CN104966172A - Large data visualization analysis and processing system for enterprise operation data analysis - Google Patents
Large data visualization analysis and processing system for enterprise operation data analysis Download PDFInfo
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Abstract
The invention relates to a large data visualization analysis and processing system for enterprise operation data analysis, which is characterized by comprising a data source judgment module, a data collection module, a data storage module, a data cleaning module, a data standardization processing module, and a background task scheduling module, wherein the data source judgment module is used for judging a data source for adopting a corresponding data collection mode; the data collection module collects data according to the corresponding data collection mode; the data storage module stores the data collected by the data collection module into to-be-cleaned data; the data cleaning module carries out data cleaning on the to-be-cleaned data and generates already-cleaned data; the data standardization processing module carries out standardization processing on the already-cleaned data, and a public navigation field is generated and stored to a data pool; and the background task scheduling module calls a built analysis model to analyze the data in the data pool and generates a visualization analysis result report. Compared with the prior art, the system of the invention has the advantages that the working efficiency is improved, cross-system data analysis is supported, secrecy is high and the like.
Description
Technical field
The present invention relates to large data processing field, especially relate to a kind of large data visualization analysis process system for enterprise operation data analysis.
Background technology
Enterprise data analysis is the basis of Modern Enterprise Administration.The Major Function of enterprise operation data analysis has: Information functions, advisory function and supervision function enterprise operation data analysis category mainly comprise: corporate environment and condition data analysis; Firms output data analysis; The data analysis of enterprise operation effect assessment; Business strategy data analysis etc.And a link important before carrying out enterprise data analysis is the collection and classification of enterprise operation data.Enterprise operation data collection techniques mostly adopts complete investigation (Statistical Account, raw readings etc.) to some immediate data enterprise, and indivedual field adopts sample survey.
Existing enterprise data analysis method roughly has following shortcoming:
1, in fairly large enterprise, each system of business operation control is often dominate construction at different times by different departments, its deposit data form is different, often also there is data redundancy, the various situations such as data are inconsistent, are difficult to Data Collection and the association analysis of carrying out cross-system.
2, business personnel does not grasp the data structure of bottom, directly cannot set up analytical model, effectively must could analyze data by the help of technician, affect the confidentiality of data analysis work and ageing, data analysis business need can not be met well.
3, business department has quite a lot of historical data yes-no formatization to store (as word document), cannot form effective knowledge hierarchy, be unfavorable for succession and the utilization of knowledge.
4, many enterprise external data have great help (public information etc. as law court, commercial department) to enterprise data analysis, but these data often form is various, exist place dispersion, can only manually search and analyze.
Summary of the invention
Object of the present invention is exactly provide a kind of increase work efficiency to overcome defect that above-mentioned prior art exists, support cross-system data analysis, the large data visualization analysis process system for enterprise operation data analysis that confidentiality is high.
Object of the present invention can be achieved through the following technical solutions:
For a large data visualization analysis process system for enterprise operation data analysis, comprising:
Data Source judge module, for judging that Data Source is to adopt corresponding Data Collection mode;
Data collection module, collects data according to corresponding Data Collection mode;
The data that described data collection module is collected are saved as data to be cleaned by data storage module;
Data cleansing module, carries out data cleansing to described data to be cleaned, generates and cleans data;
Data normalization processing module, carries out standardization to described data of having cleaned, and generates common pilot field, and is saved to data pool;
Background task scheduler module, calls the analytical model set up to the data analysis in data pool and generates visual analyzing report the test.
Described Data Source comprises internal format data, inner nonformatted data and external website data;
Corresponding Data Collection mode is specially:
For internal format data, adopt and carry out Data Collection to stationary interface, save as data to be cleaned;
For inner nonformatted data, by information extraction operations, described nonformatted data is converted into the laggard row Data Collection of formatted data, saves as data to be cleaned;
For external website data, adopt web crawlers technology to capture external website data, then information extraction operations is carried out to the data captured, nonformatted data is converted to formatted data, then carries out data collection process, save as data to be cleaned.
Described data cleansing refers to the gibberish rejected in data to be cleaned, and described gibberish comprises fail data, the outer data of the scope of business and specific privacy information.
Described data normalization processing module, to cleaning after data carry out standardization, upgrades data time stamp.
Described background task scheduler module is analyzed according to timing mode person event triggered fashion startup analysis model.
Described analytical model obtains by carrying out training to the sample data in data pool.
Described analytical model and analysis result are all kept in workspace.
Compared with prior art, the present invention has the following advantages:
1) unitized, the standardization of data layout; Set up common pilot field, carry out transformation of data and cleaning; Set up unified and standard business datum field, unified navigational field and data model, support the data analysis of cross-system.
2) on large Data Analysis Platform, visual analytical model is provided to build instrument, it is not only traditional statistically instrument, also the direct intelligent tool containing business implication is comprised as connected guarantee analysis, the intelligent algorithms such as five categories of loan, business personnel can easily be competent at whole analytical model life cycle management, reduce the computer capacity requirement to analysis modeling personnel, reduce the difficulty that business personnel sets up analytical model, eliminate the dependence to technician completely, increase work efficiency, ensured the confidentiality of data analysis work and ageing.
3) technological means such as index, information extraction is set up in employing, is extracted by the effective information in unformatted storage file, sets up knowledge base, fully effectively use historical data
4) adopt web crawlers to add the technological means such as information extraction, the effective information in external data is extracted, sets up key message storehouse, effectively use external data.
Accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.The present embodiment is implemented premised on technical solution of the present invention, give detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
The present embodiment provides a kind of large data visualization analysis process system for enterprise operation data analysis, comprise Data Source judge module, data collection module, data storage module, data cleansing module, data normalization processing module and background task scheduler module, wherein, Data Source judge module is for judging that Data Source is to adopt corresponding Data Collection mode; Data collection module is collected data according to corresponding Data Collection mode; The data that described data collection module is collected are saved as data to be cleaned by data storage module; Data cleansing module carries out data cleansing to described data to be cleaned, generates and has cleaned data and corresponding common pilot field; Data normalization processing module carries out standardization to described data of having cleaned, and is saved to data pool; Background task scheduler module is called the analytical model set up to the data analysis in data pool and is generated visual analyzing report the test.
As shown in Figure 1, applying the idiographic flow that above-mentioned large data visualization analysis platform carries out enterprise operation data analysis is:
1, whole treatment scheme can be set as regular initiation, the event that also can be set as triggers and carries out (as data file change, receive specific instruction, external website data has renewal etc.);
2, according to the difference of Data Source, different Data Collection sub-processes is initiated:
A) internal format data (data of each operation system): directly collect data according to stationary interface, data save as data to be cleaned;
B) inner nonformatted data (nonformatted data such as word document): carry out information extraction operations to document, nonformatted data is converted to formatted data, then carry out data collection process, data save as data to be cleaned;
C) external website data (outside, nonformatted data): use web crawlers technology to capture data, then information extraction operations is carried out to the data captured, nonformatted data is converted to formatted data; Finally carry out data collection process, data save as data to be cleaned;
3, carry out data cleansing by pre-defined rule, remove gibberish (comprising fail data, the outer data of the scope of business, specific privacy information etc.), and generate common pilot field;
4, data standardization is performed: will clean data importing to data pool according to standardization business scope; Waste treatment is carried out to the stale data in data pool; Upgrade data time stamp;
5, background task scheduler triggers according to timing or event the operation starting the analytical model set up, and carries out analyzing and processing, forms final analysis result, and leave in workspace by it to the mass data in data pool;
6, after task dispatcher has run analytical model, generate final analysis result information, be pushed to all levels of management personnel, analyst and business personnel by established rule.
The analytical model that background task scheduler calls obtains by carrying out training to the sample data in data pool, selects sample data suitable in data pool and carries out query statistic and analysis, form interrogation model and analytical model, be kept in workspace.
Should in the audit operations Data processing of Bank of Shanghai by the above-mentioned large data visualization analysis process system for enterprise operation data analysis, it is as follows that it implements operation:
Present system time is 21:00, following example process flow and data analysis flow process
1) according to default, the 21:00 of every night starts Data Collection flow process
A) each operation system data
That i. checks each operation system draws off deposit data catalogue with or without renewal;
Ii. judge whether it is new data by filename+timestamp;
Iii. providing data formatting process (fixed length set circle, length judges, processes, process Chinese character code special character) is carried out by standard format;
Iv. the data to be cleaned (data to be cleaned retain three days) before three days are removed;
V. the data processed are saved to data to be cleaned;
B) nonformatted data
I. check that nonformatted data storing directory is with or without renewal;
Ii. judge whether it is new data by filename+timestamp;
Iii. information extraction is carried out to nonformatted data, be converted to formatted data;
Iv. providing data formatting process (fixed length set circle, length judges, processes, process Chinese character code special character) is carried out by standard format;
V. the data to be cleaned (data to be cleaned retain three days) before three days are removed;
Vi. the data processed are saved to data to be cleaned;
C) external data
I. operational network reptile, captures related data (punishment of law court at different levels, the information such as to open a court session; The punishment information of union shop at different levels; The credit information of credit information service; The industry analysis report etc. of commercial affairs department); Save as unformatted message;
Ii. information extraction is carried out to nonformatted data, be converted to formatted data;
Iii. providing data formatting process (fixed length set circle, length judges, processes, process Chinese character code special character) is carried out by standard format;
Iv. the data to be cleaned (data to be cleaned retain three days) before three days are removed;
V. the data processed are saved to data to be cleaned;
2) evening, 23:00 started to carry out data cleansing
A) according to time range (Audit data validity is generally 3 years) cleaning data;
B) data are cleaned according to the scope of business (deleting the data of business of not launching according to industry and territorial scope);
C) according to specific privacy rule (row leader etc.) cleaning data;
D) the cleaning data (data to be cleaned retain three days) before three days are removed;
The data of e) having cleaned save as cleans data;
3) the next morning, 1:00 started data normalization operation
A) data (data retention time 3 years) outer between data retention period are deleted;
B) navigational field (department, customer ID, timestamp etc.) is generated;
C) processing time slide fastener (from flowing water class data genaration state class data);
D) data are imported according to business scope;
4) morning, 4:00 brought into operation analysis task
A) according to predefined number of concurrent (16 concurrent) startup analysis model, perform by step;
B) passing execution result (only retaining last execution result) is deleted;
C) step execution result is saved to workspace;
5) morning, 7:00 started report generation and propelling movement
A) report the test (whether operation result is successful, data time, the essential informations such as working time) and doubtful point data report (the doubtful point data that in task, each analytical model finally finds) are generated to the result of each task;
B) according to predetermined regular delivery report;
6) morning, 7:30 report distribution was complete, upgraded data time stamp
7) morning, 9:00 auditor started working, and carried out report and read and model buildings work
8) afternoon, 17:00 auditor came off duty; Each operation system starts to carry out unloading several work
9) 21:00 unloaded and counted up to into evening; Get back to 1).
Claims (7)
1., for a large data visualization analysis process system for enterprise operation data analysis, it is characterized in that, comprising:
Data Source judge module, for judging that Data Source is to adopt corresponding Data Collection mode;
Data collection module, collects data according to corresponding Data Collection mode;
The data that described data collection module is collected are saved as data to be cleaned by data storage module;
Data cleansing module, carries out data cleansing to described data to be cleaned, generates and cleans data;
Data normalization processing module, carries out standardization to described data of having cleaned, and generates common pilot field, and is saved to data pool;
Background task scheduler module, calls the analytical model set up to the data analysis in data pool and generates visual analyzing report the test.
2. the large data visualization analysis process system for enterprise operation data analysis according to claim 1, it is characterized in that, described Data Source comprises internal format data, inner nonformatted data and external website data;
Corresponding Data Collection mode is specially:
For internal format data, adopt and carry out Data Collection to stationary interface, save as data to be cleaned;
For inner nonformatted data, by information extraction operations, described nonformatted data is converted into the laggard row Data Collection of formatted data, saves as data to be cleaned;
For external website data, adopt web crawlers technology to capture external website data, then information extraction operations is carried out to the data captured, nonformatted data is converted to formatted data, then carries out data collection process, save as data to be cleaned.
3. the large data visualization analysis process system for enterprise operation data analysis according to claim 1, it is characterized in that, described data cleansing refers to the gibberish rejected in data to be cleaned, and described gibberish comprises fail data, the outer data of the scope of business and specific privacy information.
4. the large data visualization analysis process system for enterprise operation data analysis according to claim 1, is characterized in that, described data normalization processing module, to cleaning after data carry out standardization, upgrades data time stamp.
5. the large data visualization analysis process system for enterprise operation data analysis according to claim 1, is characterized in that, described background task scheduler module is analyzed according to timing mode person event triggered fashion startup analysis model.
6. the large data visualization analysis process system for enterprise operation data analysis according to claim 1, is characterized in that, described analytical model obtains by carrying out training to the sample data in data pool.
7. the large data visualization analysis process system for enterprise operation data analysis according to claim 1, it is characterized in that, described analytical model and analysis result are all kept in workspace.
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| CN105160038A (en) * | 2015-10-10 | 2015-12-16 | 广东卓维网络有限公司 | Data analysis method and system based on audit database |
| CN105447752A (en) * | 2015-12-08 | 2016-03-30 | 安徽融信金模信息技术有限公司 | Information sharing based enterprise credit assessment system |
| CN106202457A (en) * | 2016-07-17 | 2016-12-07 | 合肥赑歌数据科技有限公司 | A kind of distributed big data schema method |
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Application publication date: 20151007 |
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