CN108509599B - Data model creating method and device - Google Patents
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Abstract
The application discloses a method and a device for creating a data model, which are used for respectively acquiring information of each data item in each preset field; respectively establishing a mapping relation between each data item in each preset field and an entity class in a preset standard model, and establishing a data sub-model of each preset field according to the mapping relation and each data item information in each preset field; and respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model. The problem of fragmentation of the existing data model is solved, and the phenomenon of information isolated island in the information construction process is avoided.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and an apparatus for creating a data model.
Background
In the past data warehouse BI project, data model methodology and concepts usually surround how to design and build a data warehouse, while application system (OLTP system) model design lacks guidance of the methodology, and in addition, each application system is usually designed and developed by different manufacturers at different periods, and lacks communication among the application systems, so that data dispersion and repetition, caliber inconsistency and data compatibility are poor. Because the data warehouse belongs to a downstream system in the enterprise overall information planning, the data warehouse can only passively receive the data generated by each application system, and after the data is put into a warehouse, the data integration is greatly difficult due to inconsistent calibers and poor compatibility. The enterprise still has a large amount of 'information isolated islands' phenomenon when a large amount of manpower, material resources and funds are invested to promote informatization construction.
Disclosure of Invention
In view of this, the invention provides a method and a device for creating a data model, which solve the fragmentation problem of the existing data model and avoid the phenomenon of information isolated island in the informatization construction process.
In order to achieve the above purpose, the invention provides the following specific technical scheme:
a method of creating a data model, comprising:
respectively acquiring information of each data item in each preset field;
respectively establishing a mapping relation between each data item in each preset field and an entity class in a preset standard model, and establishing a data sub-model of each preset field according to the mapping relation and each data item information in each preset field;
and respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model.
Preferably, the data item information includes basic information, main data information, service information and interaction information;
the respectively obtaining of each data item information in each preset field includes:
extracting a plurality of data items in each preset field according to the data dictionary of each preset field, and acquiring basic information and main data information of each data item;
respectively acquiring the business process information of each preset field, and respectively establishing a mapping relation among the business process, business links and data items in the corresponding preset field according to the business process information of each preset field so as to acquire the business information of each data item;
and respectively determining whether each data item in each preset field is a field generated data item, and determining the data source of each data item, thereby acquiring the interaction information of each data item.
Preferably, the acquiring the basic information and the main data information of each data item includes:
performing duplicate removal processing on each data item in each preset field respectively to obtain a data item with uniqueness;
extracting basic information of each data item with uniqueness according to a data dictionary of each preset field, wherein the basic information comprises a table name, a table description, a field name, a field description, a field type, primary key information and foreign key information;
and judging whether each data item with uniqueness is main data according to the characteristics of the main data, thereby obtaining the main data information of each data item with uniqueness.
Preferably, the creating a data sub-model of each preset domain according to the mapping relationship and each data item information in each preset domain includes:
judging whether a data item which cannot establish a mapping relation exists;
if so, determining the data item which cannot establish the mapping relation as a model expansion demand point;
adding the model expansion demand points into a preset standard model as a newly added entity class according to the main body domain to which the model expansion demand points belong;
obtaining a data sub-model of each preset field according to the mapping relation and the data item information in each preset field;
if not, directly obtaining the data sub-model of each preset field according to the mapping relation and the data item information in each preset field.
Preferably, the integrating the data sub-models of each preset domain according to the cross-domain data item to obtain the target data model includes:
respectively connecting the preset fields in which each cross-domain data item is positioned through the cross-domain data items;
carrying out data item duplicate removal processing on the data model obtained after connection to obtain a target data model;
and carrying out graphical processing on the target data model to obtain a target data model diagram comprising a plurality of data items and association between each data item.
An apparatus for creating a data model, comprising:
the data item information acquisition unit is used for respectively acquiring each data item information in each preset field;
the mapping relation establishing unit is used for respectively establishing the mapping relation between each data item in each preset field and the entity class in the preset standard model, and obtaining the data sub-model of each preset field according to the mapping relation and the information of each data item in each preset field;
and the sub-model integration unit is used for respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain the target data model.
Preferably, the data item information includes basic information, main data information, service information and interaction information;
the data item information acquisition unit includes:
the first acquisition subunit is used for extracting a plurality of data items in each preset field according to the data dictionary of each preset field, and acquiring basic information and main data information of each data item;
the second acquiring subunit is used for respectively acquiring the service process information of each preset field, and respectively establishing a mapping relation among the service process, the service link and the data item in the corresponding preset field according to the service process information of each preset field, so as to acquire the service information of each data item;
and the third acquiring subunit is used for respectively determining whether each data item in each preset field is a field-generated data item and determining the data source of each data item, so as to acquire the interaction information of each data item.
Preferably, the first acquiring subunit includes:
the first duplicate removal processing subunit is used for respectively carrying out duplicate removal processing on each data item in each preset field to obtain a data item with uniqueness;
the extraction subunit is used for extracting basic information of each data item with uniqueness according to the data dictionary of each preset field, wherein the basic information comprises a table name, a table description, a field name, a field description, a field type, primary key information and foreign key information;
and the first judging subunit is used for judging whether each data item with uniqueness is main data according to the characteristics of the main data so as to obtain the main data information of each data item with uniqueness.
Preferably, the mapping relationship establishing unit includes:
the second judgment subunit is used for judging whether a data item which cannot establish a mapping relation exists or not; if yes, triggering the determining subunit, and if not, triggering the creating subunit;
the determining subunit is configured to determine, as a model expansion demand point, a data item for which a mapping relationship cannot be established;
the adding subunit is used for adding the model expansion demand points into a preset standard model as new entity classes according to the main body domain to which the model expansion demand points belong;
and the creating subunit is used for creating a data submodel of each preset field according to the mapping relation and the data item information in each preset field.
Preferably, the sub-model integration unit includes:
the connection subunit is used for respectively connecting the preset fields in which each cross-domain data item is positioned through the cross-domain data items;
the second duplicate removal processing subunit is used for carrying out data item duplicate removal processing on the data model obtained after connection to obtain a target data model;
and the graphical processing subunit is used for carrying out graphical processing on the target data model to obtain a target data model diagram comprising a plurality of data items and the association between each data item.
Compared with the prior art, the invention has the following beneficial effects:
according to the data model creating method and device, after the information of each data item in each preset field is obtained, the mapping relation between each data item in each preset field and the entity class in the preset standard model is established, so that each data item conforms to the preset standard model, and the data normalization and compatibility are improved. Meanwhile, a data sub-model of each preset field is created according to the mapping relation and the data item information in each preset field; and respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model. The cross-domain data are integrated together to form an integrated data model fused with each other in each business field, the fragmentation problem of the existing data model is solved, and the information isolated island phenomenon in the information construction process is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method for creating a data model according to the present invention;
FIG. 2 is a flow chart of another method for creating a data model disclosed herein;
FIG. 3 is a schematic diagram of data item information disclosed in the present invention;
fig. 4 is a schematic structural diagram of a data model creation device disclosed in the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present embodiment discloses a method for creating a data model, which specifically includes the following steps:
s101: respectively acquiring information of each data item in each preset field;
specifically, the preset fields are business fields which are divided in advance according to data sources, such as personnel organization, finance, materials, projects, power grids, assets and customers.
Specifically, the data item information includes basic information, main data information, service information and interaction information; on this basis, referring to fig. 2, the specific implementation process of S101 is as follows:
s201: extracting a plurality of data items in each preset field according to the data dictionary of each preset field, and acquiring basic information and main data information of each data item;
performing duplicate removal processing on each data item in each preset field respectively to obtain a data item with uniqueness;
extracting basic information of each data item with uniqueness according to a data dictionary of each preset field, wherein the basic information comprises a table name, a table description, a field name, a field description, a field type, primary key information and foreign key information; please refer to the basic information portion of the data item in fig. 3;
and judging whether each data item with uniqueness is main data according to the characteristics of the main data, thereby obtaining the main data information of each data item with uniqueness. Please refer to the main data information part in fig. 3.
Master Data (MD Master Data) is Data that is shared among computer systems.
S202: respectively acquiring the business process information of each preset field, and respectively establishing a mapping relation among the business process, business links and data items in the corresponding preset field according to the business process information of each preset field so as to acquire the business information of each data item; please refer to the service information part in fig. 3.
The service information of the data item comprises a service process and a service link to which the data item belongs.
S203: and respectively determining whether each data item in each preset field is a field generated data item, and determining the data source of each data item, thereby acquiring the interaction information of each data item. Please refer to the interactive information part of fig. 3.
Wherein the data source is a business system for data item generation.
S102: respectively establishing a mapping relation between each data item in each preset field and an entity class in a preset standard model, and establishing a data sub-model of each preset field according to the mapping relation and each data item information in each preset field;
the preset standard model is an enterprise information model (SG-CIM2.0) and an IEC recent standard (IEC61968V12/61970V 17).
When the data item can not correspond to any entity class in the preset standard model, the data item which can not establish the mapping relation exists.
Specifically, judging whether a data item which cannot establish a mapping relation exists;
if so, determining the data item which cannot establish the mapping relation as a model expansion demand point;
adding the model expansion demand points into a preset standard model as a newly added entity class according to the main body domain to which the model expansion demand points belong;
obtaining a data sub-model of each preset field according to the mapping relation and the data item information in each preset field;
if not, directly obtaining the data sub-model of each preset field according to the mapping relation and the data item information in each preset field.
Adding the model expansion demand point as a newly added entity class into a preset standard model according to the following principles:
1. the IEC or SG-CIM2.0 is covered, and the IEC or SG-CIM2.0 standard model is directly quoted;
2. the IEC or SG-CIM2.0 is not completely covered, and the attribute of the model is expanded and perfected according to the model design specification;
3. aiming at the situation that IEC or SG-CIM2.0 is not covered, a model entity is newly added according to the design idea of SG-CIM;
4. and (4) direct reference, namely directly referencing the class, the attribute and the relation in the CIM without changing the name and the structure in the CIM.
5. Inheritance, deriving from service classes in CIM, forming new classes, and defining attributes and relations in the new classes. For example, the "EuqTrsiLine" class is an SG-CIM extended class that inherits from the "Line" class referenced by SG-CIM in CIM.
6. And weak correlation extension, wherein the classes related to the technical mechanism, such as IdentifiedObject and Document of the CIM, are inherited because no applicable class in the CIM can be supported. For example, the "HrOrganiationInfo" class is a "Document" class that is inherited to the SG-CIM self-CIM.
S103: and respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model.
Respectively connecting the preset fields in which each cross-domain data item is positioned through the cross-domain data items;
carrying out data item duplicate removal processing on the data model obtained after connection to obtain a target data model;
and carrying out graphical processing on the target data model to obtain a target data model diagram comprising a plurality of data items and association between each data item.
In the method for creating a data model disclosed in this embodiment, after information of each data item in each preset field is obtained, a mapping relationship between each data item in each preset field and an entity class in a preset standard model is established, so that each data item conforms to the preset standard model, and data normalization and compatibility are improved. Meanwhile, a data sub-model of each preset field is created according to the mapping relation and the data item information in each preset field; and respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model. The cross-domain data are integrated together to form an integrated data model fused with each other in each business field, the fragmentation problem of the existing data model is solved, and the information isolated island phenomenon in the information construction process is avoided.
Referring to fig. 4, the present embodiment discloses a data model creating device based on the method for creating a data model disclosed in the above embodiments, including:
a data item information obtaining unit 401, configured to obtain each data item information in each preset domain respectively;
a mapping relationship establishing unit 402, configured to respectively establish a mapping relationship between each data item in each preset field and an entity class in a preset standard model, and obtain a data sub-model of each preset field according to the mapping relationship and information of each data item in each preset field;
the submodel integration unit 403 is configured to determine whether each data item in each preset domain is a cross-domain data item, and integrate the data submodels of each preset domain according to the cross-domain data item to obtain a target data model.
Preferably, the data item information includes basic information, main data information, service information and interaction information;
the data item information acquisition unit includes:
the first acquisition subunit is used for extracting a plurality of data items in each preset field according to the data dictionary of each preset field, and acquiring basic information and main data information of each data item;
the second acquiring subunit is used for respectively acquiring the service process information of each preset field, and respectively establishing a mapping relation among the service process, the service link and the data item in the corresponding preset field according to the service process information of each preset field, so as to acquire the service information of each data item;
and the third acquiring subunit is used for respectively determining whether each data item in each preset field is a field-generated data item and determining the data source of each data item, so as to acquire the interaction information of each data item.
Preferably, the first acquiring subunit includes:
the first duplicate removal processing subunit is used for respectively carrying out duplicate removal processing on each data item in each preset field to obtain a data item with uniqueness;
the extraction subunit is used for extracting basic information of each data item with uniqueness according to the data dictionary of each preset field, wherein the basic information comprises a table name, a table description, a field name, a field description, a field type, primary key information and foreign key information;
and the first judging subunit is used for judging whether each data item with uniqueness is main data according to the characteristics of the main data so as to obtain the main data information of each data item with uniqueness.
Preferably, the mapping relationship establishing unit includes:
the second judgment subunit is used for judging whether a data item which cannot establish a mapping relation exists or not; if yes, triggering the determining subunit, and if not, triggering the creating subunit;
the determining subunit is configured to determine, as a model expansion demand point, a data item for which a mapping relationship cannot be established;
the adding subunit is used for adding the model expansion demand points into a preset standard model as new entity classes according to the main body domain to which the model expansion demand points belong;
and the creating subunit is used for creating a data submodel of each preset field according to the mapping relation and the data item information in each preset field.
Preferably, the sub-model integration unit includes:
the connection subunit is used for respectively connecting the preset fields in which each cross-domain data item is positioned through the cross-domain data items;
the second duplicate removal processing subunit is used for carrying out data item duplicate removal processing on the data model obtained after connection to obtain a target data model;
and the graphical processing subunit is used for carrying out graphical processing on the target data model to obtain a target data model diagram comprising a plurality of data items and the association between each data item.
In the creating apparatus of a data model disclosed in this embodiment, after information of each data item in each preset field is obtained, a mapping relationship between each data item in each preset field and an entity class in a preset standard model is established, so that each data item conforms to the preset standard model, and data normalization and compatibility are improved. Meanwhile, a data sub-model of each preset field is created according to the mapping relation and the data item information in each preset field; and respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model. The cross-domain data are integrated together to form an integrated data model fused with each other in each business field, the fragmentation problem of the existing data model is solved, and the information isolated island phenomenon in the information construction process is avoided.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method for creating a data model, comprising:
respectively acquiring information of each data item in each preset field;
respectively establishing a mapping relation between each data item in each preset field and an entity class in a preset standard model, and establishing a data sub-model of each preset field according to the mapping relation and each data item information in each preset field;
respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model;
the creating of the data sub-model of each preset field according to the mapping relation and each data item information in each preset field comprises:
judging whether a data item which cannot establish a mapping relation exists;
if so, determining the data item which cannot establish the mapping relation as a model expansion demand point;
adding the model expansion demand points into a preset standard model as a newly added entity class according to the main body domain to which the model expansion demand points belong;
adding the model expansion demand point as a new entity class into a preset standard model, wherein the method comprises the following steps:
the IEC or SG-CIM2.0 is covered, and the IEC or SG-CIM2.0 standard model is directly quoted;
the IEC or SG-CIM2.0 is not completely covered, and the attribute of the model is expanded and perfected according to the model design specification;
aiming at the situation that IEC or SG-CIM2.0 is not covered, a model entity is newly added according to the design idea of SG-CIM;
direct reference: the naming and the structure in the CIM model are not changed, and the class, the attribute and the relation in the CIM are directly referred;
inheritance: deriving from the service class in the CIM to form a new class, and defining attributes and relations in the new class;
weak correlation extension, because no applicable class in CIM can support, inheriting from IdentifiedObject and Document of CIM and class related to technical mechanism;
obtaining a data sub-model of each preset field according to the mapping relation and the data item information in each preset field;
if not, directly obtaining the data sub-model of each preset field according to the mapping relation and the data item information in each preset field.
2. The method of claim 1, wherein the data item information includes basic information, main data information, service information, and interaction information;
the respectively obtaining of each data item information in each preset field includes:
extracting a plurality of data items in each preset field according to the data dictionary of each preset field, and acquiring basic information and main data information of each data item;
respectively acquiring the business process information of each preset field, and respectively establishing a mapping relation among the business process, business links and data items in the corresponding preset field according to the business process information of each preset field so as to acquire the business information of each data item;
and respectively determining whether each data item in each preset field is a field generated data item, and determining the data source of each data item, thereby acquiring the interaction information of each data item.
3. The method of claim 2, wherein the obtaining the basic information and the main data information of each data item comprises:
performing duplicate removal processing on each data item in each preset field respectively to obtain a data item with uniqueness;
extracting basic information of each data item with uniqueness according to a data dictionary of each preset field, wherein the basic information comprises a table name, a table description, a field name, a field description, a field type, primary key information and foreign key information;
and judging whether each data item with uniqueness is main data according to the characteristics of the main data, thereby obtaining the main data information of each data item with uniqueness.
4. The method of claim 1, wherein the integrating the data sub-models of each preset domain according to the cross-domain data items to obtain the target data model comprises:
respectively connecting the preset fields in which each cross-domain data item is positioned through the cross-domain data items;
carrying out data item duplicate removal processing on the data model obtained after connection to obtain a target data model;
and carrying out graphical processing on the target data model to obtain a target data model diagram comprising a plurality of data items and association between each data item.
5. An apparatus for creating a data model, comprising:
the data item information acquisition unit is used for respectively acquiring each data item information in each preset field;
the mapping relation establishing unit is used for respectively establishing the mapping relation between each data item in each preset field and the entity class in the preset standard model, and obtaining the data sub-model of each preset field according to the mapping relation and the information of each data item in each preset field;
the sub-model integration unit is used for respectively determining whether each data item in each preset field is a cross-domain data item, and integrating the data sub-models of each preset field according to the cross-domain data items to obtain a target data model;
the mapping relationship establishing unit includes:
the second judgment subunit is used for judging whether a data item which cannot establish a mapping relation exists or not; if yes, triggering the determining subunit, and if not, triggering the creating subunit;
the determining subunit is configured to determine, as a model expansion demand point, a data item for which a mapping relationship cannot be established;
the adding subunit is used for adding the model expansion demand points into a preset standard model as new entity classes according to the main body domain to which the model expansion demand points belong;
the creating subunit is configured to create a data submodel for each preset domain according to the mapping relationship and each data item information in each preset domain;
the creating of the data sub-model of each preset field according to the mapping relation and each data item information in each preset field comprises:
judging whether a data item which cannot establish a mapping relation exists;
if so, determining the data item which cannot establish the mapping relation as a model expansion demand point;
adding the model expansion demand points into a preset standard model as a newly added entity class according to the main body domain to which the model expansion demand points belong;
adding the model expansion demand point as a new entity class into a preset standard model, wherein the method comprises the following steps:
the IEC or SG-CIM2.0 is covered, and the IEC or SG-CIM2.0 standard model is directly quoted;
the IEC or SG-CIM2.0 is not completely covered, and the attribute of the model is expanded and perfected according to the model design specification;
aiming at the situation that IEC or SG-CIM2.0 is not covered, a model entity is newly added according to the design idea of SG-CIM;
direct reference: the naming and the structure in the CIM model are not changed, and the class, the attribute and the relation in the CIM are directly referred;
inheritance: deriving from the service class in the CIM to form a new class, and defining attributes and relations in the new class;
weak correlation extension, because no applicable class in CIM can support, inheriting from classes related to technical mechanism, such as IdentifiedObject and Document of CIM;
obtaining a data sub-model of each preset field according to the mapping relation and the data item information in each preset field;
if not, directly obtaining the data sub-model of each preset field according to the mapping relation and the data item information in each preset field.
6. The apparatus of claim 5, wherein the data item information comprises basic information, main data information, service information, and interaction information;
the data item information acquisition unit includes:
the first acquisition subunit is used for extracting a plurality of data items in each preset field according to the data dictionary of each preset field, and acquiring basic information and main data information of each data item;
the second acquiring subunit is used for respectively acquiring the service process information of each preset field, and respectively establishing a mapping relation among the service process, the service link and the data item in the corresponding preset field according to the service process information of each preset field, so as to acquire the service information of each data item;
and the third acquiring subunit is used for respectively determining whether each data item in each preset field is a field-generated data item and determining the data source of each data item, so as to acquire the interaction information of each data item.
7. The apparatus of claim 6, wherein the first obtaining subunit comprises:
the first duplicate removal processing subunit is used for respectively carrying out duplicate removal processing on each data item in each preset field to obtain a data item with uniqueness;
the extraction subunit is used for extracting basic information of each data item with uniqueness according to the data dictionary of each preset field, wherein the basic information comprises a table name, a table description, a field name, a field description, a field type, primary key information and foreign key information;
and the first judging subunit is used for judging whether each data item with uniqueness is main data according to the characteristics of the main data so as to obtain the main data information of each data item with uniqueness.
8. The apparatus of claim 5, wherein the submodel integration unit comprises:
the connection subunit is used for respectively connecting the preset fields in which each cross-domain data item is positioned through the cross-domain data items;
the second duplicate removal processing subunit is used for carrying out data item duplicate removal processing on the data model obtained after connection to obtain a target data model;
and the graphical processing subunit is used for carrying out graphical processing on the target data model to obtain a target data model diagram comprising a plurality of data items and the association between each data item.
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