SAS Visual Forecasting Software
Generate large numbers of trustworthy forecasts, quickly and automatically, using time series and machine learning techniques.
Plan better for the future with a fast, configurable, open and future-proof forecasting tool that you can trust.
Streamline and automate your forecasting process.
Automatically generate, visualize and deploy reliable forecasts at scale – without human involvement. Reduced manual intervention means there's less chance of introducing personal bias in the forecasting process. Because forecast analysts don't have to build and monitor forecasting models for every time series, they can focus on more strategic, high-value forecasts or problems that aren't suitable for automation. At the same time, more experienced forecasters can develop and share the modeling strategies and pipelines they configured for use by other areas of the business.
Produce accurate forecasts at scale for better planning.
Automatically partition data into segments of similar time series based on the nature of the data. Then apply the most effective modeling technique to each group using time series, machine learning and hybrid techniques.
Empower open source users.
Provide data science teams the option of scaling popular open source algorithms in Python and R by distributing them to run in parallel in the cloud. SAS Visual Forecasting provides an open and extensible framework that integrates and parallelizes algorithms, making them shareable and reusable in a governed and consistent way.
Incorporate external drivers and business knowledge.
Business drivers, holidays or events that affect the forecasting process are selected automatically from variables supplied to the system. Using a simple user interface, you can also override the system’s results based on actual business knowledge to further improve forecasting accuracy. Manage changes based on specific filters you define as part of the same ecosystem.
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Try the latest SAS Viya capabilities.
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SAS Visual Forecasting provides an open forecasting ecosystem for quickly and automatically producing a large number of reliable forecasts.
Data access, preparation & quality
Access, profile, cleanse and transform data using an intuitive interface that provides self-service data preparation capabilities with embedded AI.
Visually explore data and create and share smart visualizations and interactive reports through a single, self-service interface. Augmented analytics and advanced capabilities accelerate insights and help you uncover stories hidden in your data.
Automatic time series analysis & forecasting
Several function packages perform specific tasks in the time series analysis process. Convert time-stamped transactional data into a time series format, then generate forecast models automatically.
Machine learning & deep learning
Incorporate neural networks (NNs), recurrent neural networks (RNNs) and hybrid techniques (NNs + time series) in the forecasting process to model even the most challenging series. Generate features and automatically transform transactional data into the right format to eliminate manual, labor-intensive feature engineering prior to using these sophisticated techniques.
Parallelize open source algorithms
Integrate and parallelize Python and R algorithms to run in the cloud using a well-governed and consistent framework. Empower open source users to scale their code to run in lightning speed in a distributed way using SAS Viya’s worker nodes in the cloud.
Automatically segment data based on demand-classification attributes, such as volume and volatility, using a prebuilt template and model each segment separately in the project pipelines. Or import custom segments based on your business knowledge. Apply the most appropriate forecasting technique based on the nature of the data and significantly improve the quality of your forecasts.
Add events to models
Model the effect of events (holidays, retail promotions, natural disasters, etc.) on dependent time series to improve model accuracy. The solution includes default prebuilt events (e.g., major holidays), and you can add others from an external event repository.
Analyze individual time series, compare models visually and develop custom models for individual time series via a simple user interface. Assess and evaluate models with automatically generated diagnostic plots and tables, and select your own model champions.
Highly flexible forecast override
Make customized adjustments to specific filters or groups of time series defined by attributes, not just by hierarchical variables, using a powerful manual override capability via a simple user interface.
Model and forecast each series in a hierarchy individually, then reconcile top-down at multiple levels. Adjust a forecast at any level, and apportion it to lower levels to keep the hierarchy consistent. Individual forecasts (by products, locations, etc.) roll up to the top number.
Additional forecasting & econometrics procedures
Address virtually any forecasting and time series analysis challenge with access to SAS/ETS® and SAS Forecast Server procedures.
Support for APIs & other programming languages
Use the broad range of built-in forecasting models, and/or customize models that work well with your data. Use public REST APIs to add SAS Analytics to other applications. Call analytical actions, procedures and APIs from SAS, Python, R, Java and Lua.
Scripting language for distributed processing
A scripting environment supports fast, in-memory time series analysis. The scripting language is optimized and compiled for the machine it's running on – no need to rewrite code for different machines.
SAS Viya's architecture is compact, cloud native and fast. Whether you prefer to use the SAS Cloud or a public or private cloud provider, you'll be able to make the most of your cloud investment.
Available on Your Preferred Cloud Provider
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