Tableau Case Studies Tableau Selected for Homeland Security Pilot Project
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Tableau Selected for Homeland Security Pilot Project

Tableau
Analytics & Modeling - Big Data Analytics
Application Infrastructure & Middleware - Data Visualization
National Security & Defense
Business Operation
Predictive Maintenance
Data Science Services
Pacific Northwest National Laboratory (PNNL) was asked by the Department of Homeland Security to participate in a pilot program. The goal was to pilot an analytical application for the Immigration and Customs Enforcement (ICE) department that would leverage analysis techniques used for unstructured text analysis with those used in structured data analysis. PNNL’s primary objectives over the project were threefold: Provide a new capability for structured and unstructured data analysis, Evaluate/characterize ICE data, and Be deployable within eighteen months. PNNL wanted to address the question of mixed data: information typically found in structured forms with annotations, case files, reports, etc. They wanted to ensure data sharing and interoperability and to facilitate data exchange between specialized tools.
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Pacific Northwest National Laboratory (PNNL) is a Department of Energy Office of Science national laboratory that solves complex problems in energy, national security and the environment and advances scientific frontiers in the chemical, biological, materials, environmental and computational sciences. PNNL was asked by the Department of Homeland Security to participate in a pilot program. The goal was to pilot an analytical application for the Immigration and Customs Enforcement (ICE) department that would leverage analysis techniques used for unstructured text analysis with those used in structured data analysis.
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PNNL chose Tableau to help blend analysis of structured and unstructured data while simultaneously fulfilling the data visualization and presentation requirements. Throughout the lengthy pilot, PNNL is using Tableau coupled with In-Spire, a tool for unstructured data analysis, in simulated real-world environments in order to assess the following factors: Ease of use (minimal time requirement and intellectual investment), Ability to integrate into the existing infrastructure, and Ability to improve current processes.
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Provided a new capability for structured and unstructured data analysis
Evaluated/characterized ICE data
Deployable within eighteen months
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