In this course, you learn to use the SWAT (SAS Wrapper for Analytics Transfer) package to take advantage of the SAS Cloud Analytic Services (CAS) engine in SAS Viya for massively parallel processing (MPP) using familiar Python syntax.
DurationIn this course, you learn to use the SWAT (SAS Wrapper for Analytics Transfer) package to take advantage of the SAS Cloud Analytic Services (CAS) engine in SAS Viya for massively parallel processing (MPP) using familiar Python syntax.
You learn about SAS Viya and the CAS engine, how to leverage the strengths of the CAS engine and your local Python client, how to connect Python to CAS, and how to access and load data into CAS's MPP environment.
You then learn to explore, analyze, and prepare the data on the CAS server, taking advantage of the distributed processing power using familiar Pandas API and CAS actions from the SWAT package.
Lastly, you learn how to return summarized results from the CAS server to your local Python client for additional processing and visualization using native Python packages.
Prerequisites
Before taking this class, you should have experience writing Python programs for data analytics. Familiarity with JupyterLab is a plus but not required. There are no SAS prerequisites.
Our vision and mission are based on the belief that analytics changes the world.Connecting analytics and advocacy to create something new, better, purposeful and lasting.
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We envision a world where everyone can make better decisions, grounded in trusted data and assisted by the productivity and speed of SAS® AI and analytics.
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