Building a Data Strategy for Defence Partners

By Steve Neat

Published on March 14, 2023

An elderly man and woman sitting across a table, having a discussion about business. The man is holding a pen and a paper, while the woman looks attentively towards him.

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence.

This was confirmed by the UK Ministry of Defence last September when it published its Data Strategy for Defence, which for the first time provided a clear vision and guidance for defence sector companies for gathering, collating and harnessing data.

It also recognised that more and more data was being harvested — but that challenges remained over how to extract truly valuable insight from it.

It also set out a detailed plan to make data ‘an enduring, strategic asset’, with clear goals to be reached by 2025.

The Ministry sets forth four specific outcomes in the strategy:

  • Data is curated, integrated, and human- and machine-ready for exploitation

  • Data is treated as the second-most important asset, behind only people

  • People are skilled and exploiting data to drive advantage

  • Defence are data leaders with partners, allies, and industry

The Strategy also set out rules for the sector, giving every organisation the responsibility to:

  • Exercise sovereignty over data, including accountability and ownership

  • Standardise data across the defence landscape

  • Exploit data at the most effective and relevant point in the value chain

  • Secure digital data at creation and curation, and when handling, storing, and transmitting

  • Curate data, ensuring it is assured, discoverable and interoperable

  • Endure data as an asset beyond individual projects

To meet these targets by 2025, a clear data strategy — which includes a data management system — is critical.

What is a data strategy?

A data strategy is a long-term plan setting out the technologies, processes, people, and rules that manage data.

It should make data available, maintain data consistency and accuracy, and support data security.

Gartner describes it as ‘a highly dynamic process employed to support the acquisition, organisation, analysis, and delivery of data in support of business objectives’.

Why is a data strategy important?

A well-executed data strategy ensures best practice in data management – and is therefore key for defence partners in meeting the outcomes and rules set out here.

It can also unlock enormous value in areas such as:

  • Operational efficiency

  • Process optimisation

  • Rapid decision-making

  • New and enhanced revenue streams

  • Optimised customer satisfaction

  • Accelerated onboarding for data users

How do you create a data strategy?

To deliver an effective data strategy, a defence organisation should:

  • Assign responsibility for implementing policies and processes

  • Define policies for sharing and processing data

  • Create processes for naming and storing data

  • Establish measurements for keeping data clean and usable

A clear framework will be central to this and involves five key stages:


A company must know what data it has. All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. .


Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide. A centralised platform is therefore critical. This also ensures scalability and flexibility for analytics, while helping different departments to understand the value of data lineage.


Data must be packaged in a way users can access and understand. Curating involves packaging data with helpful metadata to support these goals, while creating rules and access guidelines for data, depending on a person’s role.

Once the most critical data is curated, templates should be created for a business glossary, data dictionary, and business metadata. This will help organise data vocabulary and track how many data assets or terms are uploaded within the network.


Clear processes must be established for creating, sharing, and governing data. Data technology itself doesn’t guarantee that individuals can effectively access and use data. Data must be available to non-technical users in a way that aids their understanding. Training on policies, guidelines, and technology itself is key, as is ensuring the right analysts are in place to support key business functions. Some business processes may need reviewing to include data analysis — even going as far as requiring specific data to make a business decision. Creating a clear process with documented steps will help.


Data governance models should be flexible and dynamic while proactively addressing risk management and compliance with local and global regulations. Two main models exist:

  • A centralised model, where rules around data use and processes are set by one group

  • A federated model, where several groups have authority over data

The model adopted will ultimately depend on organisational needs — but whichever route is chosen, it must evolve to ensure consistently high data quality, effective usage, and continued compliance. A decentralised model, with several individuals or teams empowered to manage different datasets, is generally better for ensuring data is accessible, discoverable, and understandable by all those who access and use it.

The role of a data catalog

Those seeking to harness the power of data and accelerate their data strategy should act rapidly to put the right tools in place for gathering, collating, accessing, using, and maintaining data. One tool that can contribute in all these areas is a data catalog: a fully scalable and flexible solution for governing, accessing and curating vast quantities of data.

This ensures it can be readily accessed in a form users can understand while meeting the needs of individuals and teams who need to access and use it, and its full potential exploited for commercial advantage.

It will all ensure data can be easily shared; is reliable, trustworthy and of high quality, and is readily reusable for as long as it is valid. In short, it can become the ‘digital backbone’ of any organisation.

Further details and some useful tips on creating a data strategy can be found here.

How can help?

Alation’s acclaimed data catalog is used by more than 400 leading organisations worldwide seeking to create a central hub for data-driven innovation.

It offers numerous features and benefits which will allow organisations to readily and effectively implement a future-proof data strategy. These range from rapid problem identification to ensuring access for the right individuals and teams, as well as tracking areas such as policy conformance, data usage, data quality, curation progress, top users and the productivity of analysts.

For further information, book a personalised demo with one of our experts today.

  • What is a data strategy?
  • Why is a data strategy important?
  • How do you create a data strategy?
  • The role of a data catalog
  • How can help?


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