Today’s data teams face escalating demands driven by AI adoption, governance complexity, and increasing regulatory oversight. To help meet these demands, CLAIRE GPT now utilizes CLAIRE agents for efficient autonomous data management.
CLAIRE agents harness advanced AI reasoning and planning models to automate complex data operations that range from data ingestion and lineage tracking to data quality assurance. CLAIRE agents redefine how you interact with Intelligent Data Management Cloud services. Instead of an interface built around specific tasks, the new experience dynamically adapts based on the current context, giving you a more conversational, personalized, and fluid experience to achieve the goal at hand. Each agent is designed to excel at specific aspects of data management, working together to deliver comprehensive solutions.
You can use the following CLAIRE agents for autonomous data management with complex prompts:
•Discovery agent
•Data quality agent
•Data integration agent
•Product help agent
Discovery agent
The discovery agent helps you quickly identify relevant, trusted, and compliant data assets for analytics. The agent performs tasks autonomously, make decisions and interact with the large language model through specific skills to achieve a specific goal with human intervention in case of any ambiguity. This agent can perform data discovery, metadata discovery, data exploration, and metadata exploration.
The discovery agent has the following skills:
•Data discovery. Helps you quickly and easily find assets across Intelligent Data Management Cloud services.
•Metadata exploration. Helps you search and explore the metadata of assets.
•Data exploration. Helps to understand the quality and shape of your source data.
For more information about the discovery agent, see Discovery agent.
Data quality agent
The data quality agent continuously monitors and remediates the data quality of assets in the catalog. The agent can assess and diagnose the data quality of assets, summarize data, identify outliers, perform data profiling on demand, and recommend and accept data quality rules.
The data quality agent has the following skills:
•Data quality assessment. Helps you discover and analyze assets based on data quality scores, status, or any specific data quality criteria. You can identify outliers in your data by asking for a detailed summary that includes a comprehensive data profile such as data type, statistics, and null and distinct values.
•Data quality diagnosis. Helps you diagnose the data quality of assets to gain additional insights into your assets. You can identify and remediate the root cause of data quality issues.
•Data quality rule recommendation. Helps you get recommendations for data quality rules for assets that don't have rules associated with them. You can accept recommended rules to instantly create data quality rule occurrences for the data elements in your catalog.
For more information about the data quality agent, see Data quality agent.
Data integration agent
The data integration agent simplifies data transformation by generating ELT pipelines.
The data integration agent has the data transformation skill. This skill is used to generate mappings.