Helping Federal Courts Expediently and Accurately Fulfill Their Duties

  • Customer Story
  • Data
  • Health & Civilian


The Judiciary Data and Analysis Office (JDAO) within the Administrative Office of the U.S. Courts (AOUSC) develops and maintains business intelligence (BI) decision support systems for U.S. federal courts. The federal judiciary includes over 32,000 users working across 90 bankruptcy courts, 94 district courts, and 13 appellate courts in a geographically dispersed environment; these users rely upon accurate and timely data to perform their judicial functions.

As courts had local data autonomy and were under no obligation to use JDAO’s tools or participate in data integration initiatives, JDAO had to contend with disparate data stored across numerous data sources, often built and maintained independently.

To better meet user needs, JDAO sought to put in place improvements that would centralize data storage and management and remove data silos while democratizing data, maintaining flexibility, allowing for growth and concurrent usage, and offering the greatest interoperability among JDAO stakeholders, applications, and programs.

Understanding the Need

To maximize the value of its data, enhance operational intelligence, and increase data visibility and accessibility, JDAO needed to:

  • Remove data silos and centralize data management and governance.
  • Build an architecture and integrated enterprise data warehouse (IEDW) that seamlessly integrated data from multiple sources while maintaining flexibility that allowed for growth and concurrent usage and maximizing interoperability.
  • Evolve from IT-centric BI to democratized data – delivering self-service capabilities to users and decision-makers.
  • Actively engage stakeholders and end-users to demonstrate the value of JDAO’s tools and initiatives and obtain buy-in.
Image shows point of view looking up at classic Greek columns and the sky.
Releases supported annually for IEDW.
Users serviced across 600 dispersed locations.
Improvement in the SAP Data Services (ETL) execution times.

Our Solution

Since 2008, GovCIO’s (formerly Salient CRGT) 60-person team has provided JDAO with full lifecycle support for the design, development, enhancement, updating, implementation, and maintenance of data warehouses, systems, and reporting applications using ITIL and Agile approaches. We continually evolve and enhance the systems, bringing in new subject areas, establishing new functionality, and modernizing to improve efficiencies and cost.

Data Warehousing Enhancements

Big Data and Predictive Analysis

Help Desk Support


Analytics Dashboard Solution Support

Database Management

Security Support


In our time supporting JDAO, GovCIO has had a significant impact on its JDAO’s ability to effectively carry out its mission. At a high level, through our team’s expertise in the fields of data warehousing, business intelligence, data integration, and data governance, we have improved efficiencies, introduced operational efficiencies, improved customer satisfaction and reduced costs. We continually evolve and enhance the systems and infrastructure we support by bringing in new subject areas, establishing new functionality, and modernizing the environment. Some of our most notable achievements under this most recent contract include:

  • Upgrading JDAO’s data infrastructure upgrade (Oracle from 11g to 18c, SAP Data Services, SAP BusinessObjects, and IBM CDC), resulting in a 30% improvement in the SAP Data Services (ETL) execution times.
  • Increasing efficiency and the ease of managing business documents by building a comprehensive, modernized document management system (business document management system) for the NewSTATS system.
  • Optimizing the query performance by moving workload from the application query to the Oracle database to improve and monitor performance across the EDW-CM/EF Bankruptcy and District application. Consequently, we improved performance by up to 300% depending on the query being executed.
  • Creating a standardized and reliable data model for integrating data from multiple sources such as EDW HR and CIRIS into a single dimensional data model. This dimensional model maximizes reuse for efficiency and allows information sharing across the enterprise.