In today's data-driven business environment, data analysis has become a key part of business decision-making. The Metad Analytics Cloud provides you with an intelligent data query experience, through its powerful AI copilot function based on ChatGPT, you can more efficiently query, optimize and interpret data. This article will introduce in detail how to turn on and configure the AI copilot in the Metad Analytics Cloud, and how to use the AI copilot in the Query Lab to improve the efficiency of data query.
Query Lab provides the function of flexibly operating the data source entity (physical table view or multi-dimensional data set) by using SQL query statement, which helps users in their daily data operation and maintenance work. The query lab is built in the semantic model workspace and operates and queries data through the data sources connected by the semantic model. If the user's data source is public network accessible, you can create a data source in the metad analytics cloud to connect query. If the user's data source is deployed in the private network, you can use the desktop agent to connect and query.
Next, this article will introduce how to turn on and configure AI copilot and use it to assist in querying the data sql in the laboratory, optimizing and explaining.