From ground sensors to aerial drones, data is becoming increasingly ubiquitous in military operations. The quality and accuracy of information derived from data depends on the ability to link and review all relevant data. However, transferring and storing huge amounts of data in one place for analysis is not only costly in terms of time and bandwidth, but also prone to errors and delays. Therefore, finding the hidden insights in the vast amounts of information becomes more difficult than ever.
Artificial intelligence (AI), including machine learning (ML), deep learning, and generative AI (Gen AI), offers new ways to discover and curate data. Combining search and AI brings together the best of both technologies to create an easier way for everyone to access data. As military forces seek to share and consume more data to make real-time decisions, service members must have confidence in the insights generated from their data and must be confident that their proprietary data will remain secure.
The Department of Defense (DoD) Chief Digital and Artificial Intelligence Office (CDAO) continues to move forward with the adoption of emerging technologies such as Gen AI. The CDAO identified nearly 200 use cases on how the department could leverage revolutionary technology in various functions, according to the office’s chief technology officer. Although Generation AI has commercial applications within the DOD, the consequences are greater and the DoD must be accountable for how the department uses the technology.
How does search analytics help
Research-based AI is one tool that can help the DoD achieve some of these goals. A distributed, real-time search and analytics engine that can store data centrally for rapid search, refined relevance, and powerful analytics can help defense agencies break down data silos and share insights. information securely. There is an urgent need for defense agencies to manage unstructured data such as text, images, geospatial data and time series, and support complex queries and aggregations. Real-time search analytics can also integrate with other tools and platforms such as Apache Hadoop, Apache Spark, business intelligence applications, and AI solutions.
Defense agencies must manage data on-premises, in the cloud, or in a hybrid environment. They must adapt to remote devices and difficult terrain. Essential security features include encryption, authentication, authorization, and auditing.
A search analytics platform should offer more than real-time search. It must integrate security features with predictive analytics. Cloud monitoring and observability capabilities are crucial. They enable automation and anomaly detection, which accelerates problem resolution and opportunity discovery.
Breaking down silos
Breaking down data silos and achieving data interoperability is a complex and challenging task. To overcome these challenges, defense agencies must adopt a multi-dimensional approach including technical innovation, organizational restructuring and cultural changes. Some of the possible strategies are:
— Promote cross-team collaboration and data sharing across different domains and partners.
— Establishment of a centralized data repository or data lake capable of storing and managing unstructured data from various sources.
— Use data integration tools and solutions that can connect, transform and enrich data from disparate systems and formats.
— Leverage cloud-based platforms and services that can provide scalable, secure, and flexible data storage and analytics capabilities.
Unlock hidden value
The future of defense depends on the ability to access, analyze and share data across different domains and platforms. But too often, data is trapped in silos that prevent effective collaboration and decision-making. This is why it is essential that defense agencies adopt methods to extract real value from data, facilitating secure sharing and ensuring interoperability.
Real-time search analytics can be a valuable tool for DoD to break down data silos and unlock the potential of their data. However, search analytics alone is not enough to solve the data silo problem. DoD must also adopt a data strategy that aligns with its mission and vision, and foster a data culture that encourages data quality, accessibility, and interoperability, as outlined in the Pentagon document. data, analytics and AI adoption strategy.
Using research-based AI, defense agencies can transform data from a liability to an asset and gain strategic advantage in a complex and dynamic world.
Chris Townsend is vice president of public sector at Elastic, a data research and analytics company.
