CN114969100A - Data extraction method and device - Google Patents

Data extraction method and device Download PDF

Info

Publication number
CN114969100A
CN114969100A CN202210743294.1A CN202210743294A CN114969100A CN 114969100 A CN114969100 A CN 114969100A CN 202210743294 A CN202210743294 A CN 202210743294A CN 114969100 A CN114969100 A CN 114969100A
Authority
CN
China
Prior art keywords
data
information
target
target information
association
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
Application number
CN202210743294.1A
Other languages
Chinese (zh)
Inventor
程航
武天舒
谢立治
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bank of China Ltd
Original Assignee
Bank of China Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Bank of China Ltd filed Critical Bank of China Ltd
Priority to CN202210743294.1A priority Critical patent/CN114969100A/en
Publication of CN114969100A publication Critical patent/CN114969100A/en
Pending legal-status Critical Current

Links

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
    • G06F16/24—Querying
    • G06F16/242—Query formulation
    • 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
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2282—Tablespace storage structures; Management thereof
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Software Systems (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Health & Medical Sciences (AREA)
  • Bioethics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Hardware Design (AREA)
  • Computer Security & Cryptography (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The application provides a data extraction method and a data extraction device, which can be applied to the field of finance, and the method comprises the following steps: acquiring target information input by a user, determining associated information according to the target information, determining one or more associated tables according to the associated information, and extracting associated data corresponding to the target information from the one or more associated tables. Therefore, the method provided by the embodiment of the application can determine the associated information directly according to the target information, then determine the associated table associated with the target information by using the associated information, extract the associated data corresponding to the target information from the associated table, quickly acquire the associated table associated with the target information from a plurality of data tables, extract the data, improve the data extraction efficiency, mainly pay attention to the associated data associated with the target information during data extraction, and meet the requirement of diversity of the extracted data.

Description

Data extraction method and device
Technical Field
The present invention relates to the field of computers, and in particular, to a data extraction method and apparatus.
Background
With the rapid development of computer technology, more and more data are stored by using data tables of a relational database. As the amount of data increases, the number of data tables in the relational database increases.
In real life, a scenario may exist in which a plurality of data associated with target information in a data table are extracted quickly so as to perform data analysis, and therefore, how to extract the data associated with the target information from a plurality of data tables in a relational database is an urgent problem to be solved.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a data extraction method and apparatus, which can determine to extract data associated with target information from a plurality of data tables in a relational database, improve data extraction efficiency, and meet the requirement of diversity of extracted data.
The embodiment of the application provides a data extraction method, which is applied to a relational database, and comprises the following steps:
acquiring target information input by a user;
determining associated information according to the target information, wherein the associated information is other attribute information associated with the target information;
determining one or more association tables according to the association information;
and extracting the associated data corresponding to the target information from the one or more associated tables.
Optionally, the extracting, in the one or more association tables, association data corresponding to the target information includes:
automatically generating an associated query statement of the associated data;
extracting the association data in the one or more association tables according to the association query statement.
Optionally, the method further comprises:
determining basic attribute information to which the target information belongs;
determining a basic information table according to the basic attribute information;
and extracting target data corresponding to the target information in the basic information table.
Optionally, the extracting target data corresponding to target information in the basic information table includes:
automatically generating a target query statement of target data;
and extracting the target data from the basic information table according to the target query statement.
Optionally, the determining the associated information according to the target information includes:
and determining the type of the target information, and determining the associated information according to the type of the target information.
Optionally, the method further comprises:
determining one or more association sub-tables corresponding to the association table;
and extracting associated sub data from the one or more associated sub tables according to the associated data, wherein the associated sub data is used for reflecting relevant information of the associated data.
Optionally, the method further comprises:
carrying out format processing on the associated data and automatically generating a data import statement;
and inserting the associated data subjected to format processing into a target database by using the data import statement.
Optionally, the method further comprises:
and encrypting the sensitive data in the associated data.
The embodiment of the application provides a data extraction device, the device includes:
the device comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring target information input by a user;
a first determining unit, configured to determine associated information according to the target information, where the associated information is other attribute information associated with the target information;
a second determining unit, configured to determine one or more association tables according to the association information;
a first extracting unit, configured to extract associated data corresponding to the target information from the one or more association tables.
Optionally, the first extracting unit is specifically configured to:
automatically generating an associated query statement of the associated data;
extracting the association data in the one or more association tables according to the association query statement.
The embodiment of the application provides a data extraction method, which comprises the following steps: the method comprises the steps of obtaining target information input by a user, wherein the target information is information which the user wants to inquire in a data table, determining associated information according to the target information, the associated information is other attribute information associated with the target information, the associated information can reflect the relevant condition of the target information, determining one or more associated tables according to the associated information, namely determining the range of the table where the associated data associated with the target information is located according to the associated information, and then extracting the associated data corresponding to the target information from the one or more associated tables. Therefore, the method provided by the embodiment of the application can determine the associated information directly according to the target information, then determine the associated table associated with the target information by using the associated information, extract the associated data corresponding to the target information from the associated table, quickly acquire the associated table associated with the target information from a plurality of data tables, extract the data, improve the data extraction efficiency, mainly pay attention to the associated data associated with the target information during data extraction, and meet the requirement of diversity of the extracted data.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart illustrating a data extraction method provided in an embodiment of the present application;
fig. 2 shows a schematic structural diagram of a data extraction apparatus provided in an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways than those described herein, and it will be apparent to those of ordinary skill in the art that the present application is not limited by the specific embodiments disclosed below.
The data extraction method and the data extraction device provided by the invention can be used in the financial field or other fields, for example, can be used in a data storage application scene in the financial field. The other fields are arbitrary fields other than the financial field, for example, the computer field. The above is merely an example, and the application fields of the data extraction method and apparatus provided by the present invention are not limited.
With the rapid development of computer technology, more and more data are stored by using data tables of a relational database. The relational database adopts a storage mode of a table, and data are stored in a row mode and a column mode. The relational database stores data according to a structured method, each data table has each defined field, namely the structure of the table is defined in advance, and then the data is stored according to the structure of the table. In order to avoid duplicating and normalizing data and fully utilize storage space, a relational database usually stores the data in the form of a minimum relational table, so that subsequent data management can be clear and clear at a glance. However, as the amount of data increases, the number of data tables in the relational database increases, and since data relates to a plurality of data tables, complex relationships exist between the data tables, as the number of data tables increases, data management becomes more complex, and accordingly, the extraction efficiency of the data becomes slower.
In actual life, a plurality of data associated with target information in a data table may be extracted quickly so as to perform a data analysis scenario, for example, when a fault occurs in an interest-bearing transaction of an account, data such as the account and related products/interest rates thereof need to be brought to a development environment for error scenario reproduction, it is difficult to complete accurately in time.
Currently, a manual extraction method is adopted for a plurality of data associated with target information, technicians determine a data table associated with the target information through experience, write a special query statement of the data table for each data table associated with the target information, and then extract the data one by one, which is long in time consumption, low in extraction efficiency and possibly wrong in data extraction.
Therefore, how to quickly extract data associated with target information from a plurality of data tables of a relational database is an urgent problem to be solved.
Based on this, the embodiment of the present application provides a data extraction method, which includes: the method comprises the steps of obtaining target information input by a user, wherein the target information is information which the user wants to inquire in a data table, determining associated information according to the target information, the associated information is other attribute information associated with the target information, the associated information can reflect the relevant condition of the target information, determining one or more associated tables according to the associated information, namely determining the range of the table where the associated data associated with the target information is located according to the associated information, and then extracting the associated data corresponding to the target information from the one or more associated tables. Therefore, the method provided by the embodiment of the application can determine the associated information directly according to the target information, then determine the associated table associated with the target information by using the associated information, extract the associated data corresponding to the target information from the associated table, quickly acquire the associated table associated with the target information from a plurality of data tables, extract the data, improve the data extraction efficiency, mainly pay attention to the associated data associated with the target information during data extraction, and meet the requirement of diversity of the extracted data.
For a better understanding of the technical solutions and effects of the present application, specific embodiments will be described in detail below with reference to the accompanying drawings.
Referring to fig. 1, the figure is a flowchart of a data extraction method provided in an embodiment of the present application. The data extraction method provided by the embodiment can be applied to a relational database.
The data extraction method provided by the embodiment comprises the following steps:
s101, acquiring target information input by a user.
In an embodiment of the present application, the target information is data-related information that the user wants to obtain, for example, the target information is a bank account.
Target information input by a user can be acquired so as to extract data related to the target information in a data table of the database.
And S102, determining the associated information according to the target information.
In the embodiment of the application, the associated information can be determined according to the target information, the associated information is other attribute information associated with the target information, and the associated information can reflect the relevant condition of the target information.
As an example, the target information is an account, and the associated information may be a product type of the account or an interest rate of the account.
The range of the associated information may be predetermined, and specifically may be determined according to the type to which the target information belongs, that is, the associated information may be determined by determining the type to which the target information belongs and then determining the associated information according to the type to which the target information belongs.
Specifically, the type of the target information may be a financing type, a loan type or a deposit type, and different types correspond to different associated information.
As an example, the target information is a loan account, the type of the target information is a loan type, and the associated information may be a product type of the loan account or interest rate information of the loan account, or financial information of the loan account.
S103, determining one or more association tables according to the association information.
In an embodiment of the application, after determining the association information according to the target information, one or more association tables may be determined according to the association information.
As an example, if the target information is a loan account, the type to which the target information belongs is a loan type, the associated information may be a product type of the loan account, the associated table is determined to be a product information table, and if the associated information may be interest rate information of the loan account, the associated table is determined to be an interest rate information table.
That is, one or more association tables are determined according to the association information, that is, the range of the table in which the association data associated with the target information is located can be determined according to the association information, and then the association data corresponding to the target information can be extracted from the one or more association tables.
S104, extracting the associated data corresponding to the target information from the one or more associated tables.
In the embodiment of the application, after the one or more association tables are determined according to the association information, the association data corresponding to the target information can be extracted from the one or more association tables.
As an example, if the target information is a loan account, the type to which the target information belongs is a loan type, the associated information may be a product type of the loan account, the associated table is determined to be a product information table, the product type data of the loan account is extracted from the product information table, and if the associated information may be interest rate information of the loan account, the associated table is determined to be an interest rate information table, and the interest rate data of the loan account is extracted from the interest rate information table.
In practical application, associated query statements aiming at associated data of different associated tables can be automatically generated by extracting the associated data from one or more associated tables, then the associated data is extracted from one or more associated tables according to the associated query statements, and the associated data is extracted by using the automatically generated associated query statements, so that the extraction time of the associated data can be shortened, the rapid data extraction aiming at different associated tables can be realized, and the data extraction efficiency is improved.
In the embodiment of the application, besides the extraction of the associated data corresponding to the associated information associated with the target information, the basic data corresponding to the target information can also be extracted.
The basic attribute information to which the target information belongs can be specifically determined, a basic information table is determined according to the basic attribute information, and target data corresponding to the target information in the basic information table is extracted.
When extracting the target data corresponding to the target information in the basic information table, a target query statement of the target data may be automatically generated, and the target data may be extracted from the basic information table according to the target query statement.
As an example, the target information is a loan account, the basic attribute information to which the target information belongs is loan account basic information, a loan basic information table is determined according to the loan account basic information, and target data of the loan account is extracted from the loan basic information table by using an automatically generated target query statement.
In the embodiment of the present application, if the basic information table has the associated information, in order to improve the data extraction efficiency, the associated table corresponding to the associated information may not be queried.
As an example, if the loan basic information table has interest rate information that is a fixed interest rate value, the extraction of the associated data of the loan account in the interest rate information table may not be continued, and if the interest rate information is a floating interest rate value, the extraction of the actual interest rate value of the loan account in the interest rate information table may be required.
In the embodiment of the application, if the associated data in the association table cannot completely reflect the target information or the integrity of the associated information, the range of the data table can be continuously expanded, and the range of the extracted data is expanded.
Specifically, one or more association sub-tables corresponding to the association table may be determined, and the association sub-data is extracted from the one or more association sub-tables according to the association data, where the association sub-data is used to reflect relevant information of the association data.
As an example, if the target information is a loan account, the type of the target information is a loan type, and the associated information may be interest rate information of the loan account, the associated table is determined to be an interest rate information table, and interest rate data of the loan account is extracted from the interest rate information table. However, in general, the interest rate data is calculated according to the data in the interest rate history table, so the interest rate information table can be used to determine the interest rate history table, and the associated data for calculating the interest rate data of the loan account is extracted from the interest rate history table according to the interest rate data of the loan account.
When the associated sub data is extracted, a query statement of the associated sub data may be automatically generated, and the associated sub data is extracted from the associated sub table according to the query statement.
Therefore, according to the embodiment of the application, the correlated information correlated with the target information is extracted step by step from the target information by utilizing the correlated characteristics in the relational database, the data is extracted step by step, for example, the target information is an account, the interest rate data and the product data of the account are extracted by utilizing the correlated information interest rate or the product of the account, if the interest rate data is the floating interest rate, the interest rate historical data of the current interest rate is continuously extracted, through a multi-stage query mechanism, although a user only inputs one target information, for example, the account, the related information of the account, such as the product and the interest rate information, can be quickly extracted when the same is obtained, and finally the data information of the whole view of the account is obtained, so that the data extraction efficiency is greatly improved.
In the embodiment of the application, after the target data and the associated data of the target information are extracted, format processing may be performed on the target data and the associated data, and the processing on the data format may be to standardize the data and generate a formatted file convenient for a user to view.
Format processing is carried out on the target data and the associated data, the target data and the associated data are processed into data with the same format, the data can be in a data format capable of being imported into a target database, a data import statement can be automatically generated, the associated data and the target data which are subjected to format processing are inserted into the target database by using the automatically generated data import statement, and the extracted data are quickly imported into the target database. The target database may be user-specified data, such as a database of a development environment, for analysis of the extracted data.
In practical applications, the data import statement may be obtained reversely by a target query statement of the target data or an associated query statement of the associated data.
In the embodiment of the application, sensitive data in the associated data or the target data can be encrypted, so that privacy security of a user is protected, and data security is improved. The sensitive data may be an account address or the like.
Therefore, the method provided by the embodiment of the application can be applied to scenes in which a user needs to rapidly extract data, the low efficiency of manually extracting the data is avoided, the extraction efficiency is improved, meanwhile, associated data can be extracted, the integrity of the data is guaranteed, in addition, a data encryption function is provided, the safety of the data is guaranteed, a standardized output file and a function of rapidly importing the data into a target database are also provided, and the user can conveniently use the extracted data in various scenes.
The embodiment of the application provides a data extraction method, which comprises the following steps: the method comprises the steps of obtaining target information input by a user, wherein the target information is information which the user wants to inquire in a data table, determining associated information according to the target information, the associated information is other attribute information associated with the target information, the associated information can reflect the relevant condition of the target information, determining one or more associated tables according to the associated information, namely determining the range of the table where the associated data associated with the target information is located according to the associated information, and then extracting the associated data corresponding to the target information from the one or more associated tables. Therefore, the method provided by the embodiment of the application can determine the associated information directly according to the target information, then determine the associated table associated with the target information by using the associated information, extract the associated data corresponding to the target information from the associated table, quickly acquire the associated table associated with the target information from a plurality of data tables, extract the data, improve the data extraction efficiency, mainly pay attention to the associated data associated with the target information during data extraction, and meet the requirement of diversity of the extracted data.
Based on the data extraction method provided by the above embodiment, the embodiment of the present application further provides a data extraction device, and the working principle of the data extraction device is described in detail below with reference to the accompanying drawings.
Referring to fig. 2, the figure is a block diagram of a data extraction apparatus according to an embodiment of the present application.
The data extraction apparatus 200 provided in the present embodiment includes:
an obtaining unit 210 for obtaining target information input by a user;
a first determining unit 220, configured to determine, according to the target information, associated information, where the associated information is other attribute information associated with the target information;
a second determining unit 230, configured to determine one or more association tables according to the association information;
a first extracting unit 240, configured to extract associated data corresponding to the target information from the one or more association tables.
Optionally, the first extracting unit 240 is specifically configured to:
automatically generating an associated query statement of the associated data;
extracting the association data in the one or more association tables according to the association query statement.
Optionally, the apparatus further comprises:
a third determining unit configured to determine basic attribute information to which the target information belongs;
a fourth determining unit, configured to determine a basic information table according to the basic attribute information;
and the second extraction unit is used for extracting target data corresponding to the target information in the basic information table.
Optionally, the second extraction unit is specifically configured to:
automatically generating a target query statement of target data;
and extracting the target data in the basic information table according to the target query statement.
Optionally, the first determining unit 220 is specifically configured to:
and determining the type of the target information, and determining the associated information according to the type of the target information.
Optionally, the apparatus further comprises:
a fifth determining unit, configured to determine one or more association sub-tables corresponding to the association table;
and a third extracting unit, configured to extract associated sub data from the one or more associated sub tables according to the associated data, where the associated sub data is used to reflect relevant information of the associated data.
Optionally, the apparatus further comprises:
the processing unit is used for carrying out format processing on the associated data and automatically generating a data import statement;
and the inserting unit is used for inserting the associated data subjected to format processing into the target database by using the data import statement.
Optionally, the apparatus further comprises:
and the encryption unit is used for encrypting the sensitive data in the associated data.
When introducing elements of various embodiments of the present application, the articles "a," "an," "the," and "said" are intended to mean that there are one or more of the elements. The terms "comprising," "including," and "having" are intended to be inclusive and mean that there may be additional elements other than the listed elements.
It should be noted that, as one of ordinary skill in the art would understand, all or part of the processes of the above method embodiments may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when executed, the computer program may include the processes of the above method embodiments. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. The above-described apparatus embodiments are merely illustrative, and the units and modules described as separate components may or may not be physically separate. In addition, some or all of the units and modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The foregoing is merely a preferred embodiment of the present application and, although the present application discloses the foregoing preferred embodiments, the present application is not limited thereto. Those skilled in the art can now make numerous possible variations and modifications to the disclosed embodiments, or modify equivalent embodiments, using the methods and techniques disclosed above, without departing from the scope of the claimed embodiments. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application still fall within the protection scope of the technical solution of the present application without departing from the content of the technical solution of the present application.

Claims (10)

1. A method of data extraction for use with a relational database, the method comprising:
acquiring target information input by a user;
determining associated information according to the target information, wherein the associated information is other attribute information associated with the target information;
determining one or more association tables according to the association information;
and extracting the associated data corresponding to the target information from the one or more associated tables.
2. The method according to claim 1, wherein the extracting the associated data corresponding to the target information from the one or more association tables comprises:
automatically generating an associated query statement of the associated data;
extracting the association data in the one or more association tables according to the association query statement.
3. The method of claim 1, further comprising:
determining basic attribute information to which the target information belongs;
determining a basic information table according to the basic attribute information;
and extracting target data corresponding to the target information in the basic information table.
4. The method according to claim 3, wherein the extracting the target data corresponding to the target information in the basic information table comprises:
automatically generating a target query statement of target data;
and extracting the target data from the basic information table according to the target query statement.
5. The method according to any one of claims 1-4, wherein the determining the association information according to the target information comprises:
and determining the type of the target information, and determining the associated information according to the type of the target information.
6. The method according to any one of claims 1-4, further comprising:
determining one or more association sub-tables corresponding to the association table;
and extracting associated sub data from the one or more associated sub tables according to the associated data, wherein the associated sub data is used for reflecting relevant information of the associated data.
7. The method according to any one of claims 1-4, further comprising:
carrying out format processing on the associated data and automatically generating a data import statement;
and inserting the associated data subjected to format processing into a target database by using the data import statement.
8. The method according to any one of claims 1-4, further comprising:
and encrypting the sensitive data in the associated data.
9. A data extraction apparatus, characterized in that the apparatus comprises:
the device comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring target information input by a user;
a first determining unit, configured to determine associated information according to the target information, where the associated information is other attribute information associated with the target information;
a second determining unit, configured to determine one or more association tables according to the association information;
a first extracting unit, configured to extract associated data corresponding to the target information from the one or more association tables.
10. The apparatus according to claim 9, wherein the first extraction unit is specifically configured to:
automatically generating an associated query statement of the associated data;
extracting the association data in the one or more association tables according to the association query statement.
CN202210743294.1A 2022-06-28 2022-06-28 Data extraction method and device Pending CN114969100A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210743294.1A CN114969100A (en) 2022-06-28 2022-06-28 Data extraction method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210743294.1A CN114969100A (en) 2022-06-28 2022-06-28 Data extraction method and device

Publications (1)

Publication Number Publication Date
CN114969100A true CN114969100A (en) 2022-08-30

Family

ID=82964798

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210743294.1A Pending CN114969100A (en) 2022-06-28 2022-06-28 Data extraction method and device

Country Status (1)

Country Link
CN (1) CN114969100A (en)

Similar Documents

Publication Publication Date Title
CN111125266B (en) Data processing method, device, equipment and storage medium
CN105512564A (en) Method and device for data tamper-proof verification
JP3344612B2 (en) Scenario search processing method in risk analysis of financial assets
CN114969100A (en) Data extraction method and device
CN115827691A (en) Batch processing result verification method and device, computer equipment and storage medium
CN115129590A (en) Test case generation method and device, electronic equipment and storage medium
CN112445461B (en) Business rule generation method and device, electronic equipment and readable storage medium
CN112307029B (en) Bill data storage and bill generation methods, devices, server and storage medium
CN113610629A (en) Method and device for screening client data features from large-scale feature set
CN110517010A (en) A kind of data processing method, system and storage medium
CN117216164A (en) Financial data synchronous processing method, apparatus, device, medium and program product
CN117093759A (en) Data processing method, device, computer equipment and storage medium
US11151293B2 (en) Method and system for data analysis using a statistical model in one or more contexts
CN118295630A (en) Method, device, computer equipment and storage medium for generating program text
CN116934001A (en) Account resource determination method, device, computer equipment and storage medium
CN118277255A (en) Data verification method, device, computer equipment, storage medium and computer program product
CN116089296A (en) Service logic testing method, device, computer equipment and storage medium
CN117236298A (en) Report data generation method, report data generation device, computer equipment, report data generation medium and program product
CN113609283A (en) Data acquisition method and system
CN115358205A (en) Index card generation method and device
CN118152374A (en) Index model establishment method, apparatus, device, storage medium and program product
CN116401323A (en) Index data processing method and device and computer equipment
CN115082183A (en) Business object processing method and device, computer equipment and storage medium
CN116467337A (en) Page display method and device and computer equipment
CN117216088A (en) Database-oriented time variable multiplexing method, system and storage medium

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