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Big Data Analytics White Papers

See the most recent Big Data Analytics whitepapers below.

Find out how your company can promote its content in this library.

Why DBMSs Matter More than Ever in the Big Data Era

Big data promises valuable insights that are enticing organizations to invest in analytics and BI tools. Yet many overlook the need for a DBMS that can stand up to the strain big data places on the underlying infrastructure. This ePaper explores the DBMS characteristics of most importance in a big data setting.


Top Tips for Securing Big Data Environments: Why Big Data Doesn’t Have to Mean Big Security Challenges

Big data environments create significant opportunities. However, organizations must come to terms with the security challenges they introduce. For example big data environments allow organizations to aggregate more and more data—much of which is financial and personal intellectual property or other types of sensitive data. Most of the data is subject to compliance regulations.


Integrating and Governing Big Data

Although the term big data has only recently come into vogue, IBM has designed solutions for decades that are capable of handling very large quantities of data, leading the way with data integration, management, security, and analytics solutions known for their reliability, flexibility, and scalability. The end-to-end information integration capabilities of IBM InfoSphere Information Server are designed to help organizations understand, cleanse, monitor, transform, and deliver data—as well as collaborate to bridge the gap between business and IT.


Big Data Integration and Governance Considerations for Healthcare

This white paper discusses how IBM InfoSphere can support the integration and governance of big data in healthcare. It reviews three case studies, including predictive analytics with electronic medical records, time series data in a neonatal intensive care unit, and predictive pathways for disease.


Next Generation Architecture for Big Data and Analytics

Organizations know they must leverage big data and analytics to outperform the competition, manage risk, create IT agility, and make better decisions. This requires an architecture that capitalizes on all types of data, including real-time information, that expands analytics to include predictive and new cognitive capabilities while also being proactive about privacy, security, and governance.


IBM Data Warehousing: Modern Ecosystems Designed for Big Data and Analytics

Five years ago, IBM observed that the planet was becoming more instrumented, interconnected, and intelligent. Some 20,000 engagements later, here’s what we’ve learned that matters in designing a modern data warehouse.


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