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SAS empowers modern demand planners with AI-driven tools like SAS Visual Forecasting and SAS Intelligent Planning to meet rising customer expectations through accurate, responsive, and scalable demand planning solutions.
SAS's Kevin Scott explains how to set up and analyze a dataset for forecasting in SAS Viya with a particular emphasis on selecting lags for dynamic models
As part of this year's IEEE Visual Analytics Science and Technology (VAST) Challenge, a group of SAS data scientists puit SAS Viya and related machine learning tools to the ultimate test - to identify individuals in a complex fishing network. Excitedly, the team received the Honorable Mention Award for Breadth of Investigation!
Learn how an intern integrated SAS Viya® and open-source code (Python) into a Machine Learning project to combine their strengths within the context of predictive modeling, and to show off the variety of ways this integration can be accomplished.
Batch manufacturing involves producing goods in batches rather than in a continuous stream. This approach is common in industries such as pharmaceuticals, chemicals, and materials processing, where precise control over the production process is essential to ensure product quality and consistency. One critical aspect of batch manufacturing is the need to manage and understand inherent time delays that occur at various stages of the process.
Empirical Mode Decomposition (EMD) is a powerful time-frequency analysis technique that allows for the decomposition of a non-stationary and non-linear signal into a series of intrinsic mode functions (IMFs). The method was first introduced by Huang et al. in 1998 and has since been widely used in various fields, such as signal processing, image analysis, and biomedical engineering.
The IEEE Visual Analytics Science and Technology (VAST) Challenge provides a great opportunity to validate our software against real-world scenarios using complex data sets. Not only do we learn from these projects, but we also send feedback to our development teams to further improve product capabilities for customers.
The Vehicle Routing Problem (VRP) algorithm aims to find optimal routes for one or multiple vehicles visiting a set of locations and delivering a specific amount of goods demanded by these locations. Problems related to the distribution of goods, normally between warehouses and customers or stores, are generally considered vehicle routing problems. For this article's example, let’s consider a real (and awesome) brewery that needs to deliver beer kegs to different bars and restaurants throughout multiple locations.
Data visualization is a critical way for anyone to turn endless rows of data into easy-to-understand results through dynamic and understandable visuals. Whether your favorite visualization is a pie chart, a geographic map or relies on natural language, showing the insights that empower you to make more informed decisions is a better way to do data-driven business. Analyst firms say that SAS has market-leading data visualization. This helps users across the globe find insights in their data using new and exciting trends in data visualization.
Active gratitude is the feeling you get when a stranger does something nice for you without expecting anything in return. While both are beneficial for our health, there is a statistically significant, positive correlation between active gratitude and pro-sociality (r = 0.374), that is not present with passive gratitude. In other words, random acts of kindness trigger other random acts of kindness to other people, which is both good for us and good for society.
