Companies in the data integration space like Fivetran could potentially explore using LLMs for various purposes. Here are some speculative ways in which Fivetran or similar companies could leverage LLMs:
- Natural Language Query Interface: Fivetran could develop a natural language query interface that allows users to interact with their data integration platform using plain language. This could simplify the process of creating data pipelines and querying data sources.
- Automated Documentation: LLMs could be used to automatically generate documentation for data pipelines. This could include explanations of data sources, transformations, and the overall data flow.
- Data Source Recommendations: Fivetran might use LLMs to analyze users’ data needs and provide recommendations for relevant data sources to integrate. The LLM could understand users’ requirements from text inputs and suggest appropriate connectors.
- Data Transformation Suggestions: LLMs could assist users in formulating data transformation steps by generating suggestions based on their descriptions of desired transformations.
- Data Pipeline Troubleshooting: If users encounter issues with their data pipelines, an LLM could help diagnose problems and suggest solutions based on the error messages or descriptions provided by the user.