KR101996382B1 - System for Data Analysis of University Information Based on Platform Using The BigData - Google Patents

Abstract

The present invention provides a university information analysis system based on a platform using big data, to remarkably reduce expenses for managing industry-university cooperation and constructing an infrastructure system. According to the present invention, the university information analysis system comprises: a collected data normalization module (110) automatically generating a data collection format, managing authentication and integrated information about existing data, and generating an output API outputted to a manager; a data collection setting module (120) setting a classification code for the collected data in accordance with a core index; a data registration module (130); and a statistical information management module (140) generating pivot data and a chart type statistical index, which are used for a visualized report, in accordance with a user′s request.

Description

[0001] The present invention relates to a platform-based university information data analysis system using Big Data,

The present invention relates to a platform-based university information data analysis system using Big Data, and more particularly, to a platform-based university information data analysis system using platform-based data analysis, Integration of various college information and performance data through the core API that registers and deletes, modifies, searches, and sets various authentication processes for the performance measurement of the task. In addition, it enables collections management without building a separate system, and it enables organic interlocking with existing established systems, thereby overcoming the problems of analyzing the performance of the university by constructing a new system, Establish standardization of business processes for data collection and analysis It relates to a platform-based university information systems data analysis using Big Data to help.

Many universities and universities establish a student information system based on the student information that was input at the time of admission by university, department or department, and establish a bachelor's information system for the class or schedule of the school based on this information. In order to carry out the research, practice, and assignment of the professors and students in the school, a separate information system is established for the school.

Various legacy systems necessary for the administration within the school are distributed and arranged. However, the conventional legacy system generates and stores data according to the requirement at the time of construction, so that the same data but different data types There are other types of un-normalized data formats such as an operating system for operating the system, a database for storing data, and the like.

In addition, there is no need to develop a migration program for interworking with data distributed in existing legacy systems or a separate program for this, and there is no data code to be matched for each data, resulting in missing data due to code mismatch.

In addition, it is often the case that the basic data for analyzing the performance occurs frequently, and the data is often repeatedly generated according to the policy for collecting and analyzing the data. In addition, according to the upgrade of the system, There is a problem that it is difficult to secure the integrity of the data according to the management method based on the human factor.

Therefore, many studies are being conducted to collect unstructured data so that data can be unified through a standardized form of data, process the data into standardized data, and utilize it for publishing and distribution.

Conventional Open Patent No. 10-2018-0014259 provides an education mediation service providing system, a training mediation service providing server, and a providing method, which provide a platform serving as an intermediary between an education demander and an education provider through a location based call system, The history of education application information received from the consumer is analyzed by various methods such as a big data method, and education recommendation information is provided.

However, in the conventional technology, there is no process of standardizing or normalizing the data of the big data method in order to provide the education mediating service, so there is a problem that the data included in the various existing legacy systems can not be utilized. There is a limit to the maintenance due to such a problem.

A conventional data interworking method using heterogeneous systems using service patterning includes a data processing apparatus for interworking data between a source system and a target system using service patterning, A step of defining a plurality of upper patterns and a plurality of lower patterns belonging to each upper pattern, wherein the upper pattern is a data extraction pattern, a data conversion pattern, and a data loading pattern Lt; / RTI > Defining a function for a subpattern as a method concept; Extracting data from a source system by executing a data extraction pattern and a subpattern attributed thereto; Executing a data conversion pattern and a subpattern assigned thereto, and converting the extracted data to be interlocked with a target system; And loading the converted data into the target system by executing the data loading pattern and the sub pattern assigned thereto.

However, the conventional technology does not use a platform-based open API for interworking data between heterogeneous systems in a data processing apparatus that interlocks data between a source system and a target system, There is also a limitation in interworking with other systems.

Korean Public Registration Publication No. 10-2018-0014259 entitled " Educational Mediation Service Providing System, Educational Mediation Service Providing Server and Providing Method " Korean Public Registration Bulletin No. 10-2018-0010704 " Method of interworking data between heterogeneous systems using service patterning "

The present invention has been made in view of the above problems, and it is an object of the present invention to provide a method and apparatus for analyzing various existing data stored in a legacy system established in a conventional institution, such as a university or an educational institution, To perform the report tool operation, core APIs that can convert the data to conform to the classification code are automatically generated, converted, and registered to the standardized, normalized, and scalable data collected from the denormalized data In this paper, we propose a method for generating a key performance indicator of a university specialization project by setting up various authentication processors and generating statistical indices to which an administrator or a user requires pivot tables or charts using the normalized data generated through the set process, Evaluation of items by data collection and analysis And to provide a platform-based university information data analysis system using new big data that can build standardization of business processes that can be provided.

However, the objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention, a data collection format is automatically generated according to a collection policy for unregistered data stored separately for each institution of a university, A collection data normalization module 110 for managing the integrated information and generating an output API for outputting to an administrator, and a controller for setting a format of data with respect to the data collected through the collection data normalization module 110, A data collection setting module 120 for managing the data codes and setting the classification codes according to the core indexes of the collected data, and a collection field for generating the normalized data through the data collection setting module 120 A data registration module 130 for automatically generating and registering APIs according to subject areas and registering them; And a data set for generating a data mart from the data registered through the data registration module 130 to generate a data mart for each subject area, and generates pivot data and chart type statistics And a statistical information management module (140) for generating an index. The platform-based university information data analysis system using big data is provided.

The collection data normalization module 110 of the platform-based university information data analysis system using the big data according to the present invention includes a collection policy setting unit 111 that receives settings for the collection policy from the manager, A classification code assignment unit 112 for assigning a classification code for unqualified data according to the collection policy setting unit 111 and an authentication integration management unit 113 for managing authentication and integration information on the non- ); And a data output unit (114) for outputting data and a data format to the manager on the existing data.

The data collection setting module 120 of the platform-based university information data analysis system using the big data according to the present invention includes a data format setting unit 121 for setting the format of the standardized data on the unqualified data collected from the manager, A core index setting unit 122 for setting a core index necessary for classification of unqualified data collected from an administrator; And a classification code setting unit (123) for setting a classification code from an administrator according to a core index according to the core index setting unit (122).

The data registration module 130 of the platform-based university information data analysis system using the big data according to the present invention analyzes the data denormalized according to the data collection setting module 120, And a key index unit for generating and classifying data by adding a key index according to the key index setting unit 123 with respect to the data normalized by the data normalization unit 131, A data classification unit 133 for generating data having a classification code added to the normalized data classified according to the key index addition unit 132; And a data registration unit (134) for storing the data for each classification code in the database with respect to the normalized data to which the classification code and the key index classified by the data classification unit (133) are added. do.

The statistical information management module 140 of the platform-based university information data analysis system using the big data according to the present invention includes a data set setting unit 141 for setting a data set necessary for generating a data mart from an administrator, A data mart generating unit 142 for generating a data mart according to the setting of the set setting unit 141, a user request inputting unit 143 for inputting the types of data and statistical indices matching the user's request from the user, A data extraction unit 144 for extracting necessary data according to a user's request inputted from the user request input unit 143 from the data mart generated by the data mart generation unit 142, A statistical indicator generator 145 for generating an statistical indicator according to the statistical indicator received from the user request input unit 143 using the data extracted from the statistical indicator; And a report construction unit (146) for constructing a performance analysis visualization report based on the statistical indices generated by the statistical indicator generation unit (145).

The statistical information management module 140 of the platform-based university information data analysis system using the big data according to the present invention calculates the reference value, the target value, the achievement value, and the achievement rate for each item of the core performance management index And a performance management evaluation unit (147) that allows the user or an administrator to display the results of the evaluation.

The platform-based university information data analysis system using Big Data according to an embodiment of the present invention converts unqualified data distributed in a legacy system into platform-based legacy systems into normalized data, Through the core API, it is possible to collect key index result data for analyzing various data and performance, linking with performance analysis and reporting tool based on the collected data, users can easily create various reports according to key indicators Analysis, and application of various college business models through the platform to enable organic interworking with existing legacy systems, and to integrate essential data not defined in existing systems into legacy systems in platform services. By directly creating and collecting at the interlocking stage In order to reduce the cost of system upgrading and new system construction required, it is possible to solve the problems of unnecessary duplication of system by making it easy to organically link with existing legacy system and interworking with database system In addition, it is possible to provide a one-stop industry-university cooperation service as well as drastically reduce the cost of establishing an industry-university cooperation operation and infrastructure system through linkage and integration with various industry-university cooperation service models.

1 is a block diagram of a platform-based university information data analysis system using Big Data according to an embodiment of the present invention;
FIG. 2 illustrates an example of a platform-based university information data analysis system using Big Data according to an embodiment of the present invention; FIG.
3 is a schematic diagram of a core API management platform of a platform-based university information data analysis system using Big Data according to an embodiment of the present invention;
4 is a block diagram of a collection data normalization module of a platform-based university information data analysis system using big data according to an embodiment of the present invention;
FIG. 5 is a block diagram of a data collection setting module of a platform-based university information data analysis system using big data according to an embodiment of the present invention; FIG.
FIG. 6 is a block diagram of a data registration module of a platform-based university information data analysis system using big data according to an embodiment of the present invention; FIG.
FIG. 7 is a block diagram of a statistical information management module of a platform-based university information data analysis system using big data according to an embodiment of the present invention; FIG.
8 is an exemplary diagram illustrating a statistical information management module of a platform-based university information data analysis system using Big Data according to an embodiment of the present invention;
FIG. 9 is a block diagram of a statistical information management module of a platform-based university information data analysis system using Big Data according to another embodiment of the present invention; FIG.
10 is an exemplary diagram illustrating a statistical information management module of a platform-based university information data analysis system using big data according to another embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In order to fully understand the present invention, a preferred embodiment of the present invention will be described in detail with reference to FIGS. 1 to 10. The embodiments of the present invention may be modified into various forms, and the scope of the present invention should not be construed as being limited to the embodiments described in detail below. The present embodiments are provided to enable those skilled in the art to more fully understand the present invention. Therefore, the shapes and the like of the elements in the drawings can be exaggeratedly expressed to emphasize a clearer description. It should be noted that in the drawings, the same members are denoted by the same reference numerals. In the drawings and the detailed description, the construction and operation of the magnetic electronic chuck, the electronic chuck control device, the control device, the database, and the like can be easily understood by those skilled in the art. Particularly, in the drawings and the detailed description of the drawings, detailed description and illustration of elements and structures of elements that are not directly related to the technical features of the present invention are omitted and only a technical structure related to the present invention is shown briefly . DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the following description of the present invention, detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

FIG. 1 is a block diagram of a platform-based university information data analysis system using big data according to an embodiment of the present invention, FIG. 2 is a diagram illustrating an example of a platform-based university information data analysis system using big data according to an embodiment of the present invention to be.

1 and 2, the data analysis system 100 includes a collection data normalization module 110, a data collection configuration module 120, a data registration module 130, and a statistical information management module 140 . The data analysis system 100 is a platform-based system capable of extracting and storing data separated and stored by each department or department in a conventional university, converting the data into a standardized format, and automatically storing and registering the converted data Data conversion and collection, and analysis.

The data analysis system 100 is capable of collecting key index result data for various data and performance analysis through a core API defined by the user, thereby linking with performance analysis and reporting tools based on the collected data It enables users to easily create various reports for each key indicator or perform analysis tasks.

3 is a schematic diagram of a core API management platform of a platform-based university information data analysis system using Big Data according to an embodiment of the present invention.

The core API management platform is the core of the data analysis system 100. The core API management platform automatically generates the data and the collection form to be collected by the user in the system, By registering and using the linking method and the DB linking rule, a standardized interface can be provided regardless of any system.

The data analysis system 100 normalizes the irregular data by mapping it to the same code through the core API platform and converts it into standardized data defined by the user even if the data format of the associated DB system is changed within the core API platform It is possible to maintain the consistency of the data by being stored.

4 is a block diagram of a collection data normalization module of a platform-based university information data analysis system using Big Data according to an embodiment of the present invention.

4, the collection data normalization module 110 includes a collection policy setting unit 111, a classification code assignment unit 112, an authentication integration management unit 113, and a data output unit 114 . The collected data normalization module 110 automatically generates a data collection format according to the collection policy for the unregulated data stored separately for each institution of the university. The collection data normalization module 110 manages authentication and integration information for existing data and generates an output API to output to the administrator.

The collection policy setting unit 111 receives settings for the collection policy from the manager for the conventional non-normalized data.

The classification code assigning unit 112 assigns a classification code for denormalized data according to the collection policy setting unit 111. [

The authentication integration management unit 113 manages the authentication and integration information with respect to the non-normalized data.

The data output unit 114 outputs the data and the data format to the manager about the existing data.

5 is a configuration diagram of a data collection setting module of a platform-based university information data analysis system using big data according to an embodiment of the present invention.

5, the data collection setting module 120 includes a data format setting unit 121, a key index setting unit 122, and a classification code setting unit 123. The data collection setting module 120 sets the data format for the data collected through the collection data normalization module 110. The data collection setting module 120 sets the key index, manages the code of the data, and sets the classification code according to the core index of the collected data.

The data format specification unit 121 sets the format of the standardized data on the non-normalized data collected from the manager.

The core index setting unit 122 sets a core index necessary for classification of the non-normalized data collected from the manager.

The classification code setting unit 123 receives the classification code from the manager according to the core index according to the core index setting unit 122. [

6 is a configuration diagram of a data registration module of a platform-based university information data analysis system using big data according to an embodiment of the present invention.

6, the data registration module 130 includes a data normalization unit 131, a core index addition unit 132, a data classification unit 133, and a data registration unit 134. As shown in FIG. The data registration module 130 automatically generates an API through a collection field for generating normalized data through the data collection setting module 120, and stores and registers the API for each subject area.

The data normalization unit 131 receives data according to the data format setting unit 121 and normalizes the data denormalized according to the data collection setting module 120.

 The key index adding unit 132 adds the key index to the data normalized by the data normalization unit 131 according to the key index setting unit 123, and generates and classifies the data.

The data classification unit 133 generates data to which the classification code is added for the normalized data classified according to the data classification unit 132. [

The data registration unit 134 stores data for each classification code in the database and registers the normalized data to which the classification index and the key index classified by the data classification unit 133 are added.

7 is a block diagram of a statistical information management module of a platform-based university information data analysis system using big data according to an embodiment of the present invention.

7, the statistical information management module 140 includes a data set setting unit 141, a data mat creating unit 142, a user request inputting unit 143, a data extracting unit 144, (145) and a report construction unit (146). The statistical information management module 140 sets a data set necessary for generating a data mart from the data registered through the data registration module 130. [ The statistical information management module 140 generates a data mart for each subject area.

8 is a diagram illustrating an example of a statistical information management module of a platform-based university information data analysis system using big data according to an embodiment of the present invention.

As shown in FIG. 8, the statistical information management module 140 generates pivot data and a statistical index in the form of a chart to be used in a visualization report according to a user's request. In the case of performance statistics for each program, the results generated by the program are generated through data marts classified by program, and business performance by department (department) is created by creating a data mart on the performance of the tasks performed by the department or department Indicate key business performance.

In addition, the results of the professors' professors can generate data marts for each professor, so that the performance of the professed or ongoing projects can be inquired.

The data set setting unit 141 sets a data set necessary for generating a data mart from the manager.

The data mart generating unit 142 generates a data mart according to the setting of the data set setting unit 141. [

The user request input section 143 receives the types of data and statistical indices corresponding to the user's request from the user.

The data extracting unit 144 extracts necessary data from the data mart generated by the data mart generating unit 142 according to the user's request inputted from the user request inputting unit 143. [

The statistical index generating unit 145 generates an statistical index according to the statistical indices received from the user request input unit 143 using the data extracted by the data extracting unit 144.

The report construction unit 146 constructs a performance analysis visualization report based on the statistical indices generated by the statistical indicator generation unit 145.

FIG. 9 is a block diagram of a statistical information management module of a platform-based university information data analysis system using Big Data according to another embodiment of the present invention. FIG. An example of a statistical information management module of a university information data analysis system.

As shown in FIG. 9 and FIG. 10, the statistical information management module 140 further includes a performance management evaluation unit 147.

The performance management evaluation unit 147 can display the reference value, the target value, the achievement value, and the achievement rate to the user or the manager for each item of the key performance management index for the performance management of the business. The performance management evaluation unit 147 presents the reference value and Mokpo value for each item in the designated core performance management index for the performance management of the business performed by the university and displays the achievement rate obtained by dividing the achievement value of the item by the target value, And can be displayed to the user or manager.

In this specification, a module may mean a functional and structural combination of hardware for carrying out the technical idea of the present invention and software for driving the hardware. For example, the module may mean a logical unit of a predetermined code and a hardware resource for executing the predetermined code, and it does not necessarily mean a physically connected code or a kind of hardware. Can be easily deduced to the average expert in the field of < / RTI >

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device and the like, and also implemented in the form of a carrier wave (for example, transmission over the Internet) .

The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. And functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers skilled in the art to which the present invention pertains.

Although the preferred embodiment of the platform-based university information data analysis system using the big data according to the embodiment of the present invention has been described with reference to the above description and drawings, It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims. And will be apparent to those skilled in the art to which the invention pertains.

100: Data analysis system 110: Collected data normalization module
111: collection policy setting unit 112: classification code provision
113: authentication integrated management unit 114: data output unit
120: Data collection setting module 121: Data formatting section
122: key index setting unit 123: classification code setting unit
130: Data registration module 131: Data normalization module
132: core indicator addition unit 133: data classification unit
134: data registration unit 140: statistical information management module
141: Data set setting unit 142: Data mart generating unit
143: user request input unit 144: data extraction unit
145: statistical index generator 146: report generator
147: Performance Management Evaluation Unit

Claims (6)

A collection policy setting unit (111) for receiving a setting of a collection policy from a manager based on a conventional non - normalized data; a classification code setting unit (111) An authentication integration management unit (113) for managing authentication and integration information on the non - normalized data; And a data output unit (114) for outputting data and a data format to an administrator with respect to existing data, wherein the data output unit (114) is configured to collect data according to a collection policy A collection data normalization module 110 for automatically generating a format, managing authentication and integration information on existing data, and generating an output API for output to an administrator;
A data type setting unit 121 for setting a format of standardized data for unqualified data collected from an administrator, and a program management unit 121 for performing program-specific performance statistics required for classifying unqualified data collected from the manager, A core index setting unit that sets a core index for evaluating the performance of a business by presenting a reference value and a Mokpo value for each item and displaying an achievement rate obtained by dividing the achievement value of the item by the target value, (122); And a classification code setting unit (123) for setting a classification code from an administrator according to a core index according to the core index setting unit (122), wherein the classification index setting unit (123) A data collection setting module 120 for setting a format of data for data, setting a core index, managing a code of data, and setting a classification code according to a core index of collected data;
The API is automatically generated through the collection field for generating the normalized data through the data collection setting module 120, and is stored for each subject area on the performance statistics by program, business performance by department (department), and business performance by professor, A data registration module 130 for receiving the data; And
A data set for each program, which is necessary for generating a data mart from the data registered through the data registration module 130, a data set for business performance per department (department) and a business performance for each professor, and generates a data mart for each subject area And a statistical information management module (140) for generating pivot data and a statistical index in the form of a chart to be used in a visualization report according to a user's request. system. delete delete The method according to claim 1,
The data registration module (130)
A data normalization unit 131 for receiving data according to the data format setting unit 121 and normalizing the data denormalized according to the data collection setting module 120;
A key index appending unit 132 for appending a key index according to the core index setting unit 123 to the data normalized by the data normalization unit 131 to generate and classify data;
A data classification unit 133 for generating data to which a classification code is added for the normalized data classified according to the key index addition unit 132; And
And a data registration unit (134) for storing the data in the database by the classification code for the normalized data to which the classification code and the core index classified by the data classifying unit (133) are added and registering the same. A platform - based university information data analysis system using Big Data. The method according to claim 1,
The statistical information management module 140,
A data set setting unit 141 for setting a data set for program-specific performance statistics required for generation of a data mart from an administrator, business performance for each department (department), and business performance for each professor;
A data mart generating unit 142 for generating a data mart according to the setting of the data set setting unit 141;
A user request inputting section 143 for receiving, from a user, information about the type of data and the type of statistical index that meet the user's request;
A data extracting unit 144 for extracting necessary data according to a request of a user input from the user request input unit 143 from the data mart generated by the data mart generating unit 142; And
An statistical indicator generator 145 for generating statistical indicators according to the statistical indicators received from the user request input unit 143 using the data extracted by the data extracting unit 144;
And a report construction unit (146) for constructing a performance analysis visualization report based on the statistical indices generated by the statistical indicator generation unit (145). system. 6. The method according to claim 1 or 5,
The statistical information management module 140,
And a performance management evaluation unit 147 for displaying a reference value, a target value, a achieved value, and a achievement rate for each item of the key performance management indicator for the performance management of the business, to the user or the manager A platform - based university information data analysis system using Big Data.

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