Ask the Expert Webinar Series

Tips and Tricks For Better Forecasting With SAS®

On-Demand • Cost: Complimentary

About the webinar

Join this webinar to learn the importance of data preparation prior to forecasting.

We will showcase effective methods to tackle common data issues to enhance forecasting results.

Examples for time-series data preparation techniques will be shown using a programming approach in SAS as well as automated methods in the UI of SAS Visual Forecasting.

This session is great for multiple skill levels.

Beginners will understand the importance of data manipulation prior to forecasting, and more advanced users will see how to manipulate the data using SAS programming as well as automated data preprocessing using SAS Visual Forecasting.

In preparation for this session, make sure to watch the presenters’ previous on-demand webinar, An A to Z Overview of Forecasting in SAS.

You will learn:

  • How to perform feature engineering for time series forecasting.
  • SAS programming techniques for time series forecasting-related data preparation.
  • The difference in data preparation when applying time series versus machine learning methods.
  • How to automatically perform data manipulation tasks in SAS Visual Forecasting UI.

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About the Experts

Gerhard Svolba
Advisory Presales Solutions Architect, SAS

Gerhard Svolba is an analytic solutions architect and data scientist at SAS in Austria. He 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, he teaches data science methods at the University of Vienna and the Medical University of Vienna.

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, Spiros worked and led advanced analytics teams in various sectors such as credit risk, customer insights and CRM.