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A collection of big data white papers reviewed by the editors of insideBIGDATA. Please visit the insideBIGDATA White Paper Library for a comprehensive list of white papers focus on big data strategies.

The Hidden Costs of Open Source

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While Linux clusters dominate HPC, there are many issues related to cost and complexity that can make open-source solutions challenging. In addition, determining real costs can be complex because every environment is different, and organizations will assess costs using their own methodologies and based on their own requirements and capabilities.

Top 5 Challenges for Hadoop MapReduce in the Enterprise

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Now that MapReduce is becoming accepted as a ‘working’ model, the next goal is to turn it into an enterprise-class solution. IBM has written a technical white paper for overcoming common challenges when deploying Hadoop MapReduce – “Top 5 Challenges for Hadoop MapReduce in the Enterprise.”

Deploying a Big Data Solution Using IBM GPFS-FPO

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Download this whitepaper today to learn best practices for deploying GPFS-FPO as a file system platform for big data analytics. The goal of this paper is to guide the administrator through various decision points to ensure optimal configuration based on the Hadoop application components being deployed.

Bridging the MapReduce Skills Gap

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Data is exploring at large organization. So is the adoption of Hadoop. Hadoop’s potential cost effectiveness and facility for accepting unstructured data is making it central to modern, “Big Data” architectures. Yet, a significant obstacle to Hadoop adoption has been a shortage of skilled MapReduce coders.

GridGain In-Memory Data Fabric

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This article is the fifth and last in an editorial series that will provide direction for enterprise thought leaders on ways of leveraging in-memory computing to analyze data faster, improve the quality of business decisions, and use the insight to increase customer satisfaction and sales performance.

Big Data for Finance – Security and Regulatory Compliance Considerations

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This article is the fifth and last in an editorial series that has the goal to provide direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively in today’s climate of working to increase the value of corporate data assets.

In-Memory Computing Performance Benchmark

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This article is the fourth in an editorial series that will provide direction for enterprise thought leaders on ways of leveraging in-memory computing to analyze data faster, improve the quality of business decisions, and use the insight to increase customer satisfaction and sales performance. In last week’s article, we set the stage for in-memory computing technology in terms of […]

Adopting Big Data for Finance

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This article is the fourth in an editorial series that has the goal to provide direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively in today’s climate of working to increase the value of corporate data assets.

Types of In-Memory Computing

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In this installment we’ll set the stage for in-memory computing technology in terms of its current state as well as its next stage of evolution. We’ll begin with a discussion of the capabilities of in-memory databases (IMDBs) and in-memory data grids (IMDGs), and show how they differ. We’ll finish up the section by demonstrating how neither one is sufficient for a company’s strategic move to IMC; instead, we will explain why a comprehensive in-memory data platform is needed.

Lustre 101

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This week’s lustre 101 article looks at the history of lustre and the typical configuration of this high-performance scalable storage solution for big data applications.