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Deploying a Complete, High-Performing Alternative SAS Language Environment

2-part on-demand webinar series

Transforming SAS language, Python, and other modern language technologies into a single, code to no-code analytics platform.

 

Learn how to:

  • Overcome licensing challenges
  • Develop end-to-end analytics workflows
  • Reduce DevOps bottlenecks
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Introduction to Altair Analytics Hub, Workbench and Engine 700x500

Part 1:
An Introduction to Altair SLC™ - a SAS language compiler and execution environment, Altair Analytics Workbench™, and Altair SmartWorks Hub™

  • Identify your team’s data needs and gaps currently preventing seamless, end-to-end analytics
  • Find out how other organizations made the switch to a strategic modern platform and saved costs and resources and preserved existing SAS language investments
  • Learn about how SAS language program capabilities fit into Altair Data Analytics
Altair Analytics Hub, Workbench and Engine 700x500

Part 2:
Establish Better, Safer, Higher-Value End-to-End Analytics: Technical Demonstration and Common Use Cases

Uncover business use cases and common implementation journeys, including

  • Successfully integrating SAS language programs into teams with users of varying skill sets, leveraging drag-and-drop coding or Open Source languages (R, Python, etc.)
  • Governing and centralizing access and credentials for siloed data programs and workflows
  • Deploying end-to-end analytics for on-demand analysis, scheduling, pipelining, and more
  • Help teams using different technologies to collaborate and make the best use of all available technologies
  • Understand how your team can take action to reduce costs and drive data workflow efficiencies

Speakers

Oliver Plaistowe-1

Oliver Plaistowe

Senior Vice President, Enterprise Data Transformation

Oliver Perilli

Oliver Perilli

Sales Manager - Data & AI Altair

Michael Vallely

Michael Vallely

Senior Data Analytics Solutions Specialist Altair

This series is perfect for organizations that need to:
 

    • Enhance governance of in-house analytics and user access to data sources
    • Deploy data analytics as APIs or pipeline
    • Launch, optimize, or audit digital transformation projects
  • CTOs, CDAOs, or anyone responsible for software investments
  • Users of the SAS language, Python, R, SQL, and other modern languages and low-code/no-code software
  • Business users and teams responsible for daily financial reporting, ETL, data prep and analytics, modeling, and DevOps

Watch now