Tag: Analytics R&D

Advanced Analytics
Ricky Tharrington 0
Parallel Processing in SAS Viya

Most computers can execute operations in parallel due to their multicore infrastructure. Performing more than one operation simultaneously has the potential to speed up most tasks and has many practical uses within the field of data science. SAS Viya offers several products that facilitate parallel task execution. Many of these

Advanced Analytics
Natalia Summerville 0
Maximize product quality with Optimization and Machine Learning models

Machine Learning models are becoming widely used to formulate and describe processes’ key metrics across different industry fields.  There is also an increasing need for the integration of these Machine Learning (ML) models with other Advanced Analytics methodologies, such as Optimization. Specifically, in the manufacturing industry, SAS explored state-of-the-art science

Advanced Analytics
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Automated linearization in SAS Optimization

Linear programming (LP) and mixed integer linear programming (MILP) solvers are powerful tools. Many real-world business problems, including facility location, production planning, job scheduling, and vehicle routing, naturally lead to linear optimization models. Sometimes a model that is not quite linear can be transformed to an equivalent linear model to reduce

Advanced Analytics
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Mathematical optimization at SAS

Note from Udo Sglavo on mathematical optimization: When data scientists look at the essence of analytics and wonder about their daily endeavor, it often comes down to supporting better decisions. Peter F. Drucker, the founder of modern management, stated: "Whenever you see a successful business, someone once made a courageous decision."