Tech Radar
Tech Radar automates the integration of data from Google Drive, Google Sheets, and MySQL, transforming documents into structured information and vector databases. By synchronizing technology data monthly, it enhances accessibility for AI agents, enabling efficient retrieval and analysis of strategic technology insights. This workflow streamlines data management, ensuring timely updates and informed decision-making across organizations.
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Workflow Overview
Tech Radar automates the integration of data from Google Drive, Google Sheets, and MySQL, transforming documents into structured information and vector databases. By synchronizing technology data monthly, it enhances accessibility for AI agents, enabling efficient retrieval and analysis of strategic technology insights. This workflow streamlines data management, ensuring timely updates and informed decision-making across organizations.
Target Audience
- Data Analysts: Those who need to extract and analyze data from Google Sheets and MySQL databases.
- Developers: Individuals looking to automate workflows involving Google Drive, Google Docs, and LangChain integrations.
- Business Analysts: Professionals aiming to generate insights from technology adoption data and manage strategic directions across companies.
- AI Enthusiasts: Users interested in leveraging AI models for querying and retrieving information from structured and unstructured data sources.
- Project Managers: Individuals overseeing technology adoption projects and requiring automated reporting and updates.
Problem Solved
This workflow automates the process of syncing data from Google Sheets to a MySQL database, ensuring that technology adoption data is always up-to-date. It addresses the challenges of manual data entry and retrieval, allowing users to efficiently manage and analyze technology trends across multiple companies. Additionally, it enables seamless integration with AI agents for advanced querying and information retrieval, enhancing decision-making processes.
Workflow Steps
- Trigger: The workflow is initiated by a webhook that listens for specific events, such as updates to a Google Drive document.
- Data Deletion: It begins by deleting all existing data in the MySQL database to ensure fresh data entry.
- Data Retrieval: The workflow retrieves data from a specified Google Sheet containing technology adoption information.
- Data Transformation: The retrieved data is transformed into a structured format suitable for insertion into the MySQL database.
- Database Insertion: The transformed data is then inserted into the MySQL database, updating the records with the latest information.
- Document Update: If there are any changes in the Google Drive document, the workflow downloads the document and updates the corresponding Google Doc.
- Vector Database Update: The workflow processes the document data to create embeddings and stores them in a Pinecone vector database for retrieval-augmented generation (RAG).
- AI Query Handling: The workflow routes user queries to the appropriate AI agent (RAG or SQL) based on the nature of the query, providing accurate responses using the updated data.