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SAS® Analytics Management

Manage your analytical models’ life cycles so you get better results that can be used more effectively

Recent studies show that leading organizations are more likely to use information and augment it with predictive analytics to drive superior results. Therefore, it makes sense that if analytics can be applied more pervasively, results would improve even further. Additionally, other factors can improve the accuracy of results generated by your analytic models:
  • Factoring in more variables.
  • Using larger or complete collections of data (instead of samples).
  • Using multiple models for the same analytical project.

While these factors can produce more accurate results, they can also make managing your analytic environment more challenging, which is why analytics management is important. With the increased focus on analytical models as high-value assets comes the realization that predictive models, as well as the underlying data, must be managed for optimal performance throughout their entire life cycles.

SAS Analytics Management provides complete lifecycle management from the data discovery and exploration phase to the test, learn, inform and act phases. With SAS, analysts can easily register, validate, deploy, monitor and retrain analytical models in a minimal amount of time. A more efficient model management process enables organizations to manage a larger number of complex analytical models and make better use of analytics across the organization.

In addition to model management and monitoring, collaboration between constituents in different departments can be facilitated, and models can be constantly tuned for the needs of dynamic environments.

Components of SAS® Analytics Management

How SAS® Is Different

  • Flexible infrastructure supports multiple analytical disciplines for increased agility. SAS Analytics management provides the flexibility to support all types of analytical scenarios. This includes support for a variety of sophisticated analytical disciplines, including data mining, forecasting, text analytics, optimizations, etc., in an integrated manner.
  • Governance and lineage tracking. Tracking lineage from data source to analytic result is critical in situations that are regulated or have strict regulatory reporting requirements.
  • Optimized for big data and high-performance analytics. Only SAS provides the ability to effectively manage models in the context of big data and high-performance environments. SAS can manage large numbers of complex models, take advantage of advanced analytical techniques, and use virtually unlimited numbers of variables and extremely large data volumes.
  • Easy-to-use model management and monitoring tools. With SAS, it is easy to track and monitor models so you can tell which models are still performing and adding value, and which ones are no longer working and should be retired. With integrated data management capabilities, you know your models are being powered by the best, most appropriate data sources.

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Call us at 1-800-727-0025 (US and Canada) or request more information.