In this course, you learn how to leverage SAS Cloud Analytics Services (CAS), the high-performance, in-memory analytics and distributed computing engine in SAS Viya. You learn how to access, explore, prepare, analyze, and summarize data using the native CAS programming language (CASL). CASL is a new scripting language designed to support the entire analytics life cycle.

This course can help prepare you for the following certification exam(s): SAS® Viya® Programming Specialist.

Learn how to

• Understand and use various SAS Viya servers.
• Leverage the CAS language to manipulate data and automate processing.
• Connect to the CAS server to access and manage data.
• Explore and validate data.
• Manipulate and update data.
• Programmatically create reports and visualizations using SAS Viya and the SAS Output Delivery System (ODS).

Who should attend

Experienced programmers interested in efficiently processing big data using SAS Viya

Formats available	Standard Duration
Classroom:	3 days
Live Web Classroom:	5 half-day session(s)	System Requirements
e-Learning:	21 hours/180 day license	System Requirements

Before attending this course, you should have the following:

• An understanding of fundamental computer programming concepts.
• At least one year of programming experience with a modern language: (SAS, R, Python, SQL, and so on).
• At least one year of experience working with data.
• Experience using an integrated development environment (IDE) to develop code.

This course is not appropriate for inexperienced programmers or users who do not have experience programming or working with data.

This course addresses SAS Viya software.

Introduction

• Introduction.

CAS Language (CASL) Fundamentals

• Introduction to CASL.
• CASL CAS actions.
• CASL numeric and string variables.
• CASL arrays.
• CASL dictionaries.

Connecting to CAS and Accessing Data

• Exploring the CAS connection.
• Exploring and accessing data sources.
• Managing in-memory tables.

Exploring and Validating Data

• Exploring table structure.
• Characterizing data.
• Validating data.

Preparing Data

• Introduction to data preparation.
• Modifying tables and values.
• Data preparation actions.
• Using SQL in CAS.

Summarizing and Analyzing Data

• Introduction to summarizing and analyzing.
• Summarizing data with actions.
• Visualizing and reporting.
• Getting the best performance.