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In today's highly-competitive business climate, immediate access to, and effective analysis of business data can mean the difference between success and failure for an organization. This white paper introduces in-memory computing technology that enables these capabilities.
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Traditional computing systems are built to analyze only structured data, or to run analytics in batch reporting jobs. Explore how Watson is an example of the new kind of workloads that businesses will apply to achieve their business goals.
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Ensuring that business intelligence data is accurate and consistent is crucial to the success of business intelligence (BI) projects. However, managing BI data quality is becoming more challenging as data varieties and sources increase. View this white paper to find out how you can get a handle on BI data quality.
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IBM®ILOG®’s business rule management system (BRMS) is widely used by leading investment banks, asset management and mutual fund firms to meet their compliance requirements while adding intelligent decisioning capabilities to applications and processes throughout the trading cycle, and business channels and systems.
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Learn how alternative methods for replicating changes from an Oracle database to a Hadoop cluster can help you maintain real-time or a near real-time copies of the tables your organization needs to meet its data analytics requirements in this brief from Dell.
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Data doesn't have to be only fact driven and metric. Learn these five best practices to help you make sense and order out of a disparate collection of facts.
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This paper introduces SAP In-Memory Computing technology concepts, explains how SAP HANA uses them to help deliver real-time business insight, and describes how synergies with Intel architecture-based server platforms drive solution value.
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Read this paper to learn how combining a high performance batch programming and execution model with a high performance analytical database provides significant business benefits for a number of different types of applications.
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Security data collection and analysis has become a big data dilemma – so why wouldn't you adopt a big data approach? This resource outlines why legacy analytics and SIEM tools are inefficient and explores how adopting a solution that combines real-time and asymmetric big data security analytics is vital to success.
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This paper discusses the Sybase CEP Implementation Methodology, which offers analytic developers a set of best practices for implementing Continuous Intelligence using Complex Event Processing. Sybase CEP provides a structured yet flexible approach to rapidly build Continuous Intelligence projects and deliver more analytic modules over time.