Watsonx.data is a fit-for-purpose data store optimized for governed data and AI workloads, designed to help enterprises scale their analytics and AI capabilities.

With watsonx.data, users can quickly connect to data sources, get trusted insights and lower data warehouse costs.

The tool is optimized for all data, analytics and AI workloads and features an open, hybrid and governed data store that allows users to access and share data.

Watsonx.data includes a shared metadata layer to access all data through a single point of entry, and built-in governance, security and automation to enhance trust in data.

The tool enables users to reduce the cost of their data warehouse by up to 50% by optimizing costly data warehouse workloads across multiple query engines and storage tiers.

Watsonx.data supports a range of fit-for-purpose query engines, including Presto, Spark, Db2 and Netezza, which dynamically scale up and down to drive analytics costs down.

Users can store vast amounts of data in vendor-agnostic open formats, such as Parquet, Avro and Apache ORC, and share a single copy of data across multiple query engines using Apache Iceberg table format and shared metadata.

The tool includes semantic automation to help users discover, augment, refine and visualize watsonx.data and metadata through the power of watsonx.ai models.

Watsonx.data enables enterprises to build, train, tune, deploy and monitor trusted AI models for mission-critical workloads with data in the lakehouse and ensure compliance with lineage and reproducibility of data used for AI.

Watsonx.data helps streamline data engineering, reduce data pipelines, simplify data transformation and enrich data for consumption using SQL, Python or an AI-infused conversational interface.

Finally, Watsonx.data enables enterprises to support self-service access for more users to more data while enabling security and compliance with centralized governance and local automated policy enforcement.