CN112650803A - Data analysis system based on business intelligence - Google Patents
Data analysis system based on business intelligence Download PDFInfo
- Publication number
- CN112650803A CN112650803A CN202011529189.5A CN202011529189A CN112650803A CN 112650803 A CN112650803 A CN 112650803A CN 202011529189 A CN202011529189 A CN 202011529189A CN 112650803 A CN112650803 A CN 112650803A
- Authority
- CN
- China
- Prior art keywords
- data
- module
- model
- analysis
- management
- 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
- 238000007405 data analysis Methods 0.000 title claims abstract description 31
- 238000004458 analytical method Methods 0.000 claims abstract description 44
- 238000007726 management method Methods 0.000 claims abstract description 29
- 238000000034 method Methods 0.000 claims abstract description 20
- 238000013523 data management Methods 0.000 claims abstract description 17
- 238000011161 development Methods 0.000 claims abstract description 15
- 238000010219 correlation analysis Methods 0.000 claims abstract description 10
- 238000013075 data extraction Methods 0.000 claims abstract description 9
- 238000000611 regression analysis Methods 0.000 claims abstract description 8
- 238000013461 design Methods 0.000 claims description 9
- 238000013499 data model Methods 0.000 claims description 7
- 230000008676 import Effects 0.000 claims description 4
- 230000010354 integration Effects 0.000 claims description 4
- 238000011835 investigation Methods 0.000 claims description 4
- 241000533950 Leucojum Species 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000012517 data analytics Methods 0.000 claims 7
- 239000000284 extract Substances 0.000 claims 1
- 238000007781 pre-processing Methods 0.000 claims 1
- 238000007670 refining Methods 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 2
- 238000012098 association analyses Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002860 competitive effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
Images
Classifications
-
- 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
- G06F16/25—Integrating or interfacing systems involving database management systems
-
- 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
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/283—Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
-
- 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
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
-
- 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
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a data analysis system based on business intelligence, which comprises an intelligent system function module, an intelligent data analysis system and a data information analysis module, and is characterized in that: the intelligent system function module mainly comprises a data correlation analysis module, a data clustering analysis module and a data regression analysis module, and the intelligent data analysis system comprises a data management module, a permission management module, a data extraction module and a data development module. The efficiency of the management process is improved, and unnecessary cost is reduced; the method analyzes data, fully recognizes customer requirements, realizes information sharing, deepens the management of informatization to decision making, enables enterprise managers and decision makers to see business data from a clearer angle, improves the operation efficiency of enterprises, increases profits, establishes good customer relations, and enables the enterprises to discover and capture business opportunities in the shortest time.
Description
Technical Field
The invention relates to the technical field of data analysis based on business intelligence, in particular to a data analysis system based on business intelligence.
Background
The intelligent data analysis of our country is still in a starting stage, the effective utilization rate of domestic enterprise data is less than 7%, many decisions are made under the condition of insufficient information support, and the investigation of the American market research company IDC shows that 37% of business decisions of our country still mainly depend on intuition or instinct. Meanwhile, the domestic application of intelligent data analysis is mainly focused on financial service industries such as banks and insurance; the telecommunications industry; the aviation industry and other industries with sufficient funds, early information starting and urgent need of data analysis. And the market environment specification of intelligent data analysis in China is not perfect.
A feature of BI practice lacking BI specifications is that the system architecture of the BI is relatively stable once the data is extracted and integrated into the data warehouse. The theoretical research and the model establishment of the domestic data warehouse part are relatively mature, and the source part of the data is extracted and integrated into the data warehouse from MIS, MRP/MRPI, SCM, CRM and other information systems based on business processing because the first-hand data of the data is extracted and integrated into the data warehouse. However, the existing systems are lack of standards, the structures of various original data are all the same and different, and even different products of the information system of the same manufacturer, different modules among the same product and data of different versions of the same module are all non-uniform. Therefore, the data extraction integration workload is very large for the implementation of the BI system.
The BI analysis system is low in enthusiasm, and is limited by objective conditions, the data required by the current business enterprise operation and analysis mainly come from the related information in the enterprise, the analysis work mainly refers to the inquiry, summarization and report of the information and data, the research on the market and consumers is not enough, and the enhancement of the competitive power of the enterprise is quite disadvantageous. Due to lack of deep analysis on business development and low utilization rate of internal information, the business analysis can not fully embody information prediction and decision making functions, various consulting services are provided for leading decisions, and the enthusiasm of enterprises for constructing high-intelligence intelligent data analysis and analysis systems is influenced.
Disclosure of Invention
The invention aims to solve the problems set forth above and provides a data analysis system based on business intelligence.
In order to achieve the purpose, the invention provides the following technical scheme: including intelligent system functional module, intelligent data analysis system and data information analysis module, its characterized in that: the intelligent system function module mainly comprises a data correlation analysis module, a data clustering analysis module and a data regression analysis module, the intelligent data analysis system comprises a data management module, a permission management module, a data extraction module and a data development module, the data management module is used for realizing data management by recording data information submitted by a user, the user needs to create a form and add fields before submitting data, then the submitted data information is stored in the form and corresponding data is imported, the data management module comprises table management, data management and field management, the permission management module is mainly used for realizing the management of the user, roles, menus, permissions and log contents, the data extraction module is mainly used for extracting the data information and respectively arranging the data information in different databases after extracting the data information, the report development module is mainly represented by the establishment of a data model, the development of a BIEE report and JAVA integration operation, the data information analysis module comprises a physical model, a logic model and a display model, the data information extraction establishes a corresponding data warehouse through the ODI, and the specific operation process is as follows:
the method comprises the following steps: creating a main database, wherein the main database stores all IT resource topological structures in the enterprise development process. The main database can store important project and data model information and provide important support for the use of the ODI graphic module;
step two: creating a working database, and storing each item and data information in the working database. The relations of the data base and the main data base correspond to each other in operation;
step three: creating a data server, and creating a plurality of physical frameworks according to the requirements of different users;
step four: creating a logic architecture, wherein the creation of the logic architecture is usually in one-to-one correspondence with the physical architecture;
step five: creating projects, wherein each project also needs to correspond to a corresponding logic architecture;
step six: the method comprises the steps of (1) establishing models, wherein each model is required to correspond to a logic structure;
step seven: and (3) creating an interface, wherein each model needs to correspond to a logic architecture after the interface is created.
Preferably, the data correlation analysis module is used for importing required classification files under corresponding paths, then selecting variables, performing expansion analysis on the variable correlation problem by applying an MTC method, determining multivariate information, and analyzing the correlation size problem of each variable in the data by means of correlation data analysis among the multivariate.
Preferably, the data association analysis module can apply a rule algorithm of association to perform analysis on the influence problem among the data, and determine the effective association rule among the data after the analysis.
Preferably, the data regression analysis module needs to import the classification data file under a certain path.
Preferably, the data clustering analysis module can realize automatic classification management of the imported data information by means of the size problem of the correlation among the data.
Preferably, the physical model refers to the design of an analysis object of the database, the physical model design is the physical implementation of the logical model in the data warehouse, the design of the physical model needs to comprehensively understand the characteristics of the database management system, the operation environment of the database system and the external equipment of the database, and after the comprehensive understanding, the data is displayed in the database in the form of a table.
Preferably, the logic model is further refined on the basis of the physical model, a plurality of data tables can be converted into dimension tables, the dimension tables are divided hierarchically, corresponding division rules are set, the logic model form of the BIEE is various, such as a snowflake model and a star model, and the data information is preprocessed after investigation and analysis. The system model has the advantages that the relation between the fact table and the dimension tables can be simplified, more visual data information is provided for users, in the star model, the fact table is located at the most central position, and the dimension tables are located around the star model to form a radial shape. In this mode, a user can query specific business data from a data warehouse, and the system of the logic model SSIS is composed of services, object models, runtime executable files, a packaged data stream engine and data stream components.
Preferably, the display models are models which are finally seen by a database user after a series of operations, each display model corresponds to an analysis theme, the relation problem between the dimension and the fact table is clearly described, the relation between the matters is clearly displayed for people, and the display models specifically comprise office data, work performance data and personal behavior data.
Compared with the prior art, the invention has the beneficial effects that: the invention relates to a data analysis system based on business intelligence, which realizes enterprise information sharing and can optimize the performance of the whole enterprise. The efficiency of the management process is improved, and unnecessary cost is reduced; the method analyzes data, fully recognizes customer requirements, realizes information sharing, deepens the management of informatization to decision making, enables enterprise managers and decision makers to see business data from a clearer angle, improves the operation efficiency of enterprises, increases profits, establishes good customer relations, and enables the enterprises to discover and capture business opportunities in the shortest time.
Drawings
FIG. 1 is a block diagram of an intelligent system function module of a business intelligence based data analysis system of the present invention.
FIG. 2 is a block diagram of an intelligent data analysis system of the business intelligence-based data analysis system of the present invention.
FIG. 3 is a block diagram of a data information analysis module of the business intelligence-based data analysis system of the present invention.
In the figure: the method comprises the following steps of 1-an intelligent system function module, 2-an intelligent data analysis system, 3-a data information analysis module, 4-a data correlation analysis module, 5-a data correlation analysis module, 6-a data clustering analysis module, 7-a data regression analysis module, 8-a data management module, 9-a permission management module, 10-a data extraction module, 11-a data development module, 12-a physical model, 13-a logical model and 14-a display model.
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. 1-3, the present invention provides a technical solution: including intelligent system functional module 1, intelligent data analysis system 2 and data information analysis module 3, its characterized in that: the intelligent system function module 1 mainly comprises a data correlation analysis module 4, a data correlation analysis module 5, a data clustering analysis module 6 and a data regression analysis module 7, the intelligent data analysis system 2 comprises a data management module 8, a permission management module 9, a data extraction module 10 and a data development module 11, the data management module 8 is used for realizing data management by recording data information submitted by a user, the user needs to create a form and add fields before submitting data, then the submitted data information is stored in the form and corresponding data is imported, the data management module 8 comprises table management, data management and field management, the permission management module 9 is mainly used for realizing management of users, roles, menus, permissions and log contents, the data extraction module 10 is mainly used for extracting data information, after data information is extracted, the data information is respectively arranged in different databases, the report development module 11 mainly represents creation of a data model, development of a BIEE report, and JAVA integration operation, the data information analysis module 3 includes a physical model 12, a logical model 13, and a presentation model 14, the data information extraction 10 establishes a corresponding data warehouse through ODI, and the specific operation process is as follows:
the method comprises the following steps: creating a main database, wherein the main database stores all IT resource topological structures in the enterprise development process. The main database can store important project and data model information and provide important support for the use of the ODI graphic module;
step two: creating a working database, and storing each item and data information in the working database. The relations of the data base and the main data base correspond to each other in operation;
step three: creating a data server, and creating a plurality of physical frameworks according to the requirements of different users;
step four: creating a logic architecture, wherein the creation of the logic architecture is usually in one-to-one correspondence with the physical architecture;
step five: creating projects, wherein each project also needs to correspond to a corresponding logic architecture;
step six: the method comprises the steps of (1) establishing models, wherein each model is required to correspond to a logic structure;
step seven: the creation of the interface, each model needs to correspond to a logic architecture after the creation of the interface is completed, the data correlation analysis module 5 is to import a required classification file under a corresponding path, then select variables, apply an MTC method to develop and analyze the variable correlation problem, determine multivariate information, analyze the correlation size problem of each variable in the data by means of the correlation data analysis among the multivariate, the data correlation analysis module 4 can apply a correlation rule algorithm to develop and analyze the influence problem among each data, determine the effective correlation rule among the data after the analysis, the data regression analysis module 7 needs to import a classification data file under a certain path, the data clustering analysis module 6 can realize the automatic classification management of the imported data information by means of the size problem of the correlation among the data, the physical model 12 refers to the design of a database analysis object, the physical model design is the physical realization of a logical model in a data warehouse, the physical model design needs to comprehensively understand the characteristics of a database management system, the operating environment of the database system and external equipment of the database, data are displayed in the database in a table form after the comprehensive understanding, the logical model 13 is the further refinement processing of the data on the basis of the physical model, can convert various data tables into dimension tables, hierarchically divides the dimension tables, sets corresponding division rules, has many logical model forms of BIEE, such as a snowflake model and a star model, and realizes the pretreatment of data information after investigation and analysis. The system model has the advantages that the relation between the fact table and the dimension tables can be simplified, more visual data information is provided for users, in the star model, the fact table is located at the most central position, and the dimension tables are located around the star model to form a radial shape. In the mode, a user can inquire specific business data from a data warehouse, a system of a logic model SSIS is composed of a service, an object model, a runtime executable file, a packaged data stream engine and a data stream component, the display model 14 is a model finally seen by a database user after a series of operations, each display model corresponds to an analysis subject, the relation problem between dimensions and a fact table is clearly described, the relation between things is clearly displayed to people, and the display model specifically comprises office data, work performance data and personal behavior data.
The intelligent data analysis system comprises three levels of contents, namely a physical layer, a logic layer and a presentation layer, can complete the creation of a data model under the background management of the BIEE, and takes the construction of an individual behavior performance model as an example, the implementation operation steps of the intelligent data analysis system are as follows:
(1) the BIEE management tool loads the data information in the database into the physical layer of the data archive base in an OCI mode.
(2) And (5) developing a BIEE report. The BIEE report needs to be logged on a BIEE server before being developed, and login browsing operation is carried out after the installation operation is completed.
And obtaining a corresponding graphic analysis result after analysis, and making different forms of reports according to the requirements of users. After the report is made, the report is embedded into a webpage through a Web Service interface, and the specific operations are as follows: firstly, downloading a wsdl file, starting a BIEE service, and opening a browser input address; secondly, producing a client code, and applying an Axis plug-in to produce the client code from the wsdl file; finally, the code description is invoked. After application BIEE login, authentication is done in the manner of logonex.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (8)
1. A data analysis system based on business intelligence comprises an intelligent system function module (1), an intelligent data analysis system (2) and a data information analysis module (3), and is characterized in that: the intelligent system function module (1) mainly comprises a data relevance analysis module (4), a data relevance analysis module (5), a data clustering analysis module (6) and a data regression analysis module (7), the intelligent data analysis system (2) comprises a data management module (8), a permission management module (9), a data extraction module (10) and a data development module (11), the data management module (8) is used for realizing data management by recording data information submitted by a user, the user needs to create a form and add fields before submitting data, then the data information submitted after being stored in the form and corresponding data is imported, the data management module (8) comprises form management, data management and field management, the permission management module (9) mainly realizes the management of the contents of the user, roles, menus, permissions and logs, the data extraction module (10) mainly extracts data information, the data information is respectively arranged in different databases after the data information is extracted, the report development module (11) mainly represents the creation of a data model, the development of a BIEE report and JAVA integration operation, the data information analysis module (3) comprises a physical model (12), a logic model (13) and a presentation model (14), the data information extraction module (10) establishes a corresponding data warehouse through an ODI, and the specific operation process is as follows:
the method comprises the following steps: creating a main database, wherein the main database stores all IT resource topological structures in the enterprise development process, and can store important project and data model information to provide important support for the use of an ODI graphic module;
step two: creating a working database, storing each item and data information in the working database, wherein the relations between the working database and the main database correspond to each other;
step three: creating a data server, and creating a plurality of physical frameworks according to the requirements of different users;
step four: creating a logic architecture, wherein the creation of the logic architecture is usually in one-to-one correspondence with the physical architecture;
step five: creating projects, wherein each project also needs to correspond to a corresponding logic architecture;
step six: the method comprises the steps of (1) establishing models, wherein each model is required to correspond to a logic structure;
step seven: and (3) creating an interface, wherein each model needs to correspond to a logic architecture after the interface is created.
2. The business intelligence-based data analytics system of claim 1, wherein: the data correlation analysis module (5) is used for importing required classification files under corresponding paths, then selecting variables, applying an MTC method to carry out expansion analysis on the variable correlation problem, determining multi-variable information, and analyzing the correlation size problem of each variable in the data by means of correlation data analysis among the multi-variables.
3. The business intelligence-based data analytics system of claim 1, wherein: the data relevance analysis module (4) can apply a relevance rule algorithm to perform analysis on influence problems among various data, and determine valid relevance rules among the data after analysis.
4. The business intelligence-based data analytics system of claim 1, wherein: the data regression analysis module (7) needs to import classification data files under a certain path.
5. The business intelligence-based data analytics system of claim 1, wherein: the data clustering analysis module (6) can realize automatic classification management of imported data information by means of the problem of the correlation among data.
6. The business intelligence-based data analytics system of claim 1, wherein: the physical model (12) refers to the design of a database analysis object, the physical model design is the physical realization of a logic model in a data warehouse, the design of the physical model needs to comprehensively understand the characteristics of a database management system, the operation environment of the database system and external equipment of the database, and data is displayed in the database in a table form after the comprehensive understanding.
7. The business intelligence-based data analytics system of claim 1, wherein: the logic model (13) is used for further refining data on the basis of a physical model, can convert various data tables into dimension tables, hierarchically divides the dimension tables, sets corresponding division rules, has a plurality of logic model forms of BIEE, such as a snowflake model and a star model, and realizes the preprocessing of data information after investigation and analysis. The system model has the advantages that the relation between the fact table and the dimension tables can be simplified, more visual data information is provided for users, in the star model, the fact table is located at the most central position, and the dimension tables are located around the star model to form a radial shape. In this mode, a user can query specific business data from a data warehouse, the architecture of the logical model SSIS is shown in fig. 2, and the system of the SSIS is composed of four key parts, namely, a service, an object model, a runtime executable file, an encapsulated data stream engine, and a data stream component.
8. The business intelligence-based data analytics system of claim 1, wherein: the display model (14) is a model finally seen by a database user after a series of operations, each display model corresponds to an analysis subject, the relation problem between the dimension and the fact table is clearly described, the relation between the matters is clearly displayed for people, and the display model specifically comprises office data, work performance data and personal behavior data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011529189.5A CN112650803A (en) | 2020-12-22 | 2020-12-22 | Data analysis system based on business intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011529189.5A CN112650803A (en) | 2020-12-22 | 2020-12-22 | Data analysis system based on business intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112650803A true CN112650803A (en) | 2021-04-13 |
Family
ID=75359050
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011529189.5A Pending CN112650803A (en) | 2020-12-22 | 2020-12-22 | Data analysis system based on business intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112650803A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113076370A (en) * | 2021-04-23 | 2021-07-06 | 上海寒光信息科技有限公司 | Internet data sky-eye agent BI system |
| CN113298310A (en) * | 2021-06-04 | 2021-08-24 | 广州天辰信息科技有限公司 | BI data analysis system and method based on custom configuration |
| CN113986904A (en) * | 2021-11-08 | 2022-01-28 | 深圳赛诺百应科技有限公司 | Business intelligent data analysis system based on Internet |
| CN116663938A (en) * | 2023-07-28 | 2023-08-29 | 珠海大横琴泛旅游发展有限公司 | Informatization management method based on enterprise data center system and related device thereof |
-
2020
- 2020-12-22 CN CN202011529189.5A patent/CN112650803A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113076370A (en) * | 2021-04-23 | 2021-07-06 | 上海寒光信息科技有限公司 | Internet data sky-eye agent BI system |
| CN113298310A (en) * | 2021-06-04 | 2021-08-24 | 广州天辰信息科技有限公司 | BI data analysis system and method based on custom configuration |
| CN113986904A (en) * | 2021-11-08 | 2022-01-28 | 深圳赛诺百应科技有限公司 | Business intelligent data analysis system based on Internet |
| CN116663938A (en) * | 2023-07-28 | 2023-08-29 | 珠海大横琴泛旅游发展有限公司 | Informatization management method based on enterprise data center system and related device thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112650803A (en) | Data analysis system based on business intelligence | |
| US7991800B2 (en) | Object oriented system and method for optimizing the execution of marketing segmentations | |
| US8234308B2 (en) | Deliver application services through business object views | |
| CN102937901B (en) | Multi-tenant architecture design method | |
| JP2008511936A (en) | Method and system for semantic identification in a data system | |
| US20190050435A1 (en) | Object data association index system and methods for the construction and applications thereof | |
| US11609926B1 (en) | Methods and systems for social awareness | |
| US11567936B1 (en) | Platform agnostic query acceleration | |
| CN111382155A (en) | Data processing method of data warehouse, electronic equipment and medium | |
| CN111126852A (en) | BI application system based on big data modeling | |
| Duan | Analysis of ERP enterprise management information system based on cloud computing mode | |
| Gopsill et al. | Trends in technology and their possible implications on PLM: looking towards 2020 | |
| Campos et al. | Engineering environment to support product-service design using value chain data | |
| Xu | [Retracted] Social Governance Structure Construction and Resource Allocation Methods under the Management Mode of the Internet of Things | |
| Dreiling et al. | From conceptual process models to running workflows: A holistic approach for the configuration of enterprise systems | |
| Wang et al. | An intelligent DevOps platform research and design based on machine learning | |
| CN113886465A (en) | Big data analysis platform for automobile logistics | |
| CN110990745A (en) | Method for automatically synchronizing similar public cloud resources | |
| CN115017185A (en) | Data processing method, device and storage medium | |
| Gan | Design of network precision marketing based on big data analysis technology | |
| CN112328604A (en) | Data middlebox construction method, system and medium for spatiotemporal portrait label management | |
| Tashkova | Big data-the new challenge facing business | |
| Juan | The research to open BIM-based building information interoperability framework | |
| Li et al. | Enterprise precision marketing effectiveness model based on data mining technology | |
| US10152556B1 (en) | Semantic modeling platform |
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 |
Application publication date: 20210413 |
|
| WD01 | Invention patent application deemed withdrawn after publication |