Database-end data analysis processing systematic platform construction method

Abstract

The invention discloses a method for constructing a data analysis and processing systematic platform at a database end. The method comprises the following steps: S1, defining naming and directory structure specifications; s2, constructing a program framework system based on the naming and directory structure specifications in the S1; s3, constructing an extensible script template library based on the framework system constructed in the S2; s4, constructing a dynamic rule configuration library; s5, designing a universal code template framework according to the program framework system constructed in the S3 and the dynamic rule configuration library constructed in the S4; and S6, setting parameterized variable group content, and embedding the variable group content with the general code template framework designed in the S5 by adopting an automatic generation lead to generate an executable SQL logic code. The platform integrates specifications, templates, rules and automation into a unified platform to form a complete development system. All logics are realized through an SQL language, external programming language dependence is prevented from being introduced, rapid integration can be realized, original traditional manual writing script transplantation is realized, and the deployment complexity is reduced.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a method for constructing a systematic platform for data analysis and processing at the database level. Background Technology

[0002] As enterprises deepen their digital transformation, data has become a core resource driving business decisions and innovation. Data analysis and processing have become important means for various industries to improve decision-making efficiency and business competitiveness, especially in fields such as finance, e-commerce, manufacturing, and logistics, where enterprises have an ever-increasing demand for real-time, accurate, and traceable data analysis. However, traditional data analysis and processing systems often rely on complex programming logic and large amounts of development resources, resulting in long development cycles, high maintenance costs, and difficulty in quickly adapting to changing business needs. Especially at the database level, many enterprises still use purely manual scripting for data processing, lacking unified standards and reusable development frameworks, leading to problems such as low development efficiency, high code duplication, and difficult system maintenance. Summary of the Invention

[0003] The purpose of this application is to provide a method for constructing a systematic platform for data analysis and processing at the database level. The specific technical solution is as follows:

[0004] A method for constructing a systematic platform for data analysis and processing at the database end includes: S1, defining naming and directory structure specifications; S2, constructing a program framework system based on the naming and directory structure specifications in S1; S3, constructing an extensible script template library based on the framework system constructed in S2; S4, constructing a dynamic rule configuration library; S5, designing a general code template framework based on the program framework system constructed in S3 and the dynamic rule configuration library constructed in S4; S6, setting parameterized variable group content, and using automated generation to embed the variable group content with the general code template framework designed in S5 to generate executable SQL logic code.

[0005] When defining naming and directory structure specifications in S1, the following are included: S1.1, defining encoding naming rules, including table names, view names, stored procedure names, and variable names; S1.2, defining directory structure, directory names, and file name rules.

[0006] When constructing the program framework in S2, the following steps are included: S2.1, dividing the data processing flow into multiple combinable standard steps as needed, including variable declaration and processing, data range determination, basic data organization, data cleaning, data processing, and data output; S2.2, developing standard process documents to clarify the responsibilities, input and output requirements, and exception handling mechanisms for each step.

[0007] When building an extensible script template library in S3, the following steps are included: S3.1, categorizing and managing templates according to business themes and data processing types; themes include premium statistics, claims analysis, and persistency rate assessments, while types include incremental updates, data synchronization, and data integration; S3.2, using abstract general logic as templates, pre-setting standard SQL script frameworks, with each step corresponding to a set of standard programs, including common code for variable declaration, logging, performance monitoring, and basic data organization.

[0008] When building a dynamic rule configuration library in S4, the process includes: S4.1, setting standard processing logic, including filtering conditions, field mapping, calculation formulas, deduplication logic, and data type conversion rules; S4.2, creating a rule configuration table, including rule ID, rule type, condition expression, execution logic, and effective time; and S4.3, setting general rule parsing code to enable dynamic rule loading.

[0009] In S6, the parameterized variable group is used for special development projects with multiple subclasses and high logical redundancy. The changing parts are abstracted, analyzed, and sorted out to form a parameterized variable group.

[0010] The beneficial effects of this application are that the platform integrates standards, templates, rules, and automation into a unified platform, forming a complete development system. All logic is implemented using SQL, avoiding dependencies on external programming languages, allowing for quick integration and porting from traditional manual scripting, thus reducing deployment complexity. Unified naming rules and program development frameworks, along with the application of template and configuration libraries, achieve orderly code management, significantly improving code readability, portability, and maintainability. The "configuration-based" nature of business logic through rule and template libraries enables agile responses of "configuration as change" without code modification. Mechanisms such as template inheritance, parametric design, and rule reuse not only effectively lower the learning curve but also reduce repetitive development work by more than 70%. Through the integration of the four modules of standards, templates, rules, and automation, this application constructs a standardized, automated, and scalable data processing platform, solving the core pain points of low efficiency, difficult maintenance, and insufficient human resources in traditional underlying data development models. Attached Figure Description

[0011] Figure 1 This is a flowchart illustrating the application process. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of this application. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0013] like Figure 1 As shown, a method for constructing a systematic platform for data analysis and processing at the database end includes:

[0014] S1. Define naming and directory structure specifications. Specifically, defining naming and directory structure specifications includes: S1.1. Defining coding naming rules, including table names, view names, stored procedure names, and variable names; S1.2. Defining directory structure, directory names, and file name rules.

[0015] S2. Construct the program framework based on the naming and directory structure specifications in S1. Specifically, constructing the program framework includes: S2.1. Dividing the data processing flow into multiple combinable standard steps as needed, including variable declaration and processing, data range determination, basic data organization, data cleaning, data processing, and data output; S2.2. Developing standard process documents to clarify the responsibilities, input and output requirements, and exception handling mechanisms for each step.

[0016] S3. Build an extensible script template library based on the framework established in S2. Specifically, building the extensible script template library includes: S3.1. Categorizing and managing templates according to business themes and data processing types; among them, themes include premium statistics, claims analysis, and persistency rate assessments, and types include incremental updates, data synchronization, and data integration; S3.2. Using abstract general logic as templates, a pre-built standard SQL script framework is provided, with each step corresponding to a set of standard programs, including common code for variable declaration, logging, performance monitoring, and basic data organization.

[0017] S4. Construct a dynamic rule configuration library. Specifically, constructing the dynamic rule configuration library includes: S4.1. Setting standard processing logic, including filtering conditions, field mapping, calculation formulas, deduplication logic, and data type conversion rules; S4.2. Creating a rule configuration table, including rule ID, rule type, conditional expression, execution logic, and effective time; S4.3. Setting general rule parsing code to achieve dynamic rule loading.

[0018] S5. Based on the program framework system built in S3 and the dynamic rule configuration library built in S4, design a general code template framework.

[0019] S6. Set the content of parameterized variable groups, and use automated generation to embed the variable group content with the general code template framework designed in S5 to generate executable SQL logic code. The parameterized variable group content is for special development with multiple subclasses and high logical repetition. The changing parts are abstracted, analyzed and sorted out to form parameterized variable groups.

Claims

1. A method for constructing a systematic platform for data analysis and processing at the database level, characterized in that, include: S1. Define naming and directory structure specifications; S2. Construct a program framework system based on the naming and directory structure specifications in S1; S3. Construct an extensible script template library based on the framework system built in S2; S4. Build a dynamic rule configuration library; S5. Design a general code template framework based on the program framework system built in S3 and the dynamic rule configuration library built in S4; S6. Set the parameterized variable group content, and use automated generation to embed the variable group content with the general code template framework designed in S5 to generate executable SQL logic code.

2. The method for constructing a systematic data analysis and processing platform at the database end as described in claim 1, characterized in that, The naming and directory structure specifications defined in S1 include: S1.1 Define coding naming rules, including table names, view names, stored procedure names, and variable names; S1.2 Define the directory structure, directory names, and file name rules.

3. The method for constructing a systematic data analysis and processing platform at the database end as described in claim 2, characterized in that, The construction of the program framework system in S2 includes: S2.1 Divide the data processing flow into multiple combinable standard steps as needed, including variable declaration and processing, data range determination, basic data organization, data cleaning, data processing, and data output; S2.2 Develop standard process documents to clarify the responsibilities, input and output requirements, and exception handling mechanisms for each step.

4. The method for constructing a systematic data analysis and processing platform at the database end as described in claim 3, characterized in that, The construction of an extensible script template library in S3 includes: S3.

1. Classify and manage templates according to business themes and data processing types; among them, the theme classification includes premium statistics, claims analysis, and persistency rate assessments, and the type classification includes incremental updates, data synchronization, and data integration. S3.

2. Using abstract general logic as a template, a standard SQL script framework is pre-built. Each step corresponds to a set of standard programs, including general code for variable declaration, logging, performance monitoring, and basic data organization.

5. The method for constructing a systematic data analysis and processing platform at the database end as described in claim 4, characterized in that, The construction of the dynamic rule configuration library in S4 includes: S4.1 Set up standard processing logic, including filtering conditions, field mapping, calculation formulas, deduplication logic, and data type conversion rules; S4.2 Create a rule configuration table, including rule ID, rule type, condition expression, execution logic, and effective time; S4.3 Set up general code for rule parsing to enable dynamic loading of rules.

6. The method for constructing a systematic data analysis and processing platform at the database end as described in claim 5, characterized in that, The parameterized variable group in S6 is formed by abstracting, analyzing and sorting out the changing parts of a special development project with multiple subclasses and high logical repetition, thus creating a parameterized variable group.

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