Salesforce, inc. (20240193174). AUTOMATIC DATA LINTING RULES FOR ETL PIPELINES simplified abstract

AUTOMATIC DATA LINTING RULES FOR ETL PIPELINES

Organization Name

salesforce, inc.

Inventor(s)

Ignacio Agustin Manzano of Buenos Aires (AR)

Subhash Periasamy of Newark CA (US)

Berkay Polat of Redwood City CA (US)

Vineeth Anand Nair of Mountain House CA (US)

Udayakumar Dhansingh of Dublin CA (US)

Vijay Gopalakrishnan of Seattle WA (US)

Saebom Kwon of San Francisco CA (US)

AUTOMATIC DATA LINTING RULES FOR ETL PIPELINES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240193174 titled 'AUTOMATIC DATA LINTING RULES FOR ETL PIPELINES

Simplified Explanation

The patent application describes a system that allows non-coders to create or transform a database in an ETL pipeline. Users can input a database and receive a ruleset to apply to it, simplifying the ETL process.

• Users can input a database and receive a ruleset for an ETL pipeline.
• The system extracts a schema and data sample from the database.
• Two rulesets are created based on the schema and data sample.
• The rulesets are combined into a final ruleset for validation.
• The final ruleset and validation report are sent to the user.

Key Features and Innovation

• Simplifies the process of creating or transforming a database in an ETL pipeline.
• Allows non-coders to easily apply rules to databases.
• Automates the creation of rulesets based on database schema and data samples.
• Validates the final ruleset for accuracy before use in an ETL pipeline.

Potential Applications

This technology can be applied in various industries where ETL processes are used, such as data analytics, business intelligence, and data warehousing.

Problems Solved

• Simplifies the ETL process for non-coders.
• Automates the creation of rulesets for database transformation.
• Ensures accuracy and validation of rulesets before implementation.

Benefits

• Increases efficiency in database transformation processes.
• Reduces the need for manual coding and rule creation.
• Improves accuracy and reliability of ETL pipelines.

Commercial Applications

Automated Database Transformation System for ETL Pipelines: Revolutionizing Data Processing in Various Industries This technology can be utilized by data analytics companies, business intelligence firms, and data warehousing providers to streamline database transformation processes and improve overall efficiency in data processing.

Prior Art

Research in the field of ETL processes, data transformation, and database automation tools can provide insights into similar technologies and advancements in the industry.

Frequently Updated Research

Stay updated on the latest developments in ETL automation, database transformation tools, and data processing technologies to enhance the efficiency and effectiveness of this system.

Questions about Automated Database Transformation System for ETL Pipelines

How does this system benefit non-coders in database transformation processes?

This system simplifies the ETL process by automating the creation of rulesets based on database schema and data samples, allowing non-coders to easily apply rules to databases without manual coding.

What industries can benefit from this technology?

Various industries such as data analytics, business intelligence, and data warehousing can benefit from this technology by improving the efficiency and accuracy of database transformation processes.

Original Abstract Submitted

in the present disclosure, systems and methods are described for allowing a non-code user to create to transform a database in an etl pipleline. specifically, as disclosed herein, a user can take a database and receive a ruleset to apply to the database in an etl pipeline. the data linting system may take the database and extract a schema and a data sample from it. further, the data linting system may use the schema and data sample to create two rulesets. with these rulesets, the data linting system combines them to create a final ruleset which may be validated using the data sample. the data linting system then sends the final ruleset and the validation report to the user. with this system, the user only needs to give it a database and will receive a ruleset that is able to be immediately used in an etl pipeline.