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Case Study: DHS Data Management

The Department of Homeland Security has the important mission of securing the nation from threats around the globe. With the varied types of threats we face – from natural disasters and cybersecurity attacks to border security and customs – the mission deals with a tremendous amount of data and information.

Our data engineering work at DHS crosses multiple agencies and components. It’s about integrating, understanding, orienting, and acting the right way at the right time. It’s about partnering with other federal and public entities to ensure that all parties have accurate and up to date information to act, and to act as one.

Customer challenges

  • Handling and integrating highly secure information related to critical infrastructure, US citizens, and national security
  • Obtain, integrate, and surface information in near realtime for response during disaster response, national security, and public safety engagements
  • Integrate data in a meaningful fashion across multiple DHS, federal, and public partners

The OneGlobe solution

OneGlobe’s data engineering and data science competency group leads the coordination of this important mission solution across multiple agency contracts. Our solutions span across the AWS commercial, GovCloud, and C2S regions, while securely integrating with DHS and other federal communications avenues. By leveraging the AWS service portfolio, in combination with leading-edge data science, machine learning, and artificial intelligence engineering tools, we make sure that data is integrated, catalogued, tracked, and put in the hands of the systems and analysts that need it.

Great outcomes

Across our DHS portfolio our data engineers and data scientists have driven some amazing outcomes using AWS data solutions and OneGlobe tools and practices:

  • Self-service integrations of the HIFLD public and sensitive datasets with other agency data for public safety and national security
  • Realtime streaming data processing between DHS and other federal partners, including chain of custody, data lineage, metadata management, and data cataloging
  • Integration of public partner data through schema-on-read flexible data layers and the AWS Data Lake solution components