KR101584661B1 - RTE-based big data analysis system and method - Google Patents

Abstract

The present invention relates to an RTA-based big data analysis system and a method thereof. The system configures metadata in an XML format including a view from a data generation start point or stores the metadata in a NoSQL DB to provide the metadata. The system includes: multiple user terminals; and a big data analysis server which collects raw data generated after online connections of the user terminals are established, converts the collected raw data to metadata in the XML format to store the metadata in an XML database, and provides the metadata stored in the XML database in response to a request from a user terminal. The system enables a user to configure a pattern needed for an analysis directly and create visualization data in a desired format.

Description

[0002] RTE-based big data analysis system and method [

More particularly, the present invention relates to an RTE-based big data analysis system and method, and more particularly, to an RTE-based big data analysis system and method, in which an XML formatted metadata including a view is generated from a data generation point, Analysis system and method.

Currently, the method of storing the data of Law Data, Log Data, Document Data, and DB Data in the DB and searching and analyzing as needed is not enough to analyze the big data that requires RTE. Even if analysis is possible, Customers, and countries need to select various solutions according to the requesting service, and in order to visualize after analyzing, it is inevitable to use another solution to provide services.

This has the problem that it can not get out of the vicious cycle of constantly paying the cost to the SI company.

Korean Patent Publication No. 10-2014-0005474

In order to solve such a problem, the present invention provides an RTE-based big data analysis system and method for storing metadata in an XML format including a view from a data generation point and storing the metadata in an XML DB or NoSQL DB .

An RTE-based big data analysis system according to an embodiment of the present invention includes a plurality of user terminals; And raw data generated after online connection of user terminals, converts the collected raw data into XML formatted metadata, stores and manages the XML data in the XML database, and provides metadata stored in the XML database in response to a request from the user terminal And a large data analysis server.

As an embodiment related to the present invention, a big data analysis server may include a data collecting unit for collecting data generated at one time during data retrieval, data retrieval, and data upload from the time of online connection of user terminals to raw data And converts the raw data collected by the data collecting unit into XML formatted metadata and stores the converted metadata in an XML database. In response to the request information provided from the user terminal, the metadata stored in the XML database is stored in a large data search function, , A business intelligent function, and a D / W function, and a data analysis unit for providing the analysis result, and a data analysis unit for analyzing the result of the analysis, such as a report, a chart, a web service, EAI, a dashboard, And a data providing unit for providing the data to the output unit.

In an embodiment related to the present invention, the data collected by the data collecting unit may be any of database, log data, document, multimedia, SNS and e-mail, XML, unspecified number of protocols, and binary format data.

As an embodiment related to the present invention, the data analysis unit may check whether the metadata of the XML format is consistent or not, and then store the metadata in the XML database.

As an embodiment related to the present invention, when the data analyzing unit stores the XML formatted metadata in the XML database, the data analyzing unit can create the screen in the wig-wig format and store it together with the corresponding XML formatted metadata.

As an embodiment related to the present invention, the data analysis unit determines whether the data collected by the data collecting unit is normal data, and if it is normal data, supports to convert it into XML formatted metadata, and if it is abnormal data, And a second data analysis unit for receiving normal data in response to the support of the first data analysis unit, converting the received normal data into XML formatted metadata, and storing the converted XML data in an XML database.

As an embodiment related to the present invention, if the collected data is determined to be abnormal data, the first data analysis unit may extract user information from the collected data and transmit an abnormal data generation alarm message based on the user information.

As an embodiment related to the present invention, when the first data analysis unit transmits the data authentication alarm message together with the authentication data input request message and the authentication data is input in response to the authentication data input request message, It is possible to proceed.

According to the embodiment of the present invention, if the first authentication data is not received within a predetermined time, the first data analysis unit may reject the request process and provide a rejection guidance message.

The RTE-based big data analysis method according to an embodiment of the present invention includes the steps of: collecting raw data generated by a user terminal having an online connection from a time of online connection of a user terminal; Analyzing the collected raw data to determine whether the big data analysis server is normal data; And the big data analysis server may convert the converted raw data into XML formatted metadata if the collected raw data is judged to be normal data, and store the transformed metadata in the XML database.

As an embodiment related to the present invention, when the collected raw data is not judged as normal data, the big data analysis server extracts user information from the collected raw data, and transmits an abnormal data generation alarm message and a user authentication information input request message ; Transmitting the abnormal data generation alarm message and the authentication information input request message based on the user information to the big data analysis server; The big data analysis server judges whether or not the identity authentication information is received within a preset time; And the big data analysis server proceeds with the process when the authentication information is received within a preset time, rejects the authentication process if the authentication information is not received within a preset time, and outputs a rejection guidance message have.

As an embodiment related to the present invention, when the big data analysis server stores the metadata of the XML format in the XML database, the big data analysis server can create the screen in the wig-wig format and register it together with the metadata of the XML format.

The present invention is configured in the form of XML formatted meta data including a view from the data creation point, and is stored in an XML DB or NoSQL DB to provide a user with a pattern for direct analysis, It has the effect of making it possible to produce the data.

In addition, the present invention utilizes SOA-based XML, so that any data can be analyzed, visualized, and analyzed on the same platform, so that it can escape the dependency from the SI vendor and reduce the enormous cost of ICT have.

In addition, since the present invention performs a desired operation on the same platform, there is no need for further convergence, and since it is developed as a W3C standard, various Open API solutions can be freely utilized.

1 is a diagram for explaining an RTE-based big data analysis system according to the present invention.
FIG. 2 is a flowchart illustrating an RTE-based big data analysis method according to the present invention.
3 is a service screen diagram provided by the RTE-based big data analysis system of FIG.

It is noted that the technical terms used in the present invention are used only to describe specific embodiments and are not intended to limit the present invention. In addition, the technical terms used in the present invention should be construed in a sense generally understood by a person having ordinary skill in the art to which the present invention belongs, unless otherwise defined in the present invention, Should not be construed to mean, or be interpreted in an excessively reduced sense. In addition, when a technical term used in the present invention is an erroneous technical term that does not accurately express the concept of the present invention, it should be understood that technical terms can be understood by those skilled in the art. In addition, the general terms used in the present invention should be interpreted according to a predefined or prior context, and should not be construed as being excessively reduced.

Furthermore, the singular expressions used in the present invention include plural expressions unless the context clearly dictates otherwise. In the present invention, terms such as "comprising" or "comprising" and the like should not be construed as encompassing various elements or various steps of the invention, Or may further include additional components or steps.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals refer to like or similar elements throughout the several views, and redundant description thereof will be omitted.

1 is a diagram for explaining an RTE-based big data analysis system according to the present invention.

As shown in FIG. 1, the RTE-based big data analysis system to which the present invention is applied collects raw data generated after on-line connection of a plurality of user terminals 100 and user terminals 100, Into a meta data in an XML format, stores the meta data in an XML database and manages it, and provides a meta data stored in an XML database in response to a request from the user terminal.

The big data analysis server 200 is configured to include an XML database 210 storing XML formatted meta data and an XML database 210 storing the meta data in XML format at a point in time of data retrieval, A data collecting unit 220 for collecting the generated data as raw data, a data collecting unit 220 for converting the raw data collected by the data collecting unit 220 into XML formatted metadata and storing the same in the XML database 210, Analysis and development function, a business intelligent function, and a D / W function in response to the request information provided from the service provider 100, and provides analysis results The analysis result of the data analyzing unit 230 and the data analyzing unit 230 can be used as a report, a chart, a web service, an EAI (Enterprise Application Intergration) And a data providing unit (240) for providing an output method of any one of print formats. In other words, the data analysis unit 230 converts all the collected raw data into metadata of the XML format and stores the converted metadata in the XML format, thereby allowing the data providing unit 240 to integrate the new data, So that analysis statistical data can be generated and provided as shown in FIG. Thus, data can be shared even without introducing any conversion process with an existing program.

The data collected by the data collection unit 220 includes a database, log data, documents, multimedia, SNS and e-mail, XML, unspecified number of protocols, and binary format data.

The data analysis unit 230 checks whether or not the metadata of the XML format is coherent and registers the XML data in the XML database 210.

When the data analyzing unit 230 stores the metadata of the XML format in the XML database, the data analyzing unit 230 can create the screen in the wig-wig format and store it together with the metadata of the XML format.

The data analysis unit 230 determines whether the data collected by the data collection unit 220 is normal data. If the data is normal data, the data analysis unit 230 supports conversion into XML formatted meta data. If the data is abnormal data, And a second data analyzing unit 232 for receiving normal data in response to the support of the first data analyzing unit 231, converting the received normal data into XML formatted metadata, .

If the collected data is determined to be abnormal data, the first data analyzer 231 extracts the user information from the collected data and transmits an abnormal data generation alarm message based on the user information.

The first data analyzing unit 231 transmits a request message for inputting the authentication information when sending the data generation alarm message, and if the authentication information is input in response to the authentication information input request message, the next process is performed.

If the first data analysis unit 231 does not receive the authentication information within a predetermined time, it rejects the request process and provides a rejection guidance message.

An operation method of the RTE-based big data analysis system configured as described above will be described below.

FIG. 2 is a flowchart illustrating an RTE-based big data analysis method according to the present invention. 3 is a service screen diagram provided by the RTE-based big data analysis system of FIG.

As shown in FIG. 2, the RTE-based big data analysis method according to the embodiment is a method in which the big data analysis server 200 generates the RTE-based big data from the online connection time of the user terminal 100 (S110). For example, when an RTE-based Big Data Analysis System is implemented to link with a portal search site such as Daum, Naver, etc., a myriad of visitors visit the site for data retrieval. At this time, To be stored in the XML database 210 (FIG. 2) and managed.

The big data analysis server 200 analyzes the collected raw data to determine whether the data is normal or not (S120). If the collected raw data is determined to be normal data, Converted into data, stored in the XML database 210, and managed (S130). Here, the collected raw data are database, log data, document, multimedia, SNS and e-mail, XML, unspecified number of protocols, and binary format data, and the rest except database data is directly converted into XML formatted metadata And converts the data into DB 2 XML format data in the case of database data, and stores the converted data in the XML database 210.

If it is determined in step S120 that the collected raw data is not normal data, the big data analysis server 200 extracts user information from the collected raw data, and transmits an abnormal data generation alarm message and a user authentication information input request message (S140).

The big data analysis server 200 transmits an abnormal data generation alarm message and a user authentication information input request message based on the user information (S150). Then, the big data analysis server 200 determines whether the authentication information is received within a preset time (S160).

As a result of the determination in step S160, when the identity authentication information is received within a predetermined time, the big data analysis server 200 proceeds to the corresponding process (S170). If the identity authentication information is not received within the preset time, A guidance message is output (S180).

Meanwhile, when the big data analysis server 200 stores the XML formatted metadata in the XML database 210 in step S130, it creates a screen in a wig format and stores it together with the corresponding XML formatted metadata.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or essential characteristics thereof. Therefore, the embodiments disclosed in the present invention are intended to illustrate rather than limit the scope of the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention should be construed according to the following claims, and all technical ideas within the scope of equivalents should be construed as falling within the scope of the present invention.

100: User terminal
200: Big Data Analysis Server
210: XML database
220: Data collection unit
230: Data analysis unit
231: first data analysis unit
232: second data analysis unit
240: data provider
300: Network

Claims (12)

A plurality of user terminals; And
The raw data generated after the online connection of the user terminals is collected, the raw data collected is converted into XML formatted metadata, the XML data is stored and managed in the XML database, and the metadata stored in the XML database is provided Includes Big Data Analysis Server,
Wherein the big data analysis server comprises:
A data collecting unit for collecting, as raw data, data generated at one of the time of data retrieval, data retrieval, and data upload from the online connection of the user terminals;
An XML conversion unit for converting the raw data collected by the data collecting unit into XML formatted metadata and building the XML data into an XML database,
Analyzing the XML formatted metadata converted by the XML conversion unit as one of a big data search function, an analysis & development function, a business intelligent function, and a D / W function in response to request information provided from the user terminal, A data analysis unit for providing an analysis result,
And a data providing unit for providing an analysis result of the data analyzing unit as an output method of a report, a chart, a web service, an EAI, a dashboard, and a print form,
The data analysis unit may determine whether the data collected by the data collection unit is normal data, convert the data into XML formatted metadata in case of normal data, A data analysis unit,
And a second data analysis unit for receiving normal data in response to the support of the first data analysis unit, converting the data into XML-formatted metadata, and storing the XML-formatted metadata in an XML database.
delete delete delete delete delete The method according to claim 1,
The first data analyzing unit,
Extracts user information from the collected data when the collected data is determined to be abnormal data, and transmits an abnormal data generation alarm message based on the user information.
8. The method of claim 7,
The first data analyzing unit,
And transmits the authentication information input request message when transmitting the data generation alarm message. When the authentication information is input in response to the authentication information input request message, the process proceeds to the next process. .
9. The method of claim 8,
The first data analyzing unit,
If the authentication information is not received within a predetermined period of time, reject the request process and provide a rejection guidance message.
Collecting raw data generated by a user terminal having an online connection from a time of online connection of the user terminal;
Analyzing the collected raw data to determine whether the data is normal data; And
Wherein the big data analysis server converts the collected raw data into XML formatted metadata if the collected raw data is determined to be normal data, and stores the converted metadata in an XML database,
Extracting user information from the collected raw data and generating an abnormal data generation alarm message and a user authentication information input request message when the collected raw data is not judged as normal data;
Transmitting the abnormal data generation alarm message and the authentication information input request message to the big data analysis server based on the user information;
The big data analysis server determining whether the authentication information is received within a preset time; And
The big data analysis server advances the process when the authentication information is received within a predetermined time, rejects the authentication process if the authentication information is not received within a preset time, and outputs a rejection guidance message;
Wherein the RTE-based big data analysis method comprises: delete delete

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