Sponsor: IBM Corporation

Follow the Money: Big Data ROI and Inline Analytics

Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
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Is your Database Ready for the Era of Big Data?

You need a database designed to control both the infrastructure and personnel costs that form the IT budget. The next generation of IBM DB2 helps organizations get more value from their big data to improve their IT economics. Major innovations provide out-of-the-box performance gains that go beyond the limitations of in-memory-only systems to support decision making at the speed of business.
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In-Memory Databases Put the Action in Actionable Insights

In order to derive business value from Big Data, practitioners must have the means to quickly (as in sub-milliseconds) analyze data, derive actionable insights from that analysis, and execute the recommended actions. While Hadoop is ideal for storing and processing large volumes of data affordably, it is less suited to this type of real-time operational analytics, or Inline Analytics. For these types of workloads, a different style of computing is required. The answer is in-memory databases.
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From Data to Action: Governance and Integration Shape Successful Information Strategies

This IT Managers Journal looks at many aspects of data governance including policy, business rules and standards, and offers best-practice advice as to what steps the enterprise should be taking today to ensure business units are getting the maximum value out of enterprise data while further ensuring compliance with security, regulatory and technology mandates. This ITMJ looks at processes and tools that help manage and leverage value of data governance with minimal impact on today’s data-heavy business practices.
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Flash or SSD: Why and When to Use IBM FlashSystem

This IBM® Redpaper™ publication explains how to select an IBM FlashSystem™ or solid-state drive (SSD) solution. It describes why and when to use FlashSystem products, and reviews total cost of ownership (TCO), economics, performance, scalability, power, and cooling. Read this guide for information about selecting the correct solution (SSD or flash technology).

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