SAS High-Performance Analytics
Big Data Requires Fast, Powerful Analytics
Analyzing Big Data is a complex, multifaceted endeavor, characterized by extreme data volumes, high velocity, and a broad variety of data generated by people, machines, and the Internet of Things. These characteristics break current models of data management, experimentation, and analysis. As a result, many attempts to analyze big data falter as they encounter:
- Reduced ability to develop and test timely new models and analytical applications.
- Reduced accuracy, caused by over-reliance on subsets rather than detailed data.
- Increased resource contention between teams sharing an analytical infrastructure.
- Reduced analyst productivity and increased backlog, caused by system delays.
SAS users are not immune. In fact, due to their analytical maturity, many SAS users encounter these challenges early in their analysis and come to view them as the critical issues in delivering on the promise of big data analytics using SAS.
For companies that are using SAS to embrace big data analytics, scaling the SAS infrastructure is critical to effectively deriving business value from big data.
Big Data Meets its Match
To meet the challenges of big data analytics, SAS and Pivotal have joined forces to drive innovations that deliver big data agility to SAS users. SAS High Performance Analytics for Pivotal accelerates the performance and capacity of SAS, enabling users to embrace big data in their analytical applications while accelerating the pace of model development, testing, and execution. Having analytical agility enables developers to build increasingly accurate models that deliver business value from big data and lead to timely business decisions.
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