Across all industries and sectors, the volume and scope of data continues to increase exponentially. It shows no sign of slowing down or reducing. UK Defence, and the wider public sector, collect vast amounts of data. They have a desire to innovate and exploit that data through analytics, artificial intelligence, and machine learning.
Their goals are to increase mission effectiveness, mitigate the threat risk, reduce operating costs and meet compliance requirements. Along with boosting efficiency to meet sustainability and financial targets. However, what is evident is that all these things combined present real challenges. They need to be addressed. If ignored, they can become a barrier to realising opportunities.
AI as a strategic imperative in government
The recent Defence AI strategy further cements government aspirations towards the use of AI as a strategic imperative. Still, without a handle on data and effective governance, progress will be slow. Or the results are not as intended, posing a significant risk to operational objectives.
Much evidence affirms a lot needs to be done in improving data management processes. Complying with legislation and effective data governance is a critical prerequisite in systems development and building the capabilities required for the country to keep pace.
The Defence Data Strategy documents some of the challenges that are presented by ineffective data management for UK Defence. The UK Defence recognises that to deliver improvement, they must start managing data far more effectively than they do today.
There needs to be a common and consistent language used across military, technical and data users. This will help break down communication barriers and aid the translation of business-level requirements into technical deliverables and vice-versa.
Data standards must be driven and adopted across defence. Including the use of Metadata to drive the governance of data and consistency in the management of data to improve use, reuse, and trust.
Many data sources remain siloed, which subsequently causes duplication as copies of data are taken to meet individual units’ requirements. This compounds the problem as teams don’t understand which data is the authoritative source. This subsequently instils a lack of trust in the insights that are derived because there doesn’t seem to be one single source of truth.
All of this leads to users wasting time and effort finding, accessing, preparing, and sharing data for analysis.
Where is the opportunity?
In support of industry partners, UK Defence needs to define a collective strategy, approach and plan that considers the following three areas:
- Establishing and enforcing governance through data standards and policies to get a consistent view of data. Including the creation of a repository of governed terms and sources to use across any system – including third-party systems.
- Breaking down data silos through reusable and automated data integration services that provide the ability to enrich data from multiple operational sources, perform duplicate elimination and manage and remediate data quality issues and bias.
- Providing a central area for the collection of metadata, combined with data management and search tools, so analysts and other data users find the data that they need. This will also serve as an inventory of available data and provide the information needed to evaluate the fitness of data for specific, intended uses.
Taking this approach will allow users to establish:
- What data is available.
- The health and quality of data.
- Understand data relationships.
- Easily locate hard-to-find data and gain access it.
- Allow data users and consumers to assess differences between data sets.
- Determine if data preparation requirements are needed.