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Özgün başlık: Now everyone can put data to work
Skip to main content Research Products Business Developers Company Foundation(opens in a new window) Log inTry ChatGPT(opens in a new window) Research Products Business Developers Company Foundation(opens in a new window) Try ChatGPT(opens in a new window)Login OpenAI September 10, 2026 Product Now everyone can put data to work Meet the new Data agent in ChatGPT Work: turn your company’s data into answers, interactive dashboards, and action, just by asking. Install Data agent(opens in a new window)Learn more Loading… Audio 2 Share Connect to the company data and context your business trusts Connect to the company data and context your business trusts Turn questions into analysis and action Built from the tools we use to analyze data at OpenAI Get started with the Data agent Try these prompts Connect to the company data and context your business trusts Turn questions into analysis and action Built from the tools we use to analyze data at OpenAI Get started with the Data agent Try these prompts People across every business have questions that data can answer. Why did sales slow down? Where is spending rising? Which issues threaten renewals in our largest accounts, and what should we fix first? Getting those answers often means waiting for a report or asking someone else to run the analysis. We’re introducing a new Data agent in ChatGPT Work(opens in a new window) to help more people answer those questions themselves.
It connects to your company data, investigates what changed, and builds interactive dashboards you can share. Direct and refine the analysis in one conversation, without writing queries or learning a new analytics tool. Connect to the company data and context your business trusts The Data agent connects to approved data sources including Amazon Redshift, Datadog, Google BigQuery, ClickHouse, Databricks, MongoDB, Snowflake, and more. It can also bring files and documents from Google Drive and SharePoint into the analysis. It uses your organization’s business terms, metric definitions, custom calculations, and data relationships to interpret the data. This context comes from semantic layers and trusted sources such as Databricks Genie Ontology, dbt, GitHub, Snowflake Horizon, and BI dashboards.