This course provides an overview of the analytic data preparation capabilities of SAS Data Preparation in SAS Viya. 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 when 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 that the data is fit for purpose in analytical models, explorations, and reports

Formats available	Standard Duration (duration can vary, see event schedule for details)
Classroom:	2.0 days
Live Web Classroom:	4 half-day session(s)	System Requirements
e-Learning:	14 hours/180 day license

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.

Data Management in the Analytics Economy

• Overview of SAS Viya and its capabilities.
• Understand the critical capabilities of analytic data preparation.
• Understand the capabilities of SAS Data Preparation to create analytic-driven data.

Discovering, Ingesting, and Exploring Data

• Manage data using SAS Data Explorer.
• Create data source connections.
• Import data from caslibs and files local to the browser.
• Import data from social media.
• Import Esri geoenrichment and geocode data.

Transforming Data into Analytics-Ready Data

• 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.

Understanding and Governing Data and Data Jobs

• Manage and govern data using SAS Lineage Viewer.
• Schedule and monitor jobs and job flows in SAS Viya.