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Tableau Selected for Homeland Security Pilot Project
Technology Category
- Analytics & Modeling - Big Data Analytics
- Application Infrastructure & Middleware - Data Visualization
Applicable Industries
- National Security & Defense
Applicable Functions
- Business Operation
Use Cases
- Predictive Maintenance
Services
- Data Science Services
The Challenge
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.
About The Customer
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.
The Solution
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.
Operational Impact
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