Shadi Shahin, Vice President of Product Strategy, SAS

Work like a disrupter. By becoming both analytically and technologically mature.

Netflix, Airbnb, Spotify and Lyft. How did these market heroes move from the seed of an idea to the disruption of an entire industry? A strong analytics and technology platform that turned data into a fundamental asset.

You may be thinking: We use analytics. We have data scientists. We know the latest machine learning techniques. But are you moving beyond using algorithms to incorporating algorithmic thinking at its core?


Intelligent data preparation

Eliminates the need to manually tag and label data

Using AI algorithms to recognize patterns in data, you can understand what data belongs together and provide context around data. It uses continuous learning to create reason-based algorithms. It can even teach models to learn from other models, and then to retrain the model itself.

Containers for analytics

Essential for deploying software in cloud environments

IT likes to test and run software in containers because they deploy software faster, manage upgrades simply and make it easy to combine different software packages. For software providers, it’s also easier to build packaged deployments, integrate with other packages and add more automation into a system.

Containers will help to democratize the use of advanced analytics and lower the barrier to entry for trying new software products. Shadi Shahin Vice President of Product Strategy SAS

ModelOps for machine learning

Improves time to deployment, ensures quality

Move models from the lab to validation, testing and production as quickly as possible while ensuring quality results. ModelOps helps you manage and scale models to meet demand and continuously monitor them for data fluctuations, model bias and model degradation.

Explore at Every Stage

No matter where you are on the continuum from traditional to disrupter, you can benefit from exploring these technologies.