Master’s in Data Governance in Defence
Online master's programme of 1,900 hours in data governance in defence. 12 modules covering data as a defence asset, governance frameworks, information classification, data quality, metadata and lineage, master data, data architecture, privacy, data security, AI data governance and decision analytics, with an assigned technical tutor.
Master’s in Data Governance in Defence — studying from New Zealand
New Zealand's defence engineering sector is centred on the New Zealand Defence Force, which operates land, sea and air capabilities, with major bases at Linton and Burnham. Defence procurement and sustainment are managed through the Ministry of Defence, and local firms support maintenance, communications and vehicle systems. Land systems engineering is closely linked to the country's agricultural and forestry sectors, where ruggedised vehicles and equipment are developed and maintained.
Fees for New Zealand: NZ$19,700 (New Zealand dollar), with instalments and employer sponsorship available.
Relevant bodies in New Zealand
Typical roles
Questions from New Zealand
How is defence and military engineering recognised in New Zealand?
Engineering registration is handled by Engineering New Zealand, and defence procurement and security clearances are managed through the New Zealand Defence Force and government procurement processes. Security clearance requirements can matter more than academic credentials for some roles. SEIUM is a private institute, and its qualifications are not accredited by a national body, so recognition rests with the employer.
What defence and land systems employers operate in New Zealand?
Opportunities arise with the New Zealand Defence Force, Defence Technology Agency, defence industry suppliers and engineering firms serving land systems and vehicles. Many roles require citizenship or security clearance. A private online qualification may support an application, but it does not guarantee a position, and clearance and experience usually weigh more heavily.
Is it possible to study from New Zealand without a visa, and can my employer pay?
Yes, programmes are 100% online and taught in English, so no student visa is needed to study from home. Each includes an assigned technical tutor and a final project. Fees are payable in instalments, and employer sponsorship is possible. Specialist courses take 300 hours, diplomas 800 and master's 1,900, so plan your workload carefully.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Design data governance frameworks tailored to defence organisations.
Apply information classification and labelling schemes in line with NATO standards.
Implement data quality, metadata and master data programmes.
Define secure, federated and resilient data architectures.
Ensure compliance in privacy and information security.
Govern the data that feeds artificial intelligence systems.
Develop a comprehensive data governance project in a Master's Thesis.
Who it's for
- Data governance leads in defence or public administration.
- Data architects.
- Data stewards.
- Data quality analysts.
- Data protection officers.
- Data strategy consultants.
- Engineering or science graduates seeking to enter the defence sector.
What you'll work with
- ISO/IEC 38505-1:2017 (governance of data)
- STANAG 4774 (confidentiality metadata labelling)
- ISO/IEC 27001:2022 (information security management systems)
- STANAG 4778 (metadata binding mechanism)
- ISO 8000 (data quality and master data)
- ISO/IEC 25012 (data quality model)
- Regulation (EU) 2016/679 (General Data Protection Regulation)
- Royal Decree 311/2022 (Spanish National Security Framework, ENS)
- Collibra
- Apache Atlas
- Apache Kafka
- Great Expectations
- Power BI
12 modules
1.1The data life cycle in defence1.2Operational, logistics and personnel data1.3Data strategies of NATO and its allies1.4Roles: CDO, owners and custodians1.5A data-driven organisational culture1.6DCAM and CMMI DMM maturity models1.7The DAMA-DMBOK reference framework1.8Valuation and prioritisation of data assets1.9Data in multi-domain operations1.10Case study: data maturity assessment
2.1ISO/IEC 38505 and data governance2.2Policies, standards and procedures2.3Governance boards and data committees2.4Federated and centralised models2.5Organisational change management2.6Data governance indicators2.7Integration with COBIT2.8Exception management and escalation2.9Implementation roadmap2.10Workshop: governance operating model
3.1National and NATO classification levels3.2The Spanish Official Secrets Act and national regulations3.3Confidentiality labelling with STANAG 47743.4Metadata binding with STANAG 47783.5Need to know and access control3.6Attribute-based access control3.7Security domains and content guards3.8Declassification and periodic review3.9Information shared with third countries3.10Practical exercise: labelling scheme for a repository
4.1Quality dimensions according to ISO/IEC 250124.2ISO 8000 and master data quality4.3Data profiling4.4Validation and cleansing rules4.5Continuous quality monitoring4.6Root cause analysis of defects4.7Sensor data quality4.8Quality of logistics and cataloguing data4.9Quality dashboards4.10Lab: profiling with Great Expectations
5.1Technical, business and operational metadata5.2Enterprise data catalogues5.3End-to-end lineage5.4Business glossaries and taxonomies5.5Ontologies and the semantic web5.6NIEM and JC3IEDM exchange models5.7Data discovery in classified environments5.8Automation of metadata capture5.9Governance of geospatial data5.10Workshop: data catalogue with Apache Atlas
6.1MDM architectures6.2The NATO Codification System for materiel6.3Reference data for units and organisations6.4Entity identity resolution6.5Golden record and survivorship rules6.6Hierarchy governance6.7Synchronisation between systems6.8Master data in defence ERP systems6.9Master data management indicators6.10Case study: consolidation of a spare parts catalogue
7.1Data lake, data warehouse and lakehouse7.2Data mesh and data products7.3Disconnected and edge architectures7.4Sovereign cloud and defence cloud7.5Integration of tactical data7.6Event streaming with Apache Kafka7.7Dimensional and graph modelling7.8FMN federated interoperability7.9Data resilience and continuity7.10Practical exercise: design of a lakehouse architecture
8.1GDPR and Spanish Organic Law 3/20188.2Spanish Organic Law 7/2021 on criminal data8.3The Spanish National Security Framework (ENS)8.4Data protection impact assessments8.5Minimisation and pseudonymisation8.6Retention and records preservation8.7International data transfers8.8Compliance audits8.9Management of personal data breaches8.10Case study: DPIA of a personnel system
9.1ISO/IEC 27001 and Annex A controls9.2Encryption at rest and in transit9.3Key management and HSM modules9.4Data loss prevention9.5Zero trust architecture9.6Access monitoring and UEBA9.7Security in multi-level environments9.8Secure erasure and media sanitisation9.9Risk analysis with MAGERIT9.10Workshop: data security controls plan
10.1Training data and labelling10.2Bias and representativeness10.3Dataset documentation10.4Model lineage and MLOps10.5AI management systems according to ISO/IEC 4200110.6Synthetic data and privacy10.7Data drift and model drift10.8NATO principles of responsible AI10.9Sensor data for machine learning10.10Lab: governed MLOps pipeline
11.1Dashboards for command11.2Descriptive, predictive and prescriptive analytics11.3Data-driven predictive maintenance11.4Availability and logistics analytics11.5Effective data visualisation11.6Data literacy in military organisations11.7Evidence-based decision-making11.8Return on investment in governance11.9Ethics of analytical use11.10Practical exercise: fleet availability dashboard
12.1Problem definition and scope12.2State-of-the-art review12.3Assessment of the target organisation12.4Design of the proposed governance framework12.5Selected architecture and tools12.6Implementation plan and risks12.7Validation through indicators12.8Conclusions and future work12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within the intake, so the programme can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Collibra, Apache Atlas, Apache Kafka, Great Expectations and Power BI, in free, academic or evaluation versions. Practical work is based on real procedures: data maturity assessments in defence organisations, design of labelling and access control schemes and implementation of governed MLOps pipelines. Assessment is continuous by module, plus the Master's Thesis.
Standards covered: ISO/IEC 38505-1:2017, STANAG 4774, ISO/IEC 27001:2022, STANAG 4778, ISO 8000, ISO/IEC 25012, Regulation (EU) 2016/679 (GDPR) and Royal Decree 311/2022 (Spanish National Security Framework).
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Collibra, Apache Atlas, Apache Kafka, Great Expectations and Power BI, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent demonstrable professional experience), a suitable computer and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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