Oracle Database 11g Product Family
This white paper provides an overview of the various feature sets available within the Oracle Database family of products. Built using a reliable database architecture, these products provide the necessary foundation to successfully deliver more information with higher quality of service and efficiently manage change within the environment to deliver better value.
Embedding BI Into Your Software Solution: Best Practices
More and more software companies are considering the addition of an analytics module to their product suite. This strategy has compelling business value—analytics can add 20 percent to 30 percent of top line revenue to your organization’s top line. This white paper offers practical advice on how to plan for, build, and ultimately market a business intelligence (BI) and analytics product.
Seven Reasons You Need Predictive Analytics Today
This white paper looks at seven strategic objectives that can be attained to their full potential by employing predictive analytics. Learn why advanced analytics tools can be essential to sustain a competitive advantage.
The seven strategic objectives that can be met with business intelligence (BI) solutions and analytics include competition, growth, and meeting consumer expectations.
The Forrester Wave™: Big Data Predictive Analytics Solutions Q2 2015
Forrester Research evaluated 13 big data predictive analytics solution vendors, with several, including IBM, emerging as analytics software leaders. Learn why in this report.
Rethinking Governance in an Analytics-driven World
Big data and analytics produce fast and accurate insights for many. And businesses which embrace an agile governance framework will ensure insightful and informed business decisions can be made quickly. Those who don’t will be bogged down by an inability to turn large data sets into actionable insights.
Data as a Service: Accelerating Application Projects for Healthcare Payers
Data truly is the lifeblood of any healthcare organization. By its very nature, healthcare data is complex. This complexity is made that much more challenging because healthcare data is fragmented across multiple, disparate systems in numerous structured and unstructured formats.
This paper examines how data as a service (DaaS) can make data more accessible to application development teams, accelerate release cycles, and reduce costs by virtualizing application environments.