Detail kurzu

Self-Service Data Preparation in SAS® Viya®

EDU Trainings s.r.o.

Popis kurzu

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. 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.

Obsah kurzu

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.

Cieľová skupina

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
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