SAS updates the Viya platform, data management becomes “AI-ready”

The technological strategy adopted plans to overcome the traditional model that requires the transfer of data between different platforms, a practice that generates latency, duplication and governance risks. SAS introduces solutions like SAS SpeedyStore, a high-performance analytics platform that runs AI directly on distributed data, reducing unnecessary travel. The same principle is applied through SAS Data Accelerator, which allows the execution of analytics within the main cloud environments used by organizations, including data warehouses and lakehouse architectures, while keeping the data on site.

The platform also supports analytics engines like DuckDB for local processing of open formats (Parquet, CSV, JSON) in governed workflows. “A modern data platform is now a critical requirement as organizations move to autonomous AI-driven workflows with less human oversight”, said Alyssa Farrell, Senior Director of Data and AI Strategy at SAS. “SAS is redefining data management for the AI ​​era, helping organizations optimize modern data estates, reduce complexity, and unlock the full value of AI, with governance and trust built right into the system foundation”.

A further pillar of the update concerns the integration of agents and co-pilots within the data lifecycle. SAS Viya Copilot for Data Discovery and SAS Viya Copilot for Code Assistance aim to reduce manual effort by enabling natural language dataset exploration and assisted development of SAS and Python code, respectively.

At the same time, the SAS Data Maker function addresses restrictions related to access to sensitive data by generating high-fidelity synthetic datasets, capable of preserving the statistical and relational properties of the originals. This AI-driven care approach aims to ensure that traceability and human supervision are preserved at every stage of operation, from preparation to distribution of the modelsproviding a defensible foundation for enterprise AI