The DataGOL AI Agents empowers business users and engineers to efficiently analyze and visualize data through a suite of specialized AI agents. These agents act as intelligent assistants, guiding users through the data exploration process and accelerating insights.
BI agent allows you to visualize data from structured datasets using various chart types and provides insights through graphical representations of data.
The DC agent helps users to clean and organize their data within a workbook. This includes tasks like deduplication, normalization, data imputation, and filtering.
The DCA enables users to quickly retrieve and analyze data from workbooks using natural language queries. Moreover, the agent also provides tabular results based on SQL queries.
The Python agent is designed to handle more complex data analysis tasks that go beyond basic SQL queries and visualizations. The Python agent is utilized for complex data manipulation tasks that exceed the capabilities of standard SQL queries. Such tasks include generating machine learning code for rapid testing, performing dimensionality reduction using PCA, and conducting anomaly detection with statistical models. Here's a breakdown of its purpose and capabilities:
RAG agents enhance Large Language Models (LLMs) by providing them with access to an external knowledge base, enabling accurate and efficient information retrieval from unstructured data.
The SQL agent in DataGOL is a tool designed to streamline the process of working with SQL by enabling users to interact with databases using natural language. It goes beyond simple query generation by also offering optimization and debugging capabilities for the created SQL.