Table of contents
Comprehensive Suite
SAS Viya offers a wide range of advanced analytics tools, from data management and visualization to machine learning and artificial intelligence, providing a one-stop solution.
Scalability
The platform is designed to scale efficiently, handling large volumes of data and complex analytical processes, suitable for big organizations.
Integration Capabilities
SAS Viya integrates well with various data sources and existing IT infrastructures, making it easy to include in diverse technical environments.
Strong Support and Resources
SAS provides extensive documentation, user communities, and customer support, which can be invaluable for troubleshooting and learning.
Advanced Security Features
The platform includes robust security measures, ensuring that sensitive data is protected throughout analytics processes.
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SAS Advanced Analytics is highly regarded as a powerful and reliable analytics platform, particularly for complex and large-scale data analysis.
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Check the traffic stats of SAS Advanced Analytics on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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SAS Advanced Analytics, part of the broader SAS Viya platform, enjoys a solid reputation in the realms of business intelligence and predictive analytics. It is often highlighted alongside other industry leaders such as IBM SPSS, Tableau, and Alteryx, which shows its prominence in the sector. However, public opinion about SAS Advanced Analytics tends to be multifaceted, reflecting both admiration and constructive criticism.
Robust Analytics Capabilities: Users frequently commend SAS Advanced Analytics for its powerful statistical analysis capabilities and sophisticated predictive modeling features. The suite is particularly valued in industries where precise data analysis is pivotal, including finance, healthcare, and manufacturing.
Comprehensive Solution: Given its integration into the SAS Viya platform, SAS Advanced Analytics offers a comprehensive suite for analytics needs, ranging from data preparation and management to advanced analytics and visualization. This end-to-end solution appeals to organizations seeking to build robust, scalable analytics infrastructure without piecemeal integration of disparate tools.
Reputation for Reliability: SAS’s longstanding reputation in the analytics field engenders a high level of trust among corporate users who depend on reliable and validated analytics products. Many users view SAS as a benchmark for serious data analysis.
Cost Transparency: One frequently noted point in assessments, as evident in its listing in numerous analytic tool reviews, is the lack of transparent pricing information on the SAS website. Potential buyers are required to request demos or get a quote, which can be a deterrent for businesses looking for straightforward, upfront pricing.
Learning Curve: While SAS Advanced Analytics is appreciated for its comprehensive capabilities, it is often critiqued for having a steep learning curve. Professionals who are not experienced in technical analytics or statistical languages may find SAS products more challenging to learn compared to some of the more intuitive tools like Tableau or QlikSense.
Competitive Environment: The competitive landscape for analytic solutions is fierce, with products like RapidMiner and Alteryx often highlighted for user-friendly interfaces and flexible pricing models. These alternatives tend to capture users looking for agile and less complex solutions at potentially lower costs.
In summary, SAS Advanced Analytics is widely respected for its technical depth and reliable performance, making it a preferred solution for sophisticated data analytics tasks. Nevertheless, its opaque pricing model and perceived complexity can be barriers to entry for some organizations. Given the diversity of business intelligence tools on the market, SAS must continue to balance its robust capabilities with greater accessibility and transparency to maintain its standing and attract new users in an increasingly competitive field. This dual challenge frames much of the contemporary public discourse surrounding the platform, as it seeks to meet the evolving needs of the analytics community.
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