Context-Based Analytics in a Big Data World: Better Decisions

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Published on July 17, 2013, updated August 26, 2013

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IBM Form #: REDP-4962-00


Authors: Lisa Sokol and Steve Chan

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    Abstract

    As the world becomes more instrumented, interconnected, and intelligent, the volume of information that is generated is growing at an exponential rate. The conversation surrounding this information explosion and about big data has centered on the size and management of this data. However, there is also an opportunity to improve critical business insight by taking advantage of the context that is created from big data.

    Context, the cumulative history that is derived from data observations about entities (people, places, and things), is a critical component of analytic decision process. Without context, business conclusions might be flawed. By using context analytics with big data, organizations can derive trends, patterns, and relationships from unstructured data and related structured data. These insights can help an organization to make fact-based decisions to anticipate and shape

    business outcomes.

    This IBM® Redbooks® Point-of-View publication describes the following key advantages of using context-based analytics:

    • Creating data within the appropriate context delivers higher quality models.
    • Higher quality models applied to contextually-correct data can lead to better mission decisions and better outcomes.
    • Using real-time contextual analytics enables timely entity assessments, while the observations are still occurring.
    • Using context analytics with big data allows organization to achieve greater success regardless of whether the objective is mitigating risk or recognizing opportunity.

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