Oracle Advanced Analytics and SAS Enterprise Miner compete in the analytics solutions category, with Oracle excelling in pricing and support, while SAS stands out for its comprehensive feature set.
Features: Oracle Advanced Analytics offers robust integration with Oracle's ecosystem, enhancing data analysis capabilities. It provides powerful data mining features and algorithmic options within the Oracle environment. Its seamless integration with SQL applications allows predictive models to be included in queries. SAS Enterprise Miner offers extensive statistical and machine learning tools. The product features advanced data management and robust data processing capabilities, supporting large datasets effectively. Its interface supports multiple algorithms for model creation and comparison.
Room for Improvement: Oracle Advanced Analytics could enhance the user interface for greater accessibility and improve documentation for non-technical users. Some users suggest better visualization options and expanded algorithm choices. SAS Enterprise Miner might benefit from streamlining its initial setup process. More intuitive guidance for beginners and enhanced integration with non-SAS systems could improve user experience.
Ease of Deployment and Customer Service: Oracle Advanced Analytics benefits from a well-established support infrastructure, ensuring smooth deployment processes. Its simplified deployment makes it user-friendly for existing Oracle users. SAS Enterprise Miner offers detailed documentation and extensive resources, but its setup can be complex, requiring more time and expertise to deploy effectively.
Pricing and ROI: Oracle Advanced Analytics presents a cost-effective solution, particularly for businesses already invested in Oracle systems, offering favorable ROI. SAS Enterprise Miner, although demanding higher setup costs, offers significant returns through its advanced analytical capabilities and the depth of its integrated tools.
Oracle Advanced Analytics 12c delivers parallelized in-database implementations of data mining algorithms and integration with open source R. Data analysts use Oracle Data Miner GUI and R to build and evaluate predictive models and leverage R packages and graphs. Application developers deploy Oracle Advanced Analytics models using SQL data mining functions and R. With the Oracle Advanced Analytics option, Oracle extends the Oracle Database to an sclable analytical platform that mines more data and data types, eliminates data movement, and preserves security to anticipate customer behavior, detect patterns, and deliver actionable insights. Oracle Big Data SQL adds new big data sources and Oracle R Advanced Analytics for Hadoop provides algorithms that run on Hadoop.
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