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. 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.
Learn How To
Connect to the CAS server in SAS Viya using Python.
Manage data on the CAS server.
Access, explore, prepare, and summarize data on the CAS server using a variety of CAS actions and familiar Pandas API from the SWAT package.
Move data between the CAS server and the Python client.
Who Should Attend
Data analysts with open-source experience who want to take advantage of the Cloud Analytic Services engine (CAS server) in SAS Viya for massively parallel processing using familiar Python syntax
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.
SAS Products Covered
SAS Viya overview.
Getting started with Python integration to SAS Viya. Accessing and Managing Data
Loading data into memory.
Promoting tables. Exploring, Analyzing, and Preparing Data
Exploring CAS tables.
Analyzing CAS tables.
Preparing CAS tables.
Executing SQL in CAS.Doing More with Python and SAS Viya