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Still stuck in legacy warehouses? This pharma leader shows how a Databricks lakehouse can turn compliance hurdles into a growth engine.
The new data lakehouse is billed as a single platform for multiple use cases including transactional, agentic, decision support, model training and tuning, and more.
The acquisition will enable enterprises to build agents that can leverage real-time data to make better decisions while acting autonomously, the company said.
Want smarter, faster decisions? A metrics layer keeps everyone on the same page with consistent, reliable numbers.
AI systems need humans to guide them with the unique enterprise history, policies, changes, and institutional knowledge before they can produce real business value.
Also adds a new code interpreter to its conversational analytics agent in Looker to help business users perform more complex data analytics in natural language.
The preview feature aims to simplify real-time analytics on transactional data, reducing ETL complexity and boosting performance.
Stream processing engine allows users to define and manage AI models in Java, Python, and Flink SQL and invoke them in real time within Flink SQL.
The new toolset, though, can only be implemented in combination with Google’s Agent Development Kit and MCP Toolbox for Databases.
Now in public preview, Snowpark Connect promises to reduce latency and complexity by moving analytics workloads where the data is.