CN113935650A - Enterprise management method and system based on big data - Google Patents
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Abstract
The application provides an enterprise management method and system based on big data, wherein the method comprises the following steps: the terminal equipment collects local operation data, classifies and counts the operation data, and sends the statistical data to the transfer equipment; the transfer equipment receives a plurality of statistical data sent by a plurality of terminal equipment, performs statistical analysis on the data of the same category of the statistical data to obtain analysis data, and sends the analysis data to the enterprise data center; and the enterprise data center performs statistical analysis on all the analysis data to obtain summarized data, and the summarized data is displayed to enterprise management users. The technical scheme that this application provided has the efficient advantage of enterprise management.
Description
Technical Field
The invention relates to the technical field of big data, in particular to an enterprise management method and system based on big data.
Background
Big data is information assets which need a new processing mode and have stronger decision-making power, insight discovery power and flow optimization capability to adapt to mass, high growth rate and diversification.
Big data is very important for enterprise management, but the existing big data is just statistics of data outside an enterprise, and data inside the enterprise is not processed and improved in a relevant manner, so that the enterprise management efficiency is influenced.
Disclosure of Invention
The embodiment of the invention provides an enterprise management method and system based on big data, which can manage the big data of enterprise content to enterprises and improve the efficiency of enterprise management.
In a first aspect, an embodiment of the present invention provides an enterprise management method based on big data, where the method includes the following steps:
the terminal equipment collects local operation data, classifies and counts the operation data, and sends the statistical data to the transfer equipment;
the transfer equipment receives a plurality of statistical data sent by a plurality of terminal equipment, performs statistical analysis on the data of the same category of the statistical data to obtain analysis data, and sends the analysis data to the enterprise data center;
and the enterprise data center performs statistical analysis on all the analysis data to obtain summarized data, and the summarized data is displayed to enterprise management users.
In a second aspect, a big data based enterprise management system is provided, the system comprising: the system comprises terminal equipment, transfer equipment and an enterprise data center; wherein the content of the first and second substances,
the terminal equipment is used for acquiring local operation data, classifying and counting the operation data and then sending the statistical data to the transfer equipment;
the transit equipment is used for receiving a plurality of statistical data sent by a plurality of terminal equipment, performing statistical analysis on data of the same type of the statistical data to obtain analysis data, and sending the analysis data to the enterprise data center;
and the enterprise data center is used for performing statistical analysis on all the analysis data to obtain summarized data, and displaying the summarized data to enterprise management users.
In a third aspect, a computer-readable storage medium is provided, which stores a program for electronic data exchange, wherein the program causes a terminal to execute the method provided in the first aspect.
The embodiment of the invention has the following beneficial effects:
the technical scheme includes that the terminal equipment collects local operation data, classifies and counts the operation data, and sends the statistical data to the transfer equipment; the transfer equipment receives a plurality of statistical data sent by a plurality of terminal equipment, performs statistical analysis on the data of the same category of the statistical data to obtain analysis data, and sends the analysis data to the enterprise data center; and the enterprise data center performs statistical analysis on all the analysis data to obtain summarized data, and the summarized data is displayed to enterprise management users. According to the technical scheme, the enterprise internal data subjected to statistical analysis is obtained in a summarizing mode, and after the data are subjected to transfer processing through the transfer equipment, the marks of the enterprise internal data are deleted, namely the data can not be determined to which person the data belong, so that the privacy of a user is protected, and after the privacy is avoided, the reliability of the enterprise managed data is not influenced, and the enterprise management efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a terminal.
FIG. 2 is a flow diagram of a big data based enterprise management method.
Fig. 3 is a schematic structural diagram of a big data-based enterprise management system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of the invention and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, result, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, fig. 1 provides a terminal device, which may specifically be: the terminal device may be a terminal of an IOS system, an android system, or other systems, for example, a hong meng system, and the application does not limit the specific system, and as shown in fig. 1, the terminal device may specifically include: the device comprises a processor, a memory, a camera and a display screen, wherein the components can be connected through a bus or in other ways, and the application is not limited to the specific way of the connection.
Big data, especially big data inside the enterprise, because it has confidentiality and privacy nature, can't send to big data center and handle, but big data of enterprise, for example, the time of the card punching situation of staff, use each application, chat data, chat time etc. all need to manage it, current big data platform because can't obtain relevant data, consequently need a local big data processing method of enterprise to handle big data, can guarantee user's privacy promptly, can provide relevant reference data for enterprise management again, improve enterprise management's efficiency.
Enterprise management is a general term for a series of activities such as planning, organizing, commanding, coordinating and controlling the production and operation activities of enterprises, and is an objective requirement for social mass production. The enterprise management aims at achieving the purposes of saving, speeding up, increasing and improving resources and achieving the maximum input-output efficiency by using resources such as manpower, material resources, financial resources, information and the like of the enterprise as much as possible.
Referring to fig. 2, fig. 2 provides a big data-based enterprise management method, which is implemented by the terminal device, the relay device and the enterprise data center shown in fig. 1, as shown in fig. 2, wherein the terminal device has a plurality of terminal devices, and the plurality of terminal devices are connected to the enterprise data center through the relay device, the method including the following steps:
step S201, the terminal device collects local operation data, classifies and counts the operation data, and sends the statistical data to the transfer device;
the above operational data includes but is not limited to: card data, running time of an application, number of character inputs, operating time of a terminal device, and the like.
For example, the foregoing manner of classifying and counting the running data may be implemented by a source or a unit of the data, for example, the running time of the application is determined when the data collected by the terminal device is a supported time period, and the input number of characters is determined if the prime number of the terminal device is the number of characters, and the like.
Step S202, a transfer device receives a plurality of statistical data sent by a plurality of terminal devices, performs statistical analysis on the data of the same type of the statistical data to obtain analysis data, and sends the analysis data to an enterprise data center;
for example, the obtaining of the analysis data after performing the statistical analysis on the data of the same category of the plurality of statistical data may specifically include:
and adding the statistical data of the same category to obtain the data average value of the same category, generating a k-line graph according to the average value of all the category data, and adding the k-line graph of the current day to the historical k-line graph to obtain analysis data.
The corresponding analysis data is embodied in a stock k-line graph mode, so that the specific situation of the data can be very intuitively viewed.
For example, the generating the k-line map according to the average value of all the category data specifically includes:
and extracting a first average value of the first class data, and obtaining the average value of the first class data in the previous day, wherein the average value of the previous one is taken as a starting point, and the first average value is taken as an end point to draw a k line of the current day in the class.
For example, the k-line may be represented by red when the average value increases, may be represented by green when the average value decreases, may be similar to domestic stocks, and may be represented by other colors for convenience.
Step S203, the enterprise data center performs statistical analysis on all the analysis data to obtain summarized data, and displays the summarized data to the enterprise management user.
For example, the obtaining of the summarized data by the enterprise data center after performing statistical analysis on all the analysis data may specifically include:
and determining the enterprise department corresponding to the analysis data according to the transfer equipment sent by the analysis data, marking the enterprise department, and summarizing the marked analysis data into a data table of the enterprise department to obtain summarized data.
According to the technical scheme, the terminal equipment collects local operation data, classifies and counts the operation data, and sends the statistical data to the transfer equipment; the transfer equipment receives a plurality of statistical data sent by a plurality of terminal equipment, performs statistical analysis on the data of the same category of the statistical data to obtain analysis data, and sends the analysis data to the enterprise data center; and the enterprise data center performs statistical analysis on all the analysis data to obtain summarized data, and the summarized data is displayed to enterprise management users. According to the technical scheme, the enterprise internal data subjected to statistical analysis is obtained in a summarizing mode, and after the data are subjected to transfer processing through the transfer equipment, the marks of the enterprise internal data are deleted, namely the data can not be determined to which person the data belong, so that the privacy of a user is protected, and after the privacy is avoided, the reliability of the enterprise managed data is not influenced, and the enterprise management efficiency is improved.
For example, the method may further include:
and drawing a plurality of average lines of the k lines by the enterprise data center according to the k lines, and recommending a management suggestion corresponding to the trend according to the trend of the average lines.
For example, if the 10 th day average line of the employee's work hours is an upward trend, then a recommendation to decrease the employee's work hours may be recommended to the manager, if the employee's application runtime is a downward trend, a recommendation to increase the employee's work hours may be recommended to the manager, and so on. The management layer is suggested through the trend graph, namely the large data can be visually observed.
Referring to fig. 3, fig. 3 provides a big data based enterprise management system, the system comprising: the system comprises terminal equipment, transfer equipment and an enterprise data center; wherein the content of the first and second substances,
the terminal equipment is used for acquiring local operation data, classifying and counting the operation data and then sending the statistical data to the transfer equipment;
the transit equipment is used for receiving a plurality of statistical data sent by a plurality of terminal equipment, performing statistical analysis on data of the same type of the statistical data to obtain analysis data, and sending the analysis data to the enterprise data center;
and the enterprise data center is used for performing statistical analysis on all the analysis data to obtain summarized data, and displaying the summarized data to enterprise management users.
By way of example, the operational data may include: the data of punching the card, the running time of an application program, the input number of characters and the operation time of the terminal equipment.
In an example, the transit device is specifically configured to add the statistical data of the same category to obtain a data average value of the same category, generate a k-line graph according to the average value of all the category data, and add the k-line graph of the current day to the historical k-line graph to obtain analysis data.
In an example, the enterprise data center is further configured to draw a plurality of average lines of the k lines according to the k lines, and recommend a management suggestion corresponding to the trend according to the trend of the average lines.
For example, the terminal device, the relay device, and the enterprise data center in the embodiment of the present application may also be used to execute the refinement scheme, the alternative scheme, and the like in the embodiment shown in fig. 2, which is not described herein again.
Embodiments of the present invention also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the big data based enterprise management methods as recited in the above method embodiments.
Embodiments of the present invention also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the big-data based enterprise management methods as recited in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may be performed in other orders or concurrently according to the present invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules illustrated are not necessarily required to practice the invention.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of a receiving hardware or a receiving software program module.
The integrated units, if implemented in the form of software program modules and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above embodiments of the present invention are described in detail, and the principle and the implementation of the present invention are explained by applying specific embodiments, and the above description of the embodiments is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (9)
1. A big data-based enterprise management method is characterized by comprising the following steps:
the terminal equipment collects local operation data, classifies and counts the operation data, and sends the statistical data to the transfer equipment;
the transfer equipment receives a plurality of statistical data sent by a plurality of terminal equipment, performs statistical analysis on the data of the same category of the statistical data to obtain analysis data, and sends the analysis data to the enterprise data center;
and the enterprise data center performs statistical analysis on all the analysis data to obtain summarized data, and the summarized data is displayed to enterprise management users.
2. The method of claim 1, wherein the run-up data comprises: the data of punching the card, the running time of an application program, the input number of characters and the operation time of the terminal equipment.
3. The method of claim 2, wherein the obtaining of the analysis data after performing the statistical analysis on the data of the same category of the plurality of statistical data specifically comprises:
and adding the statistical data of the same category to obtain the data average value of the same category, generating a k-line graph according to the average value of all the category data, and adding the k-line graph of the current day to the historical k-line graph to obtain analysis data.
4. The method of claim 3, further comprising:
and drawing a plurality of average lines of the k lines by the enterprise data center according to the k lines, and recommending a management suggestion corresponding to the trend according to the trend of the average lines.
5. A big-data based enterprise management system, the system comprising: the system comprises terminal equipment, transfer equipment and an enterprise data center; wherein the content of the first and second substances,
the terminal equipment is used for acquiring local operation data, classifying and counting the operation data and then sending the statistical data to the transfer equipment;
the transit equipment is used for receiving a plurality of statistical data sent by a plurality of terminal equipment, performing statistical analysis on data of the same type of the statistical data to obtain analysis data, and sending the analysis data to the enterprise data center;
and the enterprise data center is used for performing statistical analysis on all the analysis data to obtain summarized data, and displaying the summarized data to enterprise management users.
6. The system of claim 5, wherein the run-up data comprises: the data of punching the card, the running time of an application program, the input number of characters and the operation time of the terminal equipment.
7. The system of claim 6,
the transit device is specifically configured to add the statistical data of the same category to obtain a data average value of the same category, generate a k-line graph according to the average value of all the category data, and add the k-line graph of the current day to a historical k-line graph to obtain analysis data.
8. The system of claim 7,
the enterprise data center is further used for drawing a plurality of average lines of the k lines according to the k lines, and recommending management suggestions corresponding to the trends according to the trends of the average lines.
9. A computer-readable storage medium storing a program for electronic data exchange, wherein the program causes a terminal to perform the method as provided in any one of claims 1-4.
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