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Building a Data-Centric Business Ecosystem

We are transforming our approach to creating statistical data products. For centuries statistical agencies mainly relied on surveys to meet the nation’s data needs. Today’s technology allows us to use a wide variety of survey, administrative, and other data--often data we have already collected. This allows us to respond more effectively to the rapidly evolving needs of the nation.  

The four key innovation areas include: 

  • Data Ingest and Collection for the Enterprise (DICE) simplifies data collection
  • The Frames Program enables us to use our data in more innovative ways
  • The Enterprise Data Lake (EDL) centralizes data management and processing, enabling more efficient access and use of our data 
  • Census Enterprise Dissemination Services and Consumer Innovation (CEDSCI) makes our data more accessible

Learn More about the Census Business Ecosystem

EDL Overview
  • Overview
  • DICE Overview
  • Frames Overview
  • EDL Overview
  • CEDSCI Overview
EDL Overview

Storing & Processing Data in the Cloud

The Enterprise Data Lake (EDL) is central repository for all types of Census Bureau data. 

It will provide scalable data storage and processing for survey operations, concurrent research analytics, post-processing, data product creation and innovation, data dissemination, and archiving.

This cloud-based platform allows approved users to conduct project-based big data analytics and research to create new and innovative data products. 

Modernization benefits include:

  • Discoverable Data: All data is centrally located and cataloged in the EDL and can be searched and shared through the user interface, providing easier access for collaboration within the Census Bureau.

  • Streamlined Security: Data access and IT security policies are managed within the system, relieving that resource responsibility for program areas.

  • Multiple Environments: The ability to have multiple environments for development, testing, production, etc., allows for streamlined development without affecting business operations.

  • Quick and Cost-effective: A project would have the ability to spin up extra computing power to process data more quickly. EDL offers the ability to efficiently manage cloud usage costs by powering the cloud on/off as dictated by individual program needs.

  • Software and Environments to Meet Your Needs: Open-source software tools for processing and analyzing data, including machine learning and cloud native tools, can be used in scalable personalized environments.

  • Better Monitoring: Advanced data lineage, tracking and auditing in EDL can provide program areas with better monitoring for project data, processes, and cost management.

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Page Last Revised - February 6, 2024
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