Eliminate inconsistencies caused by excessive data movement and latency from conventional processes for scoring data. Prevent delays resulting from slow analytical processing. And capture timely insights from big data so you can seize opportunities you would otherwise miss.
Boost model performance.
Automate data-scoring processes for faster insights. Publish analytical models into database-specific functions that are deployed and executed directly within the database environment.
Increase data mining and IT productivity.
Faster deployment frees your analytics team to focus on new projects. By reducing the need to manually revalidate code for your models, you'll incur fewer labor costs.
Streamline analytic deployment.
There's no need to move data between SAS and the database for scoring purposes. This reduces the cost, complexity and latency of the scoring process. And it streamlines your analytic deployment.
Reduce data movement.
Reducing data movement and replication ensures data integrity, which is crucial for data governance. By scoring data inside the database, you can execute programs so that detail data is analyzed without crossing the database boundary.
- SAS format library.
- SAS Enterprise Miner Score Export node.
- Register SAS/STAT linear models to SAS Model Manager.
- SAS Scoring Accelerator publishing client.
- Integrated environment for tracking and monitoring model performance over time.
- Available for multiple data sources, including Hadoop.