SAS^® In-Database

SAS In-Database processing is a flexible, efficient way to leverage increasing amounts of data by integrating select SAS technology into databases or data warehouses. It utilizes the massively parallel processing (MPP) architecture of the database or data warehouse for scalability and better performance. Moving relevant data management, analytics and reporting tasks to where the data resides is beneficial in terms of speed, reducing unnecessary data movement and promoting better data governance. For decision makers, this means faster access to analytical results and more agile and accurate decisions.

Components of SAS^® In-Database

• Scoring Acceleration – High-performance model scoring with faster time to results.
• Analytics Acceleration for Teradata – Improve data governance on predictive analytics projects and produce faster, better results.
• In-Database Analytics with a Teradata Enterprise Data Warehouse – Develop and deploy SAS Analytics with the Teradata Enterprise Data Warehouse platform.

How SAS^® Is Different

• SAS has taken an industry lead in promoting in-database analytics as an emerging best practice for high-performance analytic deployments. Customers are receiving huge benefits from our integrated road map with databases and data warehouses.
• SAS supports flexible development and deployment of models (analytic data preparation, model creation and scoring) on a wide range of data warehouses and databases to support in-database analytics in a massively parallel processing environment.
• SAS In-Database addresses the challenges of the management and provisioning of data and the time constraints associated with moving large volumes of data by improving the integration between SAS and the databases or data warehouses.