Enabling the MOD's defence data management strategy with intelligent data access

The Defence Data Management Strategy includes six data rules ² that establish criteria for managing information. Each rule includes critical visibility questions: 

• What data is being accessed? 

• Who or what is accessing it? 

• Why is it being used? 

They work together to enable auditability and accountability throughout the data lifecycle. Below are the six data rules Defence is required to implement: 

1. Exercise sovereignty over data, establishing clear accountability and ownership.

2. Standardise data across the defence landscape, enabling seamless integration.

3. Exploit data at the most effective point in the value chain, maximising operational benefit.

4. Secure digital data, protecting information throughout its lifecycle.

5. Curate data, ensuring it is assured, discoverable, and interoperable.

6. Treat data as an enduring asset — preserving long-term value beyond individual projects.

By creating a comprehensive foundation for holistic visibility and auditability, Elastic helps defence teams implement all six rules effectively. Our end-to-end security approach, encryption, role-based access controls, and comprehensive audit logging, ensure that data remains protected throughout its lifecycle, while allowing complete transparency through open standards. This approach enables visibility while providing protection of the data and also illuminates its use, giving you the ability to monitor, track, and verify access across complex operations.

Maintaining data sovereignty is a key priority for Defence. The organisations must tackle a complex legacy environment, unlock data hidden in siloed systems, avoid being locked out by supplier contracts, and implement clear governance frameworks that assign accountability for data quality and security. Without these, Defence risks losing control over its most critical asset — its data.

One way to address these challenges is by adopting flexible, secure data platforms that unify siloed data sources, support cross-domain collaboration, and maintain control over where and how data is stored and accessed. Data sovereignty demands tool consolidation, vendor agnostic approach, and systems that scale securely across legacy and modern environments.

Right now, too much of Defence’s data is stuck in silos and exists in different formats, making it hard to trust or reuse. Without a shared approach to standards, Defence risks wasting time and resources on duplicated or incomplete data.

To achieve compliance with this second rule, Defence needs to eliminate data silos and apply consistent organisation structures across all data. This ensures information can be accessed, analysed, and acted on effectively and holistically, regardless of its format or where it is stored. Data mesh principles, with capabilities like cross-cluster search, make integration and cross-domain insights both possible and practical. It enables defence-wide visibility, enforces schemas, and supports governance aligned with Defence and cross-government requirements.

Exploitable data is key to Defence’s ability to act fast, share intelligence, and adapt to evolving threats. Despite the volume and value of data available, Defence often struggles to make it usable, spending too much time finding and cleaning data and not enough on using it. Teams are often stuck manually correlating disparate data from different systems, leading to delays when critical decisions need to be made.

To support large-scale data exploitation and mission-ready intelligence, Defence must bring data together into a single, searchable platform. This approach enables fast access, automation, and insight across systems. By supporting a wide range of data ingestion methods, such as lightweight agents, OpenTelemetry, and edge collection, data can be analysed and exploited at the most effective point in its lifecycle, providing commanders with decision advantage through timely, accurate, and context-rich information.

Defence operates under constant cyber threats and needs secure-by-design data. Fast, controlled access to classified information, swift breach detection, and strict compliance with legal and ethical rules are critical but difficult to achieve at scale.

To safeguard sensitive data and maintain operational integrity, Defence needs to implement strong, built-in role-based security controls, such as role-based access controls (RBAC) and attribute-based access control (ABAC), across multiple layers. These controls should be supported by unified identity management and detailed activity logging. And when combined with advanced monitoring capabilities, including machine learning to detect insider threats and unusual behaviour, these measures enable real-time policy enforcement and continuous oversight across systems.

Defence systems produce vast amounts of data, but without curation, critical insights get lost in noise and duplication, delaying operational decisions.

To eliminate blind spots and enable timely insights, Defence must unify its data and apply AI-driven search to surface the right information from different sources through a single, holistic query. Machine learning can further support data curation by revealing hidden patterns, while advanced techniques like retrieval augmented generation (RAG) enhance context-aware analysis for faster, mission-critical decisions.

Data is often locked to its original purpose, losing relevance over time or its immediate use. Defence lacks consistent ways to maintain, govern, and extract long-term value.

Managing data as a persistent asset requires implementing lifecycle policies that automatically migrate data to economical, long-term storage, maintaining queryability with minimal performance impact. Elasticsearch logsdb index mode exemplifies this approach by efficiently storing critical logs and reducing storage costs by up to 65%, enabling defence to optimize data retention expenses.