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DataGOL Documentation

website·Indexed 32 days ago

https://docs.datagol.ai

Documentation for DataGOL, a data platform featuring a Lakehouse for data source connection and orchestration, BI Analytics with custom formulas and widgets, and a SQL Playground for data retrieval. Includes guides on connecting SaaS sources like Shopify, Salesforce, and GitHub, as well as reference materials for Apache Spark formulas and RAG-based knowledge base connectors.

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What's inside DataGOL

  1. Overview of the Knowledge Graph agent

    The Knowledge Graph agent extracts structured information from documents (such as PDF and Word files) by transforming content into a network of entities and relationships. This allows users to perform complex queries using AI, which converts natural language questions into Cipher queries to retrieve data from a Neo4j database.

  2. Overview of HubSpot agent capabilities

    The HubSpot agent is an AI-powered tool that interacts with the HubSpot CRM in real-time. It enables users to perform the following tasks using natural language commands:

    • Retrieve CRM data: Fetch specific information such as leads created within a certain timeframe, high-conversion leads, or leads from specific channels.
    • Generate insights: Analyze CRM data to provide recommendations and probability scoring for leads.
    • Create leads: Create new leads in HubSpot. The agent provides a preview of the lead information for review and modification before final creation.

  3. Overview of Lakehouse Architecture

    Lakehouse is a hybrid data architecture that provides a unified platform for storing diverse data types—including structured, semi-structured, and unstructured data—while enabling advanced analytics capabilities.

  4. Overview of the Salesforce agent

    The Salesforce agent is an AI-powered assistant that integrates with Salesforce CRM to allow users to interact with data and execute operations using natural language. Key capabilities include:

    • Natural language understanding: Translates plain English commands into Salesforce actions.
    • Intelligent data retrieval: Fetches leads, contacts, accounts, opportunities, and summaries.
    • Direct action execution: Creates new accounts, contacts, leads, and opportunities.
    • Action preview: Provides a review and modification step for critical actions (like record creation) before they are committed to Salesforce.

  5. Overview of DataGOL cloud storage integration

    DataGOL integrates with AWS and Azure cloud storage. By default, the platform uses its own managed AWS and Azure resources for storage to provide immediate operation. Users also have the flexibility to configure and use their own primary data locations in either AWS or Azure.

  6. Overview of AS OF Time Travel in DataGOL

    The 'AS OF' feature allows users to explore data as it existed at a specific point in time. This is achieved by introducing parameters (such as dates or timestamps) into pipelines—typically via a WHERE clause—which are then managed at the orchestration level. When an orchestration is executed, the system prompts for these parameter values, ensuring that all interconnected pipelines in that workflow operate on the same consistent historical data version.

  7. Overview of D.A.V.E. AI Agent

    D.A.V.E. (Data Analytics and Visualization Engineer) is an intelligent AI agent that translates plain-language questions into data insights. It automatically determines the most effective way to answer a query by choosing between SQL-powered analysis, data tables, or interactive visualizations, removing the need for users to manually write SQL or configure dashboard widgets.

  8. Overview of the Datagol Playground

    The Playground is an interactive environment designed for data exploration. It allows users to connect to various data sources and explore the information they contain in a flexible, exploratory manner.

  9. Overview of the DataGOL Platform

    DataGOL is an AI-native Data and Agents platform designed to deploy governed AI agents on enterprise data. It consists of two primary components:

    1. DataOS: Enables the agentic creation of semantic data models and context using both structured and unstructured data.
    2. AgentOS: A composable AI platform built on top of DataOS that accelerates the creation of AI agents using multi-agent orchestration. These agents can be used internally or embedded into external client products.

  10. Overview of the Data Conversation Agent (DCA)

    The Data Conversation Agent (DCA) is an intelligent agent that allows users to analyze and interact with data using natural language queries. It provides contextual awareness across different workbooks within the same workspace and can generate dynamic results including tables, charts, and text-based responses.

  11. Overview of the Datagol Visualizer for BI Analytics

    The Visualizer is the Business Intelligence (BI) component used to transform raw data into actionable insights through data visualization. It builds upon 'workbooks'—which are curated and transformed data layers derived from connected data sources via pipelines and orchestrations—to create widgets and tables for data-driven decision-making.

  12. Overview of DataGOL AI Agents

    DataGOL AI agents are specialized intelligent assistants designed for business users and engineers. They facilitate the efficient analysis and visualization of data by guiding users through the data exploration process to accelerate the discovery of insights.