise by comprehensively considering the year-on-year sales volume change rate, month-on-month sales volume change rate and market share change rate of the historical preset period.

[0044] Specifically, the determination of the current life cycle stage of each business product of the target enterprise includes: summarizing the sales volume of each day of the historical preset period of each business product in the target data set, substituting it into a rectangular coordinate system with time as the horizontal axis and product sales volume as the vertical axis, and obtaining the sales volume change curve corresponding to the historical preset period of each business product and its best fitting function , substitute the data at each time point in the historical preset period into the best fitting function after first-order derivation and calculate the mean, thereby obtaining the internal sales volume change rate of each business product in the historical preset period .

[0045] Trace back the sales volume of each business product of the target enterprise on each day within the same time span of the preset number of historical preset periods, record it as the sales volume of each business product on each day of each historical reference period, substitute it into the same rectangular coordinate system and obtain the sales volume change curve and its best fitting function corresponding to each historical reference period of each business product ,in is the number of each historical reference period, , analyze the month-on-month sales change rate of various business products in the historical preset cycle .

[0046] It should be noted that the sales volume of each type of business product of the target enterprise on each day within the same time span of the preset number of historical preset periods traced back is also obtained by extracting from the business database of the target enterprise.

[0047] Summarize the cumulative sales of various business products in the target data set during the historical preset period, collect the total market sales of various business products during the historical preset period, and obtain the market share of various business products of the target enterprise during the historical preset period through ratio analysis Similarly, we can trace the market share of each business product of the target enterprise in each historical reference period. , analyze the market share change rate of various business products of the target enterprise in the historical preset period .

[0048] It should be noted that the total market sales of the above-mentioned business products in the historical preset period are extracted from the relevant industry reports of the target enterprises published on professional websites.

[0049] It should also be noted that the above The specific analysis and calculation formula is: .

[0050] Will , , The comprehensive sales change rate of each type of business product of the target enterprise in the historical preset period is accumulated by multiplying them with the corresponding preset weights respectively, and then compared with the comprehensive sales change rate intervals corresponding to each life cycle stage of the business products stored in the cloud database, so as to determine the current life cycle stage of each type of business product of the target enterprise.

[0051] Specifically, the calculation formula for the month-on-month sales volume change rate of each type of business product in the historical preset period is: ,in is the number of historical reference periods, are the start date and end date of the historical preset period, Respectively The start and end dates of the historical reference period.

[0052] The embodiment of the present invention determines the current life cycle stage of various business products of the target enterprise from three dimensions: the internal sales volume change rate, the month-on-month sales volume change rate and the market share change rate of various business products of the target enterprise in the historical preset cycle, so as to provide corresponding business development suggestions for related products, which helps the enterprise to better grasp the market dynamics and changes in consumer demand, formulate scientific and reasonable product strategies and business plans, so as to maintain product competitiveness and market leadership.

[0053] The business report feedback module is used to summarize and generate a comprehensive business analysis report including a regional business potential distribution map of the target enterprise, a customer business level arrangement map and a product business development suggestion report and provide feedback.

[0054] Specifically, the process of obtaining the target enterprise regional business potential distribution map includes: selecting a geographical map corresponding to the target enterprise's designated business coverage area as a base map, and carefully outlining the edge contours of each business sub-area therein.

[0055] According to the filling color scheme corresponding to the numerical range of each business development potential evaluation indicator stored in the cloud database, the specific filling color corresponding to the business development potential evaluation indicator of each business sub-area of ​​the target enterprise is determined.

[0056] Then, color filling operation is performed on the base map according to the filling colors corresponding to each business sub-area, so as to draw a business potential distribution map of the target enterprise area.

[0057] Specifically, the process of obtaining the customer business level arrangement diagram of the target enterprise includes: obtaining the business level corresponding to each effective business customer of the target enterprise according to the customer business level corresponding to the numerical range of each business value potential evaluation indicator stored in the cloud database, merging each effective business customer of the target enterprise at the same business level into the same sequence, so as to obtain the effective business customer sequence corresponding to each business level, and superimposing the effective business customer sequences corresponding to each business level one by one in order from low to high business level to draw the customer business level arrangement diagram of the target enterprise.

[0058] Specifically, the process of obtaining the product business development suggestion report of the target enterprise includes: each life cycle stage of the business product includes the introduction stage, growth stage, maturity stage and decline stage, creating a table, requiring it to list the business product types horizontally and the life cycle stages vertically, and filling in the corresponding development suggestions in the table column of the current life cycle stage of each type of business product of the target enterprise according to the corresponding development suggestions stored in the cloud database, thereby constructing the product business development suggestion report of the target enterprise.

[0059] It should be noted that if the above-mentioned business products are in the introduction stage, the corresponding development suggestions are: market promotion and product marketing.

[0060] If the business product is in the growth stage, the corresponding development suggestions are: market expansion and product innovation.

[0061] If the business product is in the mature stage, the corresponding development suggestions are: market segmentation and product upgrade.

[0062] If the business product is in a recession, the corresponding development suggestions are: market contraction, clearing inventory.

[0063] For example, if the target enterprise's business products A, B, C, and D are currently in the introduction stage, growth stage, maturity stage, and decline stage of their life cycle, respectively, the corresponding target enterprise product business development recommendation report may be shown in the following table.

[0064] Table 1 Target enterprise product business development suggestion report

[0065]

[0066] It should be noted that the cloud database storage of the present invention includes storage specification format requirements and storage specification content requirements for each data field of the target enterprise's business data, the filling color scheme corresponding to the numerical range of each business development potential evaluation indicator, the customer business level corresponding to the numerical range of each business value potential evaluation indicator, the comprehensive sales volume change rate range corresponding to each life cycle stage of the business product, and development suggestion content.

[0067] The data sources in the cloud database of this embodiment are shown in Table 2 below.

[0068] Table 2 Detailed description of data sources in cloud database

[0069]

[0070] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An enterprise data evaluation and analysis system based on big data, characterized in that: The system includes: The data cleaning module is used to collect the business data sets that have been archived within the historical preset period of the target enterprise and record them as the target data sets after data cleaning; The regional line analysis module is used to conduct regional line analysis on the target data set, define the business sub-regions of the target enterprise, and evaluate the corresponding business development potential based on the number of effective business customers and business product sales performance; The customer line analysis module is used to conduct customer line analysis on the target data set, and evaluate the business value potential of each effective business customer of the target enterprise by comprehensively considering the business contribution coefficient and business stability coefficient; The product line analysis module is used to conduct product line analysis on the target data set, and determine the current life cycle stage of various business products of the target enterprise by combining the year-on-year sales volume change rate, month-on-month sales volume change rate and market share change rate of the historical preset period; Business report feedback module, used to summarize and generate a comprehensive business analysis report including the target enterprise's regional business potential distribution map, customer business level layout map and product business development suggestion report and provide feedback; The evaluation of the business development potential of each business sub-region of the target enterprise includes: recording the business customers of each independent business data record in the target data set as valid business customers, aggregating the independent business data of the same business sub-region of the target enterprise in the target data set according to the geographical location of the business customers, and obtaining the number of valid business customers in each business sub-region of the target enterprise within a historical preset period. , cumulative sales of various business products and cumulative sales ,in is the number of each business sub-area of ​​the target enterprise, , It is the number of various business products. ; Collect the number of effective business customers in each business sub-region of the target enterprise in the same historical preset period in each historical year , cumulative sales of various business products and cumulative sales ,in is the number of each historical year, ; Set the value weights of various business products of the target enterprise for enterprise development , according to the formula Obtain the business development potential evaluation indicators of each business sub-area of ​​the target enterprise, including is the number of historical years; The process of obtaining the regional business potential distribution map of the target enterprise includes: selecting a geographical map corresponding to the business coverage area designated by the target enterprise as a base map, and carefully outlining the edge contours of each business sub-area therein; Determine the specific filling colors corresponding to the business development potential assessment indicators of each business sub-area of ​​the target enterprise according to the filling color schemes corresponding to the numerical ranges of each business development potential assessment indicator stored in the cloud database; Then, color filling operation is performed on the base map according to the filling colors corresponding to each business sub-area, so as to draw a business potential distribution map of the target enterprise area.

2. According to the enterprise data evaluation and analysis system based on big data as described in claim 1, it is characterized by: The specific process of data cleaning includes: retrieving each independently coded business data in the business data set archived within the historical preset period of the target enterprise, recording as each independent business data, extracting the storage content in each data field in each independent business data, wherein each data field includes business transaction time, business contact personnel, name and geographical location of business customers, type of business products, sales volume and sales amount, combining the storage specification format requirements and storage specification content requirements of each data field of the target enterprise business data stored in the cloud database, analyzing the basic data quality of each independent business data and eliminating each independent business data whose basic data quality is less than the preset basic data quality specification threshold; Summarize the independent business data retained after the elimination according to the business customer name, obtain the business transaction time and business contact personnel of each business customer within the historical preset period, analyze the business wake-up times, business wake-up cycles and business contact personnel changes of each business customer within the historical preset period, and then evaluate the basic data value of each business customer, and eliminate the relevant independent business data of each business customer whose basic data value is less than the preset basic data value standard threshold; In summary, data cleaning of the target enterprise's archived business data sets within a preset historical period is achieved.

3. The enterprise data evaluation and analysis system based on big data according to claim 2 is characterized by: The evaluation of the basic data value of each business customer includes: taking the business wake-up times within the business customer's historical preset period as 0, the business wake-up period greater than the target enterprise business product preset permission wake-up period threshold, and the ratio of the business docking personnel change times to the business wake-up times greater than the target enterprise business docking personnel preset permission change ratio threshold as business customer basic data value evaluation judgment conditions 1, 2, and 3 respectively. If a business customer meets any of the basic data value evaluation judgment conditions, the basic data value of the business customer is set to On the contrary, if a business customer does not meet any of the basic data value assessment criteria, the basic data value of the business customer is set to , thereby evaluating the value of basic data of each business customer.

4. The enterprise data evaluation and analysis system based on big data according to claim 1, characterized in that: The evaluation of the business value potential of each effective business customer of the target enterprise includes: summarizing the cumulative contribution sales and cumulative contribution sales volume of each effective business customer in the target data set for various business products in the historical preset period, and analyzing the business contribution coefficient of each effective business customer of the target enterprise; Summarize the intervals between business transactions of each valid business customer in the target data set within the historical preset period, and analyze the business stability coefficient of each valid business customer of the target enterprise; The business contribution coefficient and the business stability coefficient are added up to obtain the business value potential assessment index of each effective business customer of the target enterprise.

5. The enterprise data evaluation and analysis system based on big data according to claim 1 is characterized by: Determining the current life cycle stage of various business products of the target enterprise includes: summarizing the sales volume of various business products on each day in the historical preset period in the target data set, substituting it into a rectangular coordinate system with time as the horizontal axis and product sales volume as the vertical axis, and obtaining the sales volume change curve corresponding to the historical preset period of various business products and its best fitting function , substitute the data at each time point in the historical preset period into the best fitting function after first-order derivation and calculate the mean, thereby obtaining the internal sales volume change rate of each business product in the historical preset period ; Trace back the sales volume of each business product of the target enterprise on each day within the same time span of the preset number of historical preset periods, mark it as the sales volume of each business product on each day of each historical reference period, substitute it into the same rectangular coordinate system and obtain the sales volume change curve and its best fitting function corresponding to each historical reference period of each business product ,in is the number of each historical reference period, , analyze the month-on-month sales change rate of various business products in the historical preset cycle ; Summarize the cumulative sales of various business products in the target data set during the historical preset period, collect the total market sales of various business products during the historical preset period, obtain the market share of various business products of the target enterprise during the historical preset period through ratio analysis, and similarly trace the market share of various business products of the target enterprise in each historical reference period, and analyze the market share change rate of various business products of the target enterprise during the historical preset period ; Will , , The comprehensive sales change rate of each type of business product of the target enterprise in the historical preset period is accumulated by multiplying them with the corresponding preset weights respectively, and then compared with the comprehensive sales change rate intervals corresponding to each life cycle stage of the business products stored in the cloud database, so as to determine the current life cycle stage of each type of business product of the target enterprise.

6. The enterprise data evaluation and analysis system based on big data according to claim 5 is characterized by: The calculation formula for the month-on-month sales volume change rate of each type of business product in the historical preset period is: ,in is the number of historical reference periods, are the start date and end date of the historical preset period, Respectively The start and end dates of the historical reference period.

7. The enterprise data evaluation and analysis system based on big data according to claim 4 is characterized by: The process of obtaining the target enterprise's customer business level arrangement diagram includes: obtaining the business level corresponding to each effective business customer of the target enterprise according to the customer business level corresponding to the numerical range of each business value potential evaluation indicator stored in the cloud database, merging each effective business customer of the target enterprise at the same business level into the same sequence, thereby obtaining the effective business customer sequence corresponding to each business level, and superimposing the effective business customer sequences corresponding to each business level one by one in order from low to high business levels to draw the target enterprise's customer business level arrangement diagram.

8. The enterprise data evaluation and analysis system based on big data according to claim 5 is characterized by: The process of obtaining the product business development suggestion report of the target enterprise includes: each life cycle stage of the business product includes the introduction stage, the growth stage, the maturity stage and the decline stage, creating a table, requiring it to list the business product types horizontally and the life cycle stages vertically, and filling in the corresponding development suggestions in the table column of the current life cycle stage of each type of business product of the target enterprise according to the corresponding development suggestions of each life cycle stage stored in the cloud database, thereby constructing the product business development suggestion report of the target enterprise.

Images