Self-Service Data Preparation in SAS® Viya®

Course code: DIDP1H

This course provides an overview of the data preparation capabilities of SAS Data Preparation in SAS Viya. These data preparation capabilities include bringing data in from a variety of sources, assessing the structure and quality of data, preparing and cleansing the data to be fit for purpose, exploring and monitoring the relationships between objects in your environment, and sharing the data with others to promote collaboration and operational use.

1 080 EUR

1 307 EUR including VAT

The earliest date from 11.12.2025

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Course dates

Starting date: 11.12.2025

Type: Virtual

Course duration: 2 days

Language: en

Price without VAT: 1 080 EUR

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Starting date: Upon request

Type: In-person/Virtual

Course duration: 2 days

Language: en/cz

Price without VAT: 1 080 EUR

Register

Starting
date
Place
Type Course
duration
Language Price without VAT
11.12.2025 Virtual 2 days en 1 080 EUR Register
Upon request In-person/Virtual 2 days en/cz 1 080 EUR Register
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Course description

Learn How To
  • Ingest and blend data from a variety of data sources.
  • Visually assess and profile data with multiple tools for better understanding of quality issues.
  • Restructure and cleanse data without using code.
  • Write SAS code to perform custom processing on your data.
  • Examine relationships between data to assess impact and aid in governance.
  • Create and schedule repeatable workflows to automate time-consuming data preparation tasks.

Target group

Business and data analysts, data miners, data scientists, citizen data scientists, statisticians, and others who interact with data from a variety of sources to perform data discovery, wrangling, blending, and manipulation to ensure that the data is fit for purpose in analytical models, explorations, and reports

Course structure

Overview of Data Preparation in SAS Viya

  • Overview of SAS Viya and its capabilities.
  • Understand the analytics life cycle.
  • Understand the data preparation tools in SAS Viya and how they fit into the analytics life cycle.

Accessing, Importing, and Loading Data

  • Manage data using SAS Data Explorer.
  • Create data source connections.
  • Load and import data from caslibs and files local to the browser.
  • Enrich tables with Esri geoenrichment and geocode data.

Assessing Data Structure and Quality

  • Generate profiles in SAS Data Explorer.
  • Assess data with SAS Information Catalog.

Transforming Data for Analytics

  • Introduction to SAS Data Studio and plans.
  • Use suggestions to prepare data.
  • Prepare data using column transforms.
  • Use custom code to transform and aggregate data.
  • Cleanse data using data quality transforms.
  • Blend data using multi-input transforms.
  • Restructure and filter data using row transforms.

Governing Data and Managing Jobs

  • Monitor object relationships using SAS Lineage Viewer.
  • Schedule and monitor SAS Viya jobs and job flows in the SAS environment.

Prerequisites

No SAS experience or programming experience is required, although you should have some computer experience. Specifically, you should be able to:

  • Log on and off a computer and use a keyboard or mouse.
  • Use a web browser to access information.

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