SAS is a Leader: Gartner 2016 Magic Quadrant for Advanced Analytics Platforms
SAS recognized for completeness of vision and ability to execute
SAS is positioned highest in “ability to execute” among 16 vendors in Gartner’s February 2016 Magic Quadrant for Advanced Analytics Platforms report, which again places SAS in the Leaders quadrant.
Gartner defines advanced analytics as “the analysis of all kinds of data using sophisticated quantitative methods (such as statistics, descriptive and predictive data mining, machine learning, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) – such as query and reporting – are unlikely to discover.”
According to the report, advanced analytics platforms offer an end-to-end environment for development and deployment of models, including:
- Data access to a wide variety of data sources.
- Data preparation, exploration and visualization.
- Ability to develop and build analytic models.
- Ability to deploy models and integrate them into business processes and applications.
- Capabilities to perform platform, project and model management.
- High performance and scalability for both development and deployment.
The SAS “full stack”
Widely known for innovation, SAS’ unique capabilities span a wide set of analytics offerings. Sascha Schubert, SAS Analytics Global Marketing Director, highlighted SAS® software’s sophisticated machine learning and deep learning abilities that integrate well with open source software to meet data scientists’ needs.
“SAS customers benefit from the deepest and most advanced analytics product portfolio on the market,” said Schubert. “Many of our applications and solutions target specific business purposes. Others suit a wider range of applications. Customers in practically every industry use SAS advanced analytics to increase revenue, improve business processes and lower costs.”
SAS is also investing significantly in new architectures such as Hadoop, in-memory processing, cloud integration and large-scale modeling requirements.
Schubert pointed out the challenges posed by a growing deficit of skilled analytics practioners. “Integrating SAS advanced analytics with smart, intuitive user interfaces helps bridge the analytical skills gap with self-service analytical products for business-level users,” he said. “For example, SAS Visual Analytics and SAS Visual Statistics support customer desires to put analytics in the hands of ‘citizen data scientists.’”
SAS advanced analytics also underpin the company’s purpose-built applications such as SAS Fraud Management, SAS Cybersecurity, SAS Asset Performance Analytics, SAS Energy Forecasting, SAS Demand Planning and others.
For more insight on how advanced analytics can boost your organization’s success, please visit the SAS advanced analytics web page.
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