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Abstract:
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Many organizations collect vast amounts of data for various purposes. While data streams are often collected with a specific end goal in mind, they can also provide valuable information for broader initiatives and improved decision-making. Standard analyses can often be enhanced by incorporating additional information from previously underutilized data sources into the modeling process. The impact of individual analyses can be increased by developing reusable analysis processes with associated computational infrastructure and workflows. The integration of heterogeneous data from multiple sources can pose a variety of challenges in terms of data acquisition, storage, processing, analysis, and ongoing delivery of results. This presentation will discuss the development of an integrated analytics capability that leverages the power of statistical methods with access to data from multiple sources. Examples of analysis applications that have been developed to provide dynamic results informed by disparate data streams will also be discussed.
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