CN108959578A - A kind of tax data crash analysis method - Google Patents
A kind of tax data crash analysis method Download PDFInfo
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- CN108959578A CN108959578A CN201810738338.5A CN201810738338A CN108959578A CN 108959578 A CN108959578 A CN 108959578A CN 201810738338 A CN201810738338 A CN 201810738338A CN 108959578 A CN108959578 A CN 108959578A
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Abstract
The invention discloses a kind of tax data crash analysis methods, belong to technical field of data processing.Tax data crash analysis method of the invention, based on data warehouse, different business data collision is realized by custom rule, the data needed, wherein front end is pulled and Jsplumb line-connecting machine using Jquery, table in data warehouse is dragged in design area, data needed for the different data of line obtain by user.The tax data crash analysis method flexibility ratio of the invention is more preferable, more friendly to user, can satisfy different business demands, has good application value.
Description
Technical field
The present invention relates to technical field of data processing, specifically provide a kind of tax data crash analysis method.
Background technique
With the popularization of Golden Taxes the third stage of the project and the foundation of data management system, tax system realizes " the big collection of data
In ", how to make full use of these to become urgent problem to be solved from the data of each operation system.
Summary of the invention
Technical assignment of the invention is that in view of the above problems, it is more preferable to provide a kind of flexibility ratio, more friendly to user
It is good, it can satisfy the tax data crash analysis method of different business demands.
To achieve the above object, the present invention provides the following technical scheme that
A kind of tax data crash analysis method, this method are based on data warehouse, realize different business number by custom rule
According to collision, the data needed, wherein using Jquery dragging and Jsplumb line-connecting machine, user will be in data warehouse for front end
Table be dragged in design area, data needed for the different data of line obtain.
In tax data crash analysis method of the invention, more friendly, the line associated data of user's interaction of dragging
It is more vivid.Data warehouse possesses good linear expansion ability as distributed data base using GP database.
Preferably, this method includes data modeling, model theme library, model publication and modeling statistics, data modeling mistake
It include that model introduces, the addition of table node, incidence relation adds, data preview and model execute in journey, model theme library includes upper
Grade model data is checked, the inquiry of the same level model data, data select, data screening and data export, model publication include data
Distribute verifying, recommendation from bottom to top, it is top-down check, the reference from sharing at the same level and reticular structure, model system
Meter includes modeling situation statistics, log situation analysis, implementing result is checked, operating condition is checked and model service condition.
Preferably, the data modeling process by the data in different business domain with from treated for internet data into
Row association collision, obtains required data.
Preferably, data modeling process specifically includes the following steps:
S1: the data screening in different business domain converts to obtain treated business numeric field data；
S2: by treated, business datum is associated with to obtain crash data；
S3: crash data is screened, converts to obtain processing data；
S4: internet data screened, converts to obtain treated internet data；
S5: treated, and internet data is converted to obtain required data with processing data correlation.
Preferably, classifying the table in data warehouse to form assets mesh according to business domains first during data modeling
Record tree, statement of assets tree main body is divided into the modelling area on top and the browsing data area of lower part, in modelling area to data
Data in warehouse are designed, and in browsing data area, each table node to modelling area carries out data preview.
Tables of data is dragged into modelling area using Jquery technology preferably, pinning the following table of statement of assets tree
Table node is formed, binodal tables of data node operates tables of data, type, the type of tables of data including selecting tables of data
Detail list and summary sheet.
Preferably, being associated using Jsplumb line-connecting machine to tables of data between two table nodes, data correlation relation
Go out including interior connection, left connection, right connection, left bank, right discharge and duplicate removal merge.
Preferably, two tables of data associations generate temporary data table, relevant tax number is obtained by two tables of data collisions
According to continuing to be dragged in tables of data and current temporary data table line, collide out relevant tax data.
Preferably, after the completion of data modeling, to establishing data query, the number that model collision comes out in model theme library
It is exported according to selection, data screening and data.
Preferably, different business domains mutually quote the model of publication, respective data are generated according to the rule of model,
Form the reference of reticular structure.
Compared with prior art, tax data crash analysis method of the invention has following prominent the utility model has the advantages that institute
State tax data crash analysis method provide under the background of data centralization, make full use of each business domains data carry out across
The analysis of business domains, analytic process realized using pulling, and in time, business personnel can be by according to demand for flexibly simple and feedback
Data warehouse carries out confluence analysis, data required for collision obtains to data from multiple business domains, and model support shares machine
System has good application value.
Detailed description of the invention
Fig. 1 is the data collision schematic diagram in tax data crash analysis method of the present invention；
Fig. 2 is the flow chart of the data modeling of tax data crash analysis method of the present invention.
Specific embodiment
Below in conjunction with drawings and examples, tax data crash analysis method of the invention is made further specifically
It is bright.
Embodiment
Tax data crash analysis method of the invention is based on data warehouse, realizes different business by custom rule
Data collision, the data needed, wherein front end is pulled and Jsplumb line-connecting machine using Jquery, and user is by data warehouse
In table be dragged in design area, data needed for the different data of line obtain.
As shown in Figure 1, this method includes data modeling, model theme library, model publication and modeling statistics.Data modeling mistake
It include that model introduces, the addition of table node, incidence relation adds, data preview and model execute in journey, model theme library includes upper
Grade model data is checked, the inquiry of the same level model data, data select, data screening and data export, model publication include data
Distribute verifying, recommendation from bottom to top, it is top-down check, the reference from sharing at the same level and reticular structure, model system
Meter includes modeling situation statistics, log situation analysis, implementing result is checked, operating condition is checked and model service condition.
As shown in Fig. 2, data modeling process will impose data and risk data, is screened, converted, got rid of and do not meet
It is required that or invalid data, obtain that treated and impose, risk data, will treated imposes, risk data is associated, obtain
The collection of collision, risk data.But the collection of obtained collision, risk data may be because left and right association or other behaviour
Make, there are some improper datas, then screened to crash data, conversion process.Data from internet are screened,
Conversion, the internet data that obtains that treated are associated with the crash data after screening, conversion process, convert, obtain required data.
In the present invention, there are two types of modes for data modeling, the first is to introduce issued model.It is looked into according to business division
Required Issuance model is ask, and model information is introduced as own use.
Second is model required for dragging foundation.In the data modeling stage, first by the tables of data in data warehouse,
Classify to form statement of assets tree according to business domains, statement of assets tree is divided into modelling area and the data preview of lower part on top
Area.Modelling area is designed the data in data warehouse, and data preview area counts each table node in design area
According to preview.The following tables of data of statement of assets tree is pinned, tables of data is dragged into modelling area using Jquery technology and is formed
Table node, binodal table node can carry out relevant operation to tables of data, the type including selecting tables of data, the type detail of table
Table and summary sheet, detail list directly use the detailed data of table, and summary sheet can carry out polymerization according to the field of selection and summarize, can
To add screening conditions, the data in tables of data are screened, filter out the data of needs.It can between two tables of data nodes
To use Jsplumb line-connecting machine to be associated tables of data, the data correlation relation of six seed types, including interior company are supported at present
Connect, it is left connection, it is right connection, left bank remove, it is right exclude, duplicate removal merge.Two tables of data can generate a new interim table, this is interim
Table comes from two tables of data, obtains relevant tax data by collision by two tables of data.Choose the interim table can be with preview
The related data of the table is adjusted data model according to preview data.It can continue to be dragged in tables of data and currently interim
Table carries out line, further hits against out relevant tax data.It can be saved in specified data table by colliding obtained data,
It is put under the related subject of statement of assets tree processing district, the analysis of data further progress can be used, can use scheduling, be arranged
Data renewal frequency, periodic refreshing set objectives the data of table.
After the completion of data modeling, to the data query established model and collide out in model theme library.According to theme
Inquiry inquires the data model issued under different industries theme, different data models is introduced, and completes data modeling rank
The model of section introduces step.The data of model collision can also be checked in model theme library.It can according to need, it will
The related data of data model exports to Exccel.
Different business domain can mutually quote the data model of publication, generate respective number according to the rule of data model
According to forming the reference of reticular structure.Individual, which can log in, checks that respective model executes the time, executes frequency, realizes that data are fixed
Shi Gengxin.
Embodiment described above, the only present invention more preferably specific embodiment, those skilled in the art is at this
The usual variations and alternatives carried out within the scope of inventive technique scheme should be all included within the scope of the present invention.
Claims (10)
1. a kind of tax data crash analysis method, it is characterised in that: this method is based on data warehouse, passes through custom rule reality
Existing different business data collision, the data needed, wherein front end is pulled and Jsplumb line-connecting machine, user using Jquery
Table in data warehouse is dragged in design area, data needed for the different data of line obtain.
2. tax data crash analysis method according to claim 1, it is characterised in that: this method include data modeling,
Model theme library, model publication and modeling statistics, data modeling include that model introduces, table node adds, incidence relation in the process
Addition, data preview and model execute, and model theme library includes that upper level model data are checked, the same level model data is inquired, data
Selection, data screening and data export, model publication include that data distribute verifying, recommendation from bottom to top, top-down look into
It sees, the reference from sharing at the same level and reticular structure, modeling statistics includes modeling situation statistics, log situation analysis, executes
As a result it checks, operating condition is checked and model service condition.
3. tax data crash analysis method according to claim 2, it is characterised in that: the data modeling process will not
With business domains data with from treated for internet, data are associated collision, obtain required data.
4. tax data crash analysis method according to claim 3, it is characterised in that: data modeling process specifically includes
Following steps:
S1: the data screening in different business domain converts to obtain treated business numeric field data；
S2: by treated, business datum is associated with to obtain crash data；
S3: crash data is screened, converts to obtain processing data；
S4: internet data screened, converts to obtain treated internet data；
S5: treated, and internet data is converted to obtain required data with processing data correlation.
5. tax data crash analysis method according to claim 4, it is characterised in that: during data modeling, first
Table in data warehouse is classified to form statement of assets tree according to business domains, statement of assets tree main body is divided into the modelling on top
The browsing data area in area and lower part is designed the data in data warehouse in modelling area, in browsing data area to mould
Each table node that type designs area carries out data preview.
6. tax data crash analysis method according to claim 5, it is characterised in that: it is following to pin statement of assets tree
Tables of data is dragged to modelling area formation table node using Jquery technology by table, binodal tables of data node, to tables of data into
Row operation, including selecting the type of tables of data, the type detail list and summary sheet of tables of data.
7. tax data crash analysis method according to claim 6, it is characterised in that: used between two table nodes
Jsplumb line-connecting machine is associated tables of data, and data correlation relation includes that interior connection, left connection, right connection, left bank go out, are right
Discharge and duplicate removal merge.
8. tax data crash analysis method according to claim 7, it is characterised in that: two tables of data associations generate and face
When tables of data, relevant tax data are obtained by the collision of two tables of data, continues to be dragged in tables of data and current temporary data table connects
Line collides out relevant tax data.
9. tax data crash analysis method according to claim 8, it is characterised in that: after the completion of data modeling, in mould
In type theme library to establish the data query that model collision comes out, data selection, data screening and data export.
10. tax data crash analysis method according to claim 9, it is characterised in that: different business domains are mutually drawn
With the model of publication, respective data are generated according to the rule of model, form the reference of reticular structure.
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| CN201810738338.5A CN108959578A (en) | 2018-07-06 | 2018-07-06 | A kind of tax data crash analysis method |
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| CN201810738338.5A CN108959578A (en) | 2018-07-06 | 2018-07-06 | A kind of tax data crash analysis method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111488269A (en) * | 2019-01-29 | 2020-08-04 | 阿里巴巴集团控股有限公司 | Index detection method, device and system for data warehouse |
| CN113206759A (en) * | 2021-04-27 | 2021-08-03 | 北京赛博云睿智能科技有限公司 | Management method and system of intelligent PaaS service platform across different service domains |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106788999A (en) * | 2016-12-09 | 2017-05-31 | 武汉中软通证信息技术有限公司 | A kind of wechat evidence collecting method and system based on data collision |
-
2018
- 2018-07-06 CN CN201810738338.5A patent/CN108959578A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106788999A (en) * | 2016-12-09 | 2017-05-31 | 武汉中软通证信息技术有限公司 | A kind of wechat evidence collecting method and system based on data collision |
Non-Patent Citations (2)
| Title |
|---|
| YSX_小鱼: "利用jQuery-UI和jsPlumb实现拖拽连接模型", 《HTTPS://WWW.CNBLOGS.COM/YSX215/P/7426529.HTML》 * |
| 王艳 等: "基于HDFS和IMPALA的碰撞比对分析", 《电视技术》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111488269A (en) * | 2019-01-29 | 2020-08-04 | 阿里巴巴集团控股有限公司 | Index detection method, device and system for data warehouse |
| CN111488269B (en) * | 2019-01-29 | 2023-11-14 | 阿里巴巴集团控股有限公司 | Index detection method, device and system for data warehouse |
| CN113206759A (en) * | 2021-04-27 | 2021-08-03 | 北京赛博云睿智能科技有限公司 | Management method and system of intelligent PaaS service platform across different service domains |
| CN113206759B (en) * | 2021-04-27 | 2022-10-14 | 北京赛博云睿智能科技有限公司 | Management method and system of intelligent PaaS service platform across different service domains |
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