CN109670098A - Industry based on big data technology is to mark implementation method - Google Patents
Industry based on big data technology is to mark implementation method Download PDFInfo
- Publication number
- CN109670098A CN109670098A CN201811563234.1A CN201811563234A CN109670098A CN 109670098 A CN109670098 A CN 109670098A CN 201811563234 A CN201811563234 A CN 201811563234A CN 109670098 A CN109670098 A CN 109670098A
- Authority
- CN
- China
- Prior art keywords
- data
- mark
- industry
- implementation method
- big data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses the industries based on big data technology to mark implementation method, includes the next steps: 1) to mark data acquisition；2) mark data are compared；3) to mark data exhibiting, the mark post of industry can be more comprehensively analyzed by big data crawler technology, comparison mark post is found out where one has lagged behind, and echarts Visual Chart is passed through, what is be more clear shows the gap of itself and Best of Breed, to specify the general direction of work.It can also constantly be gone beyond oneself, by the way that confidence compared with itself, can be enhanced so as to more effectively push enterprise to industry best level snap using enterprise itself best level as internal mark post.
Description
Technical field:
The present invention relates to big data processing technology fields, and in particular to the industry based on big data technology is to mark realization side
Method.
Background technique:
In big data era, data mining is chief work.The excavation of big data be from magnanimity, it is incomplete, have
Discovery is implied in wherein valuable, potentially useful information and knowledge in noise, fuzzy, random large database
Process and a kind of decision support processes.It is based primarily upon artificial intelligence, machine learning, pattern learning, statistics etc..Pass through
Big data is analyzed increasingly automatedly, makes the reasoning of inductive, therefrom excavates potential mode.
And so-called " to mark " is exactly to compare mark post to find out where one has lagged behind.Carry out bidding assessment, the sight of enterprise is sought to tightly to stare at
Firmly industry best level, specifies the gap of itself and Best of Breed, to specify the general direction of work.
Traditional industry is lack of pertinence mark index system, is poor to mark directiveness, index is without further decomposing downwards
And refinement, the forming process of index not can be effectively controlled.
Summary of the invention:
The prior art is difficult to meet the needs of people, and to solve the above problems, the invention proposes based on big
The industry of data technique is to mark implementation method.
To achieve the above object, the invention provides the following technical scheme: the industry based on big data technology is to mark realization side
Method, it is characterised in that: the following steps are included:
(1) to mark data acquisition；
(2) mark data are compared；
(3) to mark data exhibiting.
Preferably, in the step 1 to mark data acquisition the following steps are included:
(1) by aggregation crawler technology, reservation is related with theme to be linked, and index is established, to retrieve and to inquire later；
And it puts it into etc. in URL queue to be captured；Then folding is selected to grab from queue in next step according to certain search strategy
Webpage URL, stop until reaching the desired result of system；In addition, the data being crawled will will be further described, analyze, mistake
Filter is finally stored, so that the industry data of State Statistics Bureau is obtained, including industry achievement data, economical operation data etc.；
(2) financial data of all listed companies in stock markets of Shanghai and Shenzhen and the financial data of new three plate company are obtained, to financial number
Industry achievement data is calculated according to index is carried out；
(3) State-owned Assets Supervision industry achievement data is obtained；
(4) achievement data of the same trade is obtained, general enterprises voluntarily provide.
Further, the foundation in above-mentioned steps 1 is indexed, including with ClouderaSearch full-text index,
Real-time query and index service for CDH and your extension at Enterprise Data center, flexibility；Based on MapReduce reality
Now batch indexes；Dynamic rope (Dynamic index) is drawn by GO-LIVE and is updated；For real-time query, it is integrated with
Flume and Lily HBase indexer；The support of non-mode (Schema-less) and dynamic field make schema management more
Simply；The support of multifile (Multi-file) format and integration capability；By HDFS, realize that scalability and fault-tolerance index are deposited
Storage and access；With integrating for Apache Sentry, based role, fine-grained permission control are realized；By using Index
Aliasing and Oozie workflows using Data Migration and is serviced simpler.
Further, for the described search strategy in above-mentioned steps 1 the following steps are included:
(1) classified according to affiliated web site, the website more for the page to be downloaded is preferential to download；
(2) it is then retrieved for downloading the more website of the page according to the level of tree, if this level is not retrieved
It completes, then will not enter next level；
(3) level is only waited search complete the retrieval for just carrying out next level；Because whole figure can be retrieved,
More webpages can be covered as far as possible；
Preferably, in the step 2 to mark data comparing the following steps are included:
1) increase by the asset-liability ratio of different regions of the same trade or different company, liquidity ratio, current rate, operating income
The financial index such as long rate, running cost growth rate are compared analysis, pass through lateral, longitudinal various dimensions comparison；
2) standardized comparison object and measurement are established, establish it is standardized comparison can be time standard, space criteria,
Specific criteria, planning standard.
3) by monthly, average daily, three index systems per capita, the flow performance of enterprise's application is described comprehensively, with competing product pair
Than diagnosing problem, apparent strengths and weaknesses；
4) single industry is clicked again or company enters the trend comparison analysis based on the time of current industry or company；
5) by analysis user context data, cashability and market strategy effect are assessed；By user's competition analysis, comment
Estimate the possibility of competing product user conversion.
Preferably, in the step 3 to mark data exhibiting the following steps are included:
1) data exhibiting uses data visualization tool echarts, for handling the visual analyzing of big data；It can make
The displaying of various data is shown with charts such as k line chart, cake chart, histogram, rectangular system line charts；
2) compare and ranking analysis rectangular system line chart is shown, the ranking and difference to mark data can be obviously observed
Away from；
3) trend comparison analysis is shown with k line chart, is capable of the real variation of thorough observed to mark data.
Compared with prior art, the beneficial effects of the present invention are:
The mark post of industry can be more comprehensively analyzed by big data crawler technology, comparison mark post is found out where one has lagged behind, passed through
Echarts Visual Chart, what is be more clear shows the gap of itself and Best of Breed, to specify the totality side of work
To.It can also be constantly super using enterprise itself best level as internal mark post, by the way that confidence can be enhanced compared with itself
More self, so as to more effectively push enterprise to industry best level snap.
Detailed description of the invention:
Fig. 1 is flow diagram of the invention；
Specific embodiment:
In order to be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, tie below
Conjunction is specifically illustrating, and the present invention is further explained.
Embodiment 1, the industry based on big data technology is to mark implementation method, it is characterised in that: the following steps are included:
(1) to mark data acquisition；
(2) mark data are compared；
(3) to mark data exhibiting.
Embodiment 2
Place same as Example 1 no longer repeats, and difference from Example 1 is:
Preferably, in the step 1 to mark data acquisition the following steps are included:
(1) by aggregation crawler technology, reservation is related with theme to be linked, and index is established, to retrieve and to inquire later；
And it puts it into etc. in URL queue to be captured；Then folding is selected to grab from queue in next step according to certain search strategy
Webpage URL, stop until reaching the desired result of system；In addition, the data being crawled will will be further described, analyze, mistake
Filter is finally stored, so that the industry data of State Statistics Bureau is obtained, including industry achievement data, economical operation data etc.；
(2) financial data of all listed companies in stock markets of Shanghai and Shenzhen and the financial data of new three plate company are obtained, to financial number
Industry achievement data is calculated according to index is carried out；
(3) State-owned Assets Supervision industry achievement data is obtained；
(4) achievement data of the same trade is obtained, general enterprises voluntarily provide.
Embodiment 3
Place same as Example 2 no longer repeats, and difference from Example 1 is:
Further, the foundation in above-mentioned steps 1 is indexed, including with ClouderaSearch full-text index,
Real-time query and index service for CDH and your extension at Enterprise Data center, flexibility；Based on MapReduce reality
Now batch indexes；Dynamic rope (Dynamic index) is drawn by GO-LIVE and is updated；For real-time query, it is integrated with
Flume and Lily HBase indexer；The support of non-mode (Schema-less) and dynamic field make schema management more
Simply；The support of multifile (Multi-file) format and integration capability；By HDFS, realize that scalability and fault-tolerance index are deposited
Storage and access；With integrating for Apache Sentry, based role, fine-grained permission control are realized；By using Index
Aliasing and Oozie workflows using Data Migration and is serviced simpler.
Embodiment 4
Place same as Example 2 no longer repeats, and difference from Example 1 is:
Further, for the described search strategy in above-mentioned steps 1 the following steps are included:
(1) classified according to affiliated web site, the website more for the page to be downloaded is preferential to download；
(2) it is then retrieved for downloading the more website of the page according to the level of tree, if this level is not retrieved
It completes, then will not enter next level；
(3) level is only waited search complete the retrieval for just carrying out next level；Because whole figure can be retrieved,
More webpages can be covered as far as possible.
Embodiment 5
Place same as Example 2 no longer repeats, and difference from Example 1 is:
Preferably, in the step 2 to mark data comparing the following steps are included:
1) increase by the asset-liability ratio of different regions of the same trade or different company, liquidity ratio, current rate, operating income
The financial index such as long rate, running cost growth rate are compared analysis, pass through lateral, longitudinal various dimensions comparison；
2) standardized comparison object and measurement are established, establish it is standardized comparison can be time standard, space criteria,
Specific criteria, planning standard.
3) by monthly, average daily, three index systems per capita, the flow performance of enterprise's application is described comprehensively, with competing product pair
Than diagnosing problem, apparent strengths and weaknesses；
4) single industry is clicked again or company enters the trend comparison analysis based on the time of current industry or company；
5) by analysis user context data, cashability and market strategy effect are assessed；By user's competition analysis, comment
Estimate the possibility of competing product user conversion.
Embodiment 6
Place same as Example 5 no longer repeats, and difference from Example 1 is:
Preferably, in the step 3 to mark data exhibiting the following steps are included:.
1) data exhibiting uses data visualization tool echarts, for handling the visual analyzing of big data；It can make
The displaying of various data is shown with charts such as k line chart, cake chart, histogram, rectangular system line charts；
2) compare and ranking analysis rectangular system line chart is shown, the ranking and difference to mark data can be obviously observed
Away from；
3) trend comparison analysis is shown with k line chart, is capable of the real variation of thorough observed to mark data.
The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the above embodiments and description only describe this
The principle of invention, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its
Equivalent thereof.
Claims (4)
1. the industry based on big data technology is to mark implementation method, it is characterised in that: the following steps are included:
(1) to mark data acquisition；
(2) mark data are compared；
(3) to mark data exhibiting.
2. the industry according to claim 1 based on big data technology is to mark implementation method, it is characterised in that: the step
In 1 to mark data acquisition the following steps are included:
(1) by aggregation crawler technology, reservation is related with theme to be linked, and index is established, to retrieve and to inquire later；And it will
It is put into etc. in URL queue to be captured；Then the folding net to be grabbed in next step is selected from queue according to certain search strategy
Page URL stops until reaching the desired result of system；In addition, the data being crawled will will be further described, analyze, filter most
After stored, to obtain the industry data of State Statistics Bureau, including industry achievement data, economical operation data etc.；
(2) obtain all listed companies in stock markets of Shanghai and Shenzhen financial data and new three plate company financial data, to financial data into
Industry achievement data is calculated in row index；
(3) State-owned Assets Supervision industry achievement data is obtained；
(4) achievement data of the same trade is obtained, general enterprises voluntarily provide.
3. the industry according to claim 1 based on big data technology is to mark implementation method, it is characterised in that: the step
In 2 to mark data comparing the following steps are included:
(1) increase by the asset-liability ratio of different regions of the same trade or different company, liquidity ratio, current rate, operating income
The financial index such as rate, running cost growth rate are compared analysis, pass through lateral, longitudinal various dimensions comparison；
(2) standardized comparison object and measurement are established, establishing standardized comparison can be time standard, space criteria, spy
Calibration standard, planning standard；
(3) it by the way that monthly, average daily, three index systems, the flow for describing enterprise's application comprehensively show per capita, is examined with the comparison of competing product
Disconnected problem, apparent strengths and weaknesses；
(4) single industry is clicked again or company enters the trend comparison analysis based on the time of current industry or company；
(5) by analysis user context data, cashability and market strategy effect are assessed, passes through user's competition analysis, assessment
The possibility of competing product user conversion.
4. the industry according to claim 1 based on big data technology is to mark implementation method, it is characterised in that: the step
In 3 to mark data exhibiting the following steps are included:
1) data exhibiting uses data visualization tool echarts, for handling the visual analyzing of big data；K can be used
The charts such as line chart, cake chart, histogram, rectangular system line chart show the displayings of various data；
2) compare and ranking analysis rectangular system line chart is shown, the ranking and gap to mark data can be obviously observed；
3) trend comparison analysis is shown with k line chart, is capable of the real variation of thorough observed to mark data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811563234.1A CN109670098A (en) | 2018-12-20 | 2018-12-20 | Industry based on big data technology is to mark implementation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811563234.1A CN109670098A (en) | 2018-12-20 | 2018-12-20 | Industry based on big data technology is to mark implementation method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109670098A true CN109670098A (en) | 2019-04-23 |
Family
ID=66144006
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811563234.1A Pending CN109670098A (en) | 2018-12-20 | 2018-12-20 | Industry based on big data technology is to mark implementation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109670098A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111612313A (en) * | 2020-04-29 | 2020-09-01 | 上海融贷通金融信息服务有限公司 | Valuation management system for non-listed enterprises |
| CN112667634A (en) * | 2020-12-29 | 2021-04-16 | 广州广电运通信息科技有限公司 | Benchmarking analysis method, system, device and storage medium for enterprise data |
| CN112819297A (en) * | 2021-01-18 | 2021-05-18 | 树根互联股份有限公司 | Production task completion efficiency analysis method and device and terminal equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7043066B1 (en) * | 1998-11-05 | 2006-05-09 | Arch Development Corporation | System for computerized processing of chest radiographic images |
| CN102750653A (en) * | 2011-04-20 | 2012-10-24 | 中国南方电网有限责任公司 | Method and system for performing multi-dimensional benchmarking analysis on electric power scheduling information |
| CN104156801A (en) * | 2014-07-17 | 2014-11-19 | 国网山东省电力公司 | Benchmarking data processing system and data processing method for municipal company teams |
| CN105184451A (en) * | 2015-08-14 | 2015-12-23 | 国网天津市电力公司 | Benchmarking result assessment evaluation realization method based on mark post deviation method |
| CN107464134A (en) * | 2017-07-10 | 2017-12-12 | 广东华联建设投资管理股份有限公司 | A kind of various dimensions material price comparative analysis and visualization show method |
| CN108681842A (en) * | 2018-07-06 | 2018-10-19 | 广州广电研究院有限公司 | Bidding assessment method, apparatus, equipment and the medium of conglomerate's management state |
-
2018
- 2018-12-20 CN CN201811563234.1A patent/CN109670098A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7043066B1 (en) * | 1998-11-05 | 2006-05-09 | Arch Development Corporation | System for computerized processing of chest radiographic images |
| CN102750653A (en) * | 2011-04-20 | 2012-10-24 | 中国南方电网有限责任公司 | Method and system for performing multi-dimensional benchmarking analysis on electric power scheduling information |
| CN104156801A (en) * | 2014-07-17 | 2014-11-19 | 国网山东省电力公司 | Benchmarking data processing system and data processing method for municipal company teams |
| CN105184451A (en) * | 2015-08-14 | 2015-12-23 | 国网天津市电力公司 | Benchmarking result assessment evaluation realization method based on mark post deviation method |
| CN107464134A (en) * | 2017-07-10 | 2017-12-12 | 广东华联建设投资管理股份有限公司 | A kind of various dimensions material price comparative analysis and visualization show method |
| CN108681842A (en) * | 2018-07-06 | 2018-10-19 | 广州广电研究院有限公司 | Bidding assessment method, apparatus, equipment and the medium of conglomerate's management state |
Non-Patent Citations (1)
| Title |
|---|
| 赵赛锋等: "基于智能化辅助分析系统的对标数据可视化管理与应用", 《企业管理》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111612313A (en) * | 2020-04-29 | 2020-09-01 | 上海融贷通金融信息服务有限公司 | Valuation management system for non-listed enterprises |
| CN112667634A (en) * | 2020-12-29 | 2021-04-16 | 广州广电运通信息科技有限公司 | Benchmarking analysis method, system, device and storage medium for enterprise data |
| CN112819297A (en) * | 2021-01-18 | 2021-05-18 | 树根互联股份有限公司 | Production task completion efficiency analysis method and device and terminal equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Maynard et al. | Assessing relative resilience potential of coral reefs to inform management | |
| Khan et al. | Business intelligence: an integrated approach | |
| Shneiderman et al. | Network visualization by semantic substrates | |
| Shankarnarayan et al. | Paradigm change in Indian agricultural practices using Big Data: Challenges and opportunities from field to plate | |
| CN109670098A (en) | Industry based on big data technology is to mark implementation method | |
| CN106844585A (en) | A kind of time-space relationship analysis system based on multi-source Internet of Things location aware | |
| Guo et al. | Detecting spatial community structure in movements | |
| Sumiran | An overview of data mining techniques and their application in industrial engineering | |
| Matlaba et al. | Classic and spatial shift-share analysis of state-level employment change in Brazil | |
| Kemball-Cook et al. | The search for appropriate OR: A review of operational research in developing countries | |
| Chen et al. | Visualization in law enforcement | |
| CN108416524A (en) | Estate planning based on a figure general framework refines deciphering method | |
| Mladineo et al. | An evaluation of multicriteria analysis for DSS in public policy decision | |
| Brondízio | Intraregional analysis of land-use change in the Amazon | |
| DE112018005424T5 (en) | Automatic connection of external data with a business analysis process | |
| CN112990575A (en) | Industry development path prediction method and device based on knowledge graph | |
| CN113064998A (en) | Map construction method and device for financial institution wind control and storage medium | |
| Jiang et al. | Discovering periodic frequent travel patterns of individual metro passengers considering different time granularities and station attributes | |
| CN104885075B (en) | A kind of method and device executing reverse search using crucial link | |
| CN110175151A (en) | A kind of processing method, device, equipment and the storage medium of agricultural big data | |
| Minn et al. | Detection of foreclosure-related landscape management changes using Landsat | |
| Wang et al. | Visual analytics of topological higher order information for emergency management based on tourism trajectory datasets | |
| CN107562909A (en) | A kind of big data analysis system and its analysis method for merging search and calculating | |
| CN107678839A (en) | Client's follow-up method, system and readable storage medium storing program for executing based on priority | |
| Xu et al. | Vector quantization: Timeline-based location data extraction and route fitting for crowdsourcing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190423 |