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High-Performance Data Processing with CASL in SAS(R) Viya(R)

Course code: CASL01

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.
1 080 EUR

1 307 EUR including VAT

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Course dates

Starting date: Upon request

Type: E-learning

Course duration: 14 hours

Language: en

Price without VAT: 1 080 EUR

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Starting date: Upon request

Type: Upon request

Course duration: 20 hours

Language: en

Price without VAT: 1 800 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
Upon request E-learning 14 hours en 1 080 EUR Register
Upon request Upon request 20 hours en 1 800 EUR Register
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Target group

Experienced programmers interested in efficiently processing big data using SAS Viya

Course structure

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.

Prerequisites

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.

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