A government defense agency with the problem of disparate data scattered globally in over 100 different data stores required a secure mechanism to pull sensitive information into a central data mart and make it available in near real-time for monitoring, trending, and improved decision making.

We leveraged our lightweight agents in the field as part of our MDACA solution set to meet the clients requirements. MDACA agents have the intelligence to act on instructions received and transmit back to the central hub/location securely.

Our team deployed a prototype consisting of three sites in four months. Once the pilot was successfully completed, we continued a very aggressive deployment schedule across a hundred sites within six months. Today, the MDACA support Operational Data Store (ODS) processes nearly 9 billion transactions per day, supports more than 35,000 users, contains more than 20 terabytes of data, and continues to expand as other data sources and requirements are added to meet the worldwide mission.

Today MDACA processes more than 8.2 billion transactions per day, supports more than 35,000 users, and contains more than 20 terabytes of data

The MDACA platform provides the foundation for aggregation and consolidation of decentralized data sources into a common data repository. The platform offers:

  • Near real-time data aggregation and consolidation of external data sources

  • Consolidated data available to external analytics applications

  • Highly transactional Oracle RAC services

  • SOA based architecture

  • Hardware modernization and consolidation

  • RMF accredited COTS platform residing in a DoD enclave

Our team was able to solve the problem of having multiple decentralized data sources, both within the contiguous United States (CONUS), as well as outside of the contiguous United States (OCONUS), with no single reporting database instance. Our services provided a low latency solution to consolidate these data sources and allowed for a central reporting repository that resided inside the client data center, thereby reducing the time and effort required to complete complex data analytics.