Here are some white papers about IBM and Oracle featuring data science topics:
Data Science Methodology: Best Practices for Successful Implementat... - In the domain of data science, solving problems and answering questions through data analysis is standard practice. Often, data scientists construct a model to predict outcomes or discover underlying patterns, with the goal of gaining insights. Organizations can then use these insights to take actions that ideally improve future outcomes.
IBM Analytics for Apache Spark - IBMAnalytics for ApacheSpark. Deep, rich, interactive analytics. Intelligent applications. Head-ache free. IBMAnalytics for ApacheSpark is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to other technologies on the market today.
(White Paper) Six Patterns of Big Data and Analytics Adoption - The Importance of the Information Architecture. In this white paper, IDC describes lessons learned from interviews and surveys of organizations engaged in Big Data initiatives and the patterns of adoption they have followed to expand existing or initiate new Big Data projects to create value for their organizations.
White Paper: Thriving in the Age of Big Data Analytics and Self-Ser... - Turn the technology disruption into innovation: - Engage with the data: free new users to explore any data with simple yet stunning visuals. - Make big data easier: simplify the process of working with diverse new data in Hadoop. - Protected and govern any critical data: ensure that the right people have access to the right data at the right time.