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DataViZ, Data Science and Machine Learning White Papers - Part 2

Here are some white papers about IBM and Oracle featuring data science topics:

IBM

  • 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. 
  • Why NoSQL? Your database options in the new non-relational world - Why NoSQL? Your database options in the new non-relational world. The database you pick for your next application matters now more than ever. It can be difficult, and often times impossible, to quickly join today's data into the relational model.
  • IBM Analytics for Apache Spark - IBM Analytics for Apache Spark. Deep, rich, interactive analytics. Intelligent applications. Head-ache free. IBM Analytics for Apache Spark 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.
  • Blending predictive and prescriptive analytics - IBM Whitepaper - Make optimal decisions using integrated predictive and prescriptive analytics. To thrive in today’s complex and ever-changing environment, companies need to gain rapid insights and translate those insights into actions.

Oracle

  • (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.

For more white papers, click here.

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