Ask the Expert Webinar Series

An A to Z Overview of Forecasting in SAS®  

On-Demand • Cost: Complimentary

About the webinar

Join this webinar to learn how you can build time series forecasting models with SAS, allowing you to automatically generate large quantities of high-quality forecasts.

Our experts will give software demos showing how to use SAS procedures like PROC ESM, PROC ARIMA or PROC TIMESERIES to prepare your data and produce forecasts.

Get an overview of SAS Model Studio, a low-/no-code environment that allows you to perform automated forecasting at scale using time series and machine learning algorithms. It also lets you segment your time series into groups in the modeling phase and distribute open source algorithms to run in parallel in the cloud.

This session is great for all skill levels. Beginners will see how to produce time series forecasts with SAS procedure calls. Advanced users will learn how to run their forecasting and machine learning models on many time series in an automated way.

You’ll get tips for how to quality check and prepare your time series data as well as how to integrate open source algorithms into forecasting pipelines.

You will learn:

  • How to program time series analysis in SAS.
  • What procedures are available and how can they be used.
  • How forecasting can be performed automatically in SAS with no or little coding and be put into production effectively.
  • How to scale your open source algorithms to run in a distributed manner in the cloud.
  • Why time series analysis is more than just specifying a certain model. Data preparation and exploring the time series are important as well.

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About the Experts


Gerhard Svolba
Advisory Presales Solutions Architect, SAS

Gerhard Svolba is involved in numerous analytic and data science projects in different business and research domains, including demand forecasting, analytical CRM, risk modeling, fraud prediction and production quality. His project experience ranges from business and technical conceptual considerations to data preparation and analytic modeling across industries. He is the author of the SAS Press books Data Preparation for Analytics Using SAS, Data Quality for Analytics Using SAS and Applying Data Science: Business Case Studies Using SAS. As a part-time lecturer, Svolba teaches data science methods at the University of Vienna, the Medical University of Vienna and for business schools.


Spiros Potamitis
Senior Product Marketing Manager, SAS

Spiros Potamitis is a data scientist and a Global Product Marketing Manager of forecasting and optimization at SAS. He has extensive experience in the development and implementation of advanced analytics solutions across different industries and provides subject matter expertise in the areas of forecasting, machine learning and AI. Prior to joining SAS, Potamitis has worked on and led advanced analytics teams in various sectors such as credit risk, customer insights and CRM.

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