Oracle Advanced Analytics and IBM SPSS Modeler are competitors in data analytics. IBM SPSS Modeler appears superior due to its comprehensive features and usability.
Features: Oracle Advanced Analytics integrates tightly with Oracle's ecosystem, offers robust data management, and excellent predictive analytics leveraging Oracle databases. IBM SPSS Modeler provides an intuitive drag-and-drop interface, a wide array of statistical and machine learning algorithms, and easy data manipulation, making it suitable for various scenarios.
Room for Improvement: Oracle could enhance its user interface and offer more flexible deployment options. It might also expand its suite of algorithms. IBM SPSS Modeler can improve visualization capabilities, enhance integration for governance, and reduce the need for additional software for advanced data visualization.
Ease of Deployment and Customer Service: IBM SPSS Modeler supports flexible deployment both on-premises and cloud-based, adapting to various IT environments. Oracle Advanced Analytics is preferred within Oracle-centric infrastructures. Oracle offers comprehensive support via a global network, while IBM provides specialized analytical support teams.
Pricing and ROI: Oracle Advanced Analytics involves higher setup costs but promises a strong ROI within an Oracle environment. IBM SPSS Modeler's pricing may be higher, yet its broader applicability and integration ease make it a lucrative investment for diverse business requirements.
IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.
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https://www.ibm.com/products/spss-modeler/pricing
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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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