With SAS®, your modelers can be 100x more efficient.

Decisions based on smarter, faster analytical models are what truly differentiate an organization.

From declining a credit card transaction for risk or fraud, to loan approval, product quality control and anything where data plays a role, automated analytical models are what drives digital transformation.

The steps from data to discovery to deployment are a continuous loop in the analytics life cycle, driven by teams of business analysts, data scientists and development operations experts.

With time-to-value always in mind, one goal is to intelligently automate and speed up processing wherever possible. One key aspect of solving the processing problem is called massively parallel processing (MPP), which increases the speed of running analytical models through large complex data, allowing your modelers to be up to 100x more efficient.


Quickly and efficiently access and prepare trusted data

With SAS, successful organizations have proven data management technology powering every process. Modularized for rapid results. Designed with IT and business collaboration in mind. And ready to help transform analytics into opportunity.  Read more about our solutions for data access and integration, data quality, data preparation and data governance.


Transform data into intelligence faster

SAS embeds AI capabilities in our software to provide you with more intelligent, automated solutions. From machine learning, to computer vision, to natural language processing (NLP), to forecasting and optimization, our breadth and seamless integration of AI technologies support diverse environments and scale to meet changing business needs.


Rapidly deploy models in minutes, not months

By operationalizing analytics, you can literally drive better decisions per second. With SAS, you can deploy a single analytics platform in any IT environment. Create routine analysis that continuously monitors model performance and health. Centralize analytic asset governance. And integrate business rules that allow you to respond in real time.

SAS helps make organizations exponentially more efficient, and productive. How?

  • We have automated repetitive steps across the analytics life cycle and the entire analytics process.
  • We have packaged best practices into intelligent templates that data scientists can use and customize for rapid prototyping.
  • We can increase the speed and productivity of data science teams by enabling analytical workloads to run in massively parallel processing (MPP) environments – allowing modelers to be 100x more efficient.
  • By automatically generating natural language to explain findings in the data, we ensure that analytics automation helps everyone in the organization become more productive.
  • Model Deployment: With SAS, you can register and deploy analytical models with one click for instant value, avoiding months of recoding for operational environments.
  • Model Health: SAS ensures your models are in optimum health at all times. With efficient model processing and governance, you can easily compare and test analytical models, generate performance benchmarking reports and alerts, and send workflow notifications.

The Analytics Life Cycle


There’s an easy button for data science. (Well, pretty close anyway.)

Data Science Pilot Action Set allows you to move from a data set to a deployable model with much greater ease – providing actions such as automating data science workflows, including automatic machine learning pipeline exploration, execution and ranking.   Included with SAS Visual Data Mining and Machine Learning (VDMML), the pilot consists of seven actions that implement a policy-based, configurable, and scalable approach to automating data science workflows.