CN112800046A - Artificial intelligence platform applied to field data management - Google Patents
Artificial intelligence platform applied to field data management Download PDFInfo
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- CN112800046A CN112800046A CN202110217401.2A CN202110217401A CN112800046A CN 112800046 A CN112800046 A CN 112800046A CN 202110217401 A CN202110217401 A CN 202110217401A CN 112800046 A CN112800046 A CN 112800046A
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- 238000013523 data management Methods 0.000 title claims abstract description 17
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 16
- 238000007726 management method Methods 0.000 claims abstract description 21
- 238000013499 data model Methods 0.000 claims description 19
- 230000003287 optical effect Effects 0.000 claims description 3
- 239000013589 supplement Substances 0.000 claims description 2
- 238000006243 chemical reaction Methods 0.000 abstract description 7
- 230000009286 beneficial effect Effects 0.000 abstract description 4
- 230000003993 interaction Effects 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 9
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- 230000008520 organization Effects 0.000 description 4
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
- G06F2216/03—Data mining
Abstract
This patent relates to the field of computers. The artificial intelligence platform applied to field data management comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring original input data from a user side; the data management module is used for managing the original input data according to the data standard and the management standard to generate a management result; and the data standard module is used for storing data standards and governing specifications. The data standard includes data format, encoding rule, dictionary value, and the like. The good data standard is beneficial to sharing, interaction and application of data, and the work of data conversion between different systems can be reduced.
Description
Technical Field
The invention relates to the field of computers, in particular to a data processing platform.
Background
With the continuous maturity of big data related technologies, data is regarded as an asset and is valued by more and more enterprise organizations, and in order to effectively utilize the data asset, data governance becomes a problem of important attention of enterprises. By treating the enterprise data, the consistency and the accuracy of the enterprise data can be improved, so that the quality of the enterprise data is improved, and business decisions can be made by an enterprise decision layer.
Disclosure of Invention
The invention aims to provide an artificial intelligence platform applied to field data management so as to improve the consistency and accuracy of enterprise data.
The technical problem solved by the invention can be realized by adopting the following technical scheme:
the artificial intelligence platform is applied to field data management and is characterized by comprising a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring original input data from a user side; the data management module is used for managing the original input data according to the data standard and the management standard to generate a management result; and the data standard module is used for storing data standards and governing specifications.
In the process of data governance, finding the relationship among the mining data is particularly important. And for the databases of the same data source, judging the relation among the database tables according to the initial design document, the E-R graph, the foreign key and the like. For databases of different data sources, the similarity is used to assist data governors in judging the relationship between data by means of an algorithm. The similarity judgment has a plurality of dimensions, and each dimension can be endowed with a certain weight according to the actual situation. Common dimensions are similarity of metadata itself, such as metadata name, data type, data length, etc.; in addition, the similarity of the actual data represented by the metadata is judged; or the dimension of the incidence relation of the data source; through the calculation of the similarity, the data relation between different data can be judged globally, and therefore data carding personnel can be assisted to judge the association relation between metadata quickly.
The data standard includes data format, encoding rule, dictionary value, and the like. The good data standard is beneficial to sharing, interaction and application of data, and the work of data conversion between different systems can be reduced.
The abatement specifications include a data model. The data model is an important part in data management, is a proper, reasonable and compliant data model, can effectively improve the reasonable distribution and use of data, and is a key and key point of data management. The data model comprises three parts, namely a data structure, data operation and data constraint. The data structure is mainly used for describing the type, content, property, relation and the like of data. The data structure is the basis of the data model, and data operations and data constraints are basically established on the data structure. Different data structures have different operations and constraints. And (4) data operation. Data operations in the data model are primarily used to describe the type and manner of operation on the corresponding data structure. And (4) data constraint. The data constraints in the data model are mainly used for describing grammars, word sense connections, constraints and dependency relationships among data in the data structure and dynamically changing rules of the data so as to ensure the correctness, effectiveness and compatibility of the data.
The governance specification also includes metadata management. Metadata is divided into business metadata, technical metadata, and operational metadata. The service metadata guides the technical metadata, the technical metadata is designed by taking the service metadata as a reference, and the operation metadata provides support for the management of the service metadata and the technical metadata. And the service metadata is used for assisting in positioning, understanding and accessing information. The scope of the service metadata mainly includes: business indicators, business rules, data quality rules, terminology, data standards, conceptual data models, entities/attributes, logical data models, and the like. The technical metadata is divided into structural technical metadata and associative technical metadata. Structural technology metadata provides a description of data in the infrastructure of information technology, such as the location of data, the type of data stored, the relationship of the blood-based data, etc. The association technology metadata describes the association between data and the flow of data through the information technology environment. The scope of technical metadata mainly includes: technical rules (calculation/statistics/conversion/summary), data quality rules technical description, fields, derived fields, facts/dimensions, statistical indicators, tables/views/files/interfaces, reports/multidimensional analysis, databases/view groups/file groups/interface groups, source code/programs, systems, software, hardware, etc. Technical metadata is typically designed with existing business metadata as a reference. Operation metadata refers to the operation data generated by the organization, stations, responsibilities, processes, and system daily operations related to metadata management. The content of the operation metadata management mainly comprises the following steps: the organization, the post, the responsibility, the flow, the project, the version related to the metadata management, and the operation record in the production running of the system, such as the running record, the application program and the running job.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained below.
The artificial intelligence platform applied to field data management comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring original input data from a user side; the data management module is used for managing the original input data according to the data standard and the management standard to generate a management result; and the data standard module is used for storing data standards and governing specifications.
In the process of data governance, finding the relationship among the mining data is particularly important. And for the databases of the same data source, judging the relation among the database tables according to the initial design document, the E-R graph, the foreign key and the like. For databases of different data sources, the similarity is used to assist data governors in judging the relationship between data by means of an algorithm. The similarity judgment has a plurality of dimensions, and each dimension can be endowed with a certain weight according to the actual situation. Common dimensions are similarity of metadata itself, such as metadata name, data type, data length, etc.; in addition, the similarity of the actual data represented by the metadata is judged; or the dimension of the incidence relation of the data source; through the calculation of the similarity, the data relation between different data can be judged globally, and therefore data carding personnel can be assisted to judge the association relation between metadata quickly.
The data standard includes data format, encoding rule, dictionary value, and the like. The good data standard is beneficial to sharing, interaction and application of data, and the work of data conversion between different systems can be reduced.
The abatement specifications include a data model. The data model is an important part in data management, is a proper, reasonable and compliant data model, can effectively improve the reasonable distribution and use of data, and is a key and key point of data management. The data model comprises three parts, namely a data structure, data operation and data constraint. The data structure is mainly used for describing the type, content, property, relation and the like of data. The data structure is the basis of the data model, and data operations and data constraints are basically established on the data structure. Different data structures have different operations and constraints. And (4) data operation. Data operations in the data model are primarily used to describe the type and manner of operation on the corresponding data structure. And (4) data constraint. The data constraints in the data model are mainly used for describing grammars, word sense connections, constraints and dependency relationships among data in the data structure and dynamically changing rules of the data so as to ensure the correctness, effectiveness and compatibility of the data. The governance specification also includes metadata management. Metadata is divided into business metadata, technical metadata, and operational metadata. The service metadata guides the technical metadata, the technical metadata is designed by taking the service metadata as a reference, and the operation metadata provides support for the management of the service metadata and the technical metadata. And the service metadata is used for assisting in positioning, understanding and accessing information. The scope of the service metadata mainly includes: business indicators, business rules, data quality rules, terminology, data standards, conceptual data models, entities/attributes, logical data models, and the like. The technical metadata is divided into structural technical metadata and associative technical metadata. Structural technology metadata provides a description of data in the infrastructure of information technology, such as the location of data, the type of data stored, the relationship of the blood-based data, etc. The association technology metadata describes the association between data and the flow of data through the information technology environment. The scope of technical metadata mainly includes: technical rules (calculation/statistics/conversion/summary), data quality rules technical description, fields, derived fields, facts/dimensions, statistical indicators, tables/views/files/interfaces, reports/multidimensional analysis, databases/view groups/file groups/interface groups, source code/programs, systems, software, hardware, etc. Technical metadata is typically designed with existing business metadata as a reference. Operation metadata refers to the operation data generated by the organization, stations, responsibilities, processes, and system daily operations related to metadata management. The content of the operation metadata management mainly comprises the following steps: the organization, the post, the responsibility, the flow, the project, the version related to the metadata management, and the operation record in the production running of the system, such as the running record, the application program and the running job.
The data acquisition module can be a keyboard, a mouse, a camera and the like.
Preferably, a fingerprint acquisition module is integrated on the mouse. This patent has add the fingerprint collection module on mouse, utilizes fingerprint collection module can gather user's fingerprint to information such as the authority that the discernment user is who, user. Mouse includes the shell, and the left side of shell is equipped with the left button, and the right side of shell is equipped with the right button, and the centre of left button and right button is equipped with the gyro wheel, and fingerprint collection module's fingerprint collection unit is located the place ahead of gyro wheel. This patent has been injectd the position of fingerprint collection unit, and on the one hand, the user need not to change the use custom of current mouse, and on the other hand, the user can not cause interference and influence to fingerprint collection module when using mouse alone. More crucial is, both combine the back together, can realize the quick collection of fingerprint, and people roll the gyro wheel of mouse with the forefinger moreover usually, set up the place ahead at the gyro wheel with fingerprint collection module, when the fingerprint need gather, the displacement of finger is minimum, and because of the forefinger more abundant with the contact of fingerprint collection module, therefore data are more accurate. The fingerprint collection module can be an optical fingerprint collection module, a thermosensitive sensor fingerprint collection module and a biological radio frequency fingerprint collection module. Preferably, the fingerprint acquisition module based on optics comprises a signal processing unit, the signal processing unit is connected with a camera, and the signal processing unit is further connected with a light supplement lamp. The front of the roller is provided with a window which penetrates through the inside and the outside, the window is covered with an infrared filter, the camera is positioned below the infrared filter, a gap exists between the camera and the infrared filter, and the camera and the infrared filter are used as fingerprint acquisition units. The infrared filter is preferably a thin middle infrared filter with two thick sides. On the one hand, the center of indent can be utilized to effectively guide the finger, and on the other hand, the structure of concave mirror type can effectively improve the light path. The camera can be located under the infrared filter, and the camera lens of camera is outwards. Or a reflector inclined at an angle of 30-60 degrees is arranged right below the infrared filter, and the lens of the camera faces the reflector. Preferably, the camera is located the foremost end of shell, and more backward tilt up more, and the reflector panel is located infrared filter's under the rear, and the rear of reflector panel is the gyro wheel. The reflector plate can not only reflect light, but also isolate the roller. The inclined reflector not only can enable the lens to capture fingerprints more clearly, but also saves space for the roller, and finally the whole volume of the equipment is not too large. The light filling lamp is an LED lamp strip, and lamp beads on the LED lamp strip are embedded into the infrared filter. On the one hand, can carry out the light filling to the camera when gathering the fingerprint, on the other hand can play the effect that the mouse was decorated with. This patent can avoid the aversion of LED lamp area and infrared filter in installation and use with lamp pearl embedding infrared filter in, makes the light path more stable. In addition, the lamp beads embedded into the infrared filter play a role in fixing the lamp strip, and the fixing requirements on the lamp strip can be reduced. Preferably the light strip is glued to the infrared filter by means of glue. Can establish the recess that the opening is outwards on infrared filter's outer terminal surface, lamp pearl intercommunication lamp area imbeds in the recess together. At the moment, the structure with the thin middle part and the thick two sides of the infrared filter can provide larger area for the groove of the groove. The lamp strip is preferably arranged around the infrared filter and at least surrounds three fourths of the infrared filter. Besides the beneficial effects mentioned above, because the lamp area has certain elasticity, encircle the lamp area that sets up, can also play the effect of certain shock attenuation and buffering, can effectively avoid infrared filter striking camera, cause the camera to damage. The mouse comprises a shell, a circuit board is arranged in the shell, a signal processing unit is fixed on the circuit board, a first signal line used for outputting mouse signals is connected to the circuit board, a second signal line used for outputting signals of a fingerprint acquisition module is connected to the signal processing unit, and a USB connector is arranged at each of the tail ends of the first signal line and the second signal line. The first signal line and the second signal line are preferably twisted. The twisted connection mode is favorable for ensuring the bending resistance and the tensile resistance of the circuit and is also favorable for releasing the heat expansion and cold contraction energy. In order to distinguish the two signal lines, the outer surfaces of the first signal line and the second signal line are different in color. The colors of the outer surfaces of the two USB connectors are different, or distinguishing marks or signs are engraved on the outer surfaces of the two USB connectors. Therefore, the mouse signal and the fingerprint signal are respectively output, the processing difficulty of data is reduced, and meanwhile, the safety and the normalization of the data are guaranteed. The touch sensing switch is arranged in front of the infrared filter and connected between the signal processing unit and the power supply, so that the touch sensing switch is used for controlling the opening and closing of the whole signal processing unit, the camera and the light supplementing lamp, and the energy consumption is reduced. The power supply can be an independent power supply, and the signal processing unit can be connected with the electric energy input module on the circuit board to obtain electric energy from the circuit board.
For the unit with thinner authority division such as bank and thinner document security classification, when in use, different input devices can be used for identity recognition with different authorities. For example, users with high level authority are identified by iris plus fingerprint, and users with low level authority are identified by fingerprint.
The governing standard also comprises authority management, wherein the authority management comprises the classification of authority, level and data processing standard. The data management module identifies the identity of the user according to the acquired fingerprint information, then judges the level of the user according to the identity of the user, matches the authority of the user according to the level of the user, and controls the issued data content, the storage position of the uploaded data content and the data standard of the uploaded data content according to the authority of the user. The data standard here includes a security level, processing time, data format, and the like. Preferably, the data formats and encoding rules of the data belonging to the same authority level are consistent. And when the data format and the coding rule of the input original data are inconsistent, the data management module carries out format conversion. For example, when the data obtained by the keyboard and the data obtained by the camera are input by a user with the same authority level, data conversion is performed to make the data format and the coding rule consistent. The patent creatively associates the data format and the coding rule with the authority level, is favorable for data unification, and is more critical to conveniently carry out interaction and encryption processing on the data under the same authority level.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The artificial intelligence platform is applied to field data management and is characterized by comprising a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring original input data from a user side; the data management module is used for managing the original input data according to the data standard and the management standard to generate a management result; and the data standard module is used for storing data standards and governing specifications.
2. The artificial intelligence platform applied to field data governance according to claim 2, wherein the data standards comprise data formats and encoding rules.
3. The artificial intelligence platform for application in field data governance according to claim 1, wherein governance specifications comprise data models comprising data structures, data operations, data constraints.
4. The artificial intelligence platform for application in field data governance according to claim 3, wherein governance specifications further include metadata management, metadata divided into business metadata, technical metadata and operational metadata.
5. The artificial intelligence platform applied to field data governance according to claim 1, wherein the data acquisition module is a keyboard, a mouse, a fingerprint acquisition module, or a camera.
6. The artificial intelligence platform applied to field data governance according to claim 5, wherein a fingerprint acquisition module is integrated on the mouse.
7. The artificial intelligence platform applied to field data governance according to claim 6, wherein the mouse comprises a housing, a left button is arranged on the left side of the housing, a right button is arranged on the right side of the housing, a roller is arranged between the left button and the right button, and the fingerprint acquisition unit of the fingerprint acquisition module is positioned in front of the roller.
8. The artificial intelligence platform applied to field data governance according to claim 7, wherein the fingerprint collection module is an optical-based fingerprint collection module, the optical-based fingerprint collection module comprises a signal processing unit, the signal processing unit is connected with a camera, and the signal processing unit is further connected with a light supplement lamp.
9. The artificial intelligence platform applied to field data governance according to claim 8, wherein a window is opened in front of the roller, the window is covered by an infrared filter, the camera is positioned below the infrared filter, a gap is formed between the camera and the infrared filter, and the camera and the infrared filter are used as fingerprint acquisition units.
10. The artificial intelligence platform applied to field data governance according to claim 7, wherein a circuit board is disposed in the housing, the signal processing unit of the fingerprint acquisition module is fixed on the circuit board, a first signal line for outputting mouse signals is connected to the circuit board, a second signal line for outputting signals of the fingerprint acquisition module is connected to the signal processing unit, and a USB connector is disposed at each of the ends of the first signal line and the second signal line.
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| CN202110217401.2A CN112800046A (en) | 2021-02-26 | 2021-02-26 | Artificial intelligence platform applied to field data management |
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