Data Preparation on the SAS Viya Open Analytic Platform

This course provides an overview of the analytic data preparation capabilities of SAS Data Preparation on the SAS Viya platform. These self-service data preparation capabilities include bringing data in from a variety of sources, preparing and cleansing the data to be fit-for-purpose, analyzing data for better understanding and governance, and sharing the data with others to promote collaboration and operational use.

Learn how to

• ingest and blend data from a variety of data sources
• visually analyze and profile data for better understanding of quality issues
• collaborate and share data on data management projects
• wrangle data in a self-service data preparation environment with no coding skills
• leverage custom SAS code preparing analytic-driven data
• examine relationships between data to assess impact and aid in governance
• create and schedule repeatable workflows to automate time-consuming data preparation tasks.

Who should attend

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 the data is fit-for-purpose in analytical models, explorations, and reports.

Formats available	Duration
Classroom:	2.0 days
Live Web Classroom:	4 half-day session(s)

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.

This course addresses SAS Viya software.

Introduction to SAS Viya and SAS Data Preparation

• overview of the SAS Viya platform and its capabilities
• understand the critical capabilities of analytic data preparation
• understand the capabilities of SAS Data Preparation to create analytic-driven data

Collaborate on Data Management Projects

• understand the fundamental requirements of a data socialization platform
• create a data management project to promote data reuse, consistency, and team collaboration

Discover, Ingest, and Explore Data

• understand best practices and effective data ingestion considerations for exploring data
• ingest and filter data from a variety of sources, including SAS data sets and social media
• profile data to better understand the quality and structure

Self-Service Data Preparation for Analytics-Ready Data

• create and manage target tables and their columns
• cleanse data using data quality transforms that leverage the SAS Quality Knowledge Base (QKB)
• create data preparation plan files to track, view, and modify changes made to data

Transform Data into Analytics-Ready Data

• manage and aggregate target table columns
• leverage SAS functions and CAS action sets
• cleanse data using data quality transforms and the SAS Quality Knowledge Base
• filter and transpose table data rows
• create data preparation plan files to track and schedule data preparation tasks