The Defense Information Systems Agency’s new Office of the Chief Data Officer signals the Department of Defense’s continued commitment to leveraging data as a strategic asset. This requires enhanced data sharing and integration; and early and important initiatives have involved surveying data systems and owners, meeting with industry partners, evaluating data tools, and creating metrics that can help measure the value of their systems.
We recently heard from DISA leaders about the challenges the agency has faced in its endeavor, and while these challenges are not uncommon to agencies or organizations of any kind, for DISA and for America’s national security interests, they will be critical to address and overcome in short order. These range from managing the vast amounts of data generated in numerous DISA ecosystems, the isolation of much of that data, and the inherent difficulties associated with bringing such large amounts of data together for governance and analytics.
In our experience at GDIT, there are a number of mission-impacting best practices that allow agencies to effectively and efficiently find greater value and insights in their data. Among them:
Distributed Processing to effectively and economically process big data loads
Data Lakes that bring all data assets together for a broader and deeper view of the enterprise
Cloud-Native data analytics services for economical insights in a pay-as-you-go model
Machine Learning to predict future events, classify risk, and automate human tasks
Self-Service Tools to democratize data analysis by assisting data preparation and analysis
Data Discovery Tools to help find data assets relevant to the scope of analysis
Open-Source software, packages, and frameworks to drive innovation
Data Curation to govern and improve data, augmented by user insights and share best practices
To achieve deeper insights Artificial Intelligence methods including Machine Learning, Computer Vision, Natural Language Processing, Intelligent Automation, and Cognitive Agents can leverage vast amounts of data to automate, innovate, and operationalize both back-office functions and mission-critical operations alike.
For our clients, GDIT regularly uses cloud-native AI and Data services to acquire, store, transform, analyze, and consume data. We use a reference service architecture that identifies core services needed for data analytics solutions. Our GDIT Mission Insights platform extends cloud-native services with data enrichments from AI services such as Image Analytics, Text Analytics, Image Analytics, Video Analytics, Audio transcription, and Speech Understanding. More than important, this is a gamechanger because with these enrichments, we can leverage data in all formats with powerful search, matching, correlation, and predictive analytics.
These capabilities address the specific challenges DISA is facing in leveraging its data to improve both operations and missions; they also address the challenges of any large organization looking to make strategic use of a valuable, dynamic, and growing asset: its data.
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