SAS Still Dominates the Market After Decades of its Inception

According to the 2016 February report by Gartner, the top slot in execution ability was bagged by SAS and SAS was once again placed in the quadrant of leaders in the Magic Quadrant for Advanced Analytics Platforms. Advanced analytics, according to Gartner, involves various sorts of data analysis through the use of quantitative methods of great sophistication like machine learning, statistics, simulation, data-mining. The report compiled by Gartner further states that the advanced platforms for analytics provide a comprehensive environment which develops and deploys models which include:

• ·         Access to data generated from multiple sources
• ·         Preparing, exploring and visualizing data
• ·         Building and developing models for analytics
• ·         Putting in place models while integrating them with the applications and processes of                   business
• ·         Managing of projects, platforms and models
• ·         Ability to scale up as required and high performance while both deploying and developing

SAS Covers All the Bases-

SAS is widely known for its continuous evolution over a period of time and its unique ability regarding analysis. It is also compatible with various open source tools and is effective in deep learning and machine learning abilities.

According to the majority of experts, SAS provides the best in-depth and advanced analysis of products. SAS has proved to be efficient for specific purposes of business as well as for applications that are wider in range. Its advanced analytics applications are used by customers to increase their revenue and lower the costs incurred by their firm.

SAS has also made important investments in emerging architectures like Hadoop, integration with the cloud, in-memory processing and requirements for modeling on a large scale. It has also solved the lack of skilled professionals by integrating the advanced analytics with intuitive and smart user interface. Because of this, ordinary people can become data scientists with the help of tools like Visual Statistics and Visual Analytics.

It also lays stress on applications with specific purposes like SAS Fraud Management, SAS Asset Performance Analytics, SAS Cyber security, SAS Demand Planning and SAS Energy forecasting among others. Therefore, it can be said that despite its age SAS has managed to remain as effective as ever with the software suite provided by it.

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