Postgraduate DiplomaBusiness, Management & Technology Policy Applications open

Diploma in Data Sharing, Marketplaces and Monetisation Models

Online postgraduate diploma of 800 hours in data sharing, marketplaces and monetisation models. 8 modules covering the data economy, the Data Act and Data Governance Act, data spaces, marketplaces, monetisation models, privacy-enhancing technologies and data product governance, with an assigned technical tutor.

Duration6–8 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma

Diploma in Data Sharing, Marketplaces and Monetisation Models — studying from New Zealand

Engineering management and technology policy roles are important across New Zealand, particularly in infrastructure, energy, primary industries and the technology sector, which is concentrated in Auckland and Wellington. Organisations such as the Ministry of Business, Innovation and Employment shape innovation policy, while Callaghan Innovation supports research commercialisation and industrial development. Professionals in this field usually combine technical knowledge with project governance, procurement and strategic planning for large public and private organisations.

Fees for New Zealand: NZ$2,160 (New Zealand dollar), with instalments and employer sponsorship available.

Relevant bodies in New Zealand

  • Ministry of Business, Innovation and Employment (MBIE)
  • Callaghan Innovation
  • Institute of Directors in New Zealand

Typical roles

  • Engineering Project Manager
  • Technology Policy Analyst
  • Innovation Manager
  • Operations Manager

Questions from New Zealand

Do New Zealand professional bodies recognise business or technology policy qualifications for engineers?

Engineering New Zealand regulates engineering registration, including Chartered Professional Engineer status, and focuses on engineering competence rather than management study alone. Other relevant bodies include professional institutes for management and project leadership. SEIUM's qualifications are private, not state degrees, and not accredited by any national body, so their standing is determined by the employer or relevant body.

Where do engineers with management and technology policy skills work in New Zealand?

Typical employers include government agencies, infrastructure and energy organisations, consultancies, and technology companies needing leaders who understand both engineering and policy. Advancement often depends on experience, results and professional networks. A private programme can add credibility to a CV, but it does not guarantee promotion or a particular role.

Can I manage this study alongside a job and get my employer to pay?

The programmes are online and in English, so you can study from New Zealand without a student visa. Specialist courses take 300 hours, postgraduate diplomas 800 hours and master's programmes 1,900 hours, each with an assigned technical tutor and a final project. Fees are payable in instalments, and employer sponsorship is possible. Plan a realistic weekly schedule before enrolling.

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Learning outcomes

What you will be able to do

01

Analyse the economic value of data.

02

Apply the European legal framework for data sharing.

03

Design architectures for sovereign data spaces.

04

Set up data products for marketplaces.

05

Define sustainable monetisation models.

06

Incorporate privacy-enhancing technologies.

07

Govern data products with quality and traceability.

Profile

Who it's for

  • Data product managers.
  • Data strategists.
  • Data space architects.
  • Legal advisers working on data contracts and compliance.
  • Monetisation analysts.
  • Data partnership managers building data ecosystems.
  • Engineering or science graduates looking to enter the mobility and transport sector.
Standards & tools

What you'll work with

  • Regulation (EU) 2023/2854 Data Act (access to and use of data)
  • Regulation (EU) 2022/868 Data Governance Act (data intermediaries and re-use)
  • Regulation (EU) 2016/679 GDPR (personal data protection)
  • Directive (EU) 2019/1024 (open data and public-sector information)
  • ISO/IEC 25012 (data quality model)
  • Directive (EU) 2016/943 (protection of trade secrets)
  • IDSA RAM 4 (reference architecture for data spaces)
  • Eclipse Dataspace Connector
  • Snowflake Marketplace
  • Databricks
  • Collibra
  • Python
Syllabus

8 modules

  1. 1.1Data as an economic asset
  2. 1.2Economic characteristics of data
  3. 1.3Network effects and platforms
  4. 1.4Data value chains
  5. 1.5Personal and non-personal data
  6. 1.6Industrial and mobility data
  7. 1.7The European data strategy
  8. 1.8Sectoral data spaces
  9. 1.9Barriers to data sharing
  10. 1.10Case study: data assets of a logistics operator
  1. 2.1The European Data Act
  2. 2.2The Data Governance Act
  3. 2.3GDPR and lawful bases
  4. 2.4Anonymisation and pseudonymisation
  5. 2.5Re-use of public-sector data
  6. 2.6Competition law and sharing agreements
  7. 2.7Protection of trade secrets
  8. 2.8Data-sharing contracts
  9. 2.9The Commission's model clauses
  10. 2.10Workshop: business-to-business data-sharing contract
  1. 3.1The IDSA reference architecture
  2. 3.2The Gaia-X initiative and federated services
  3. 3.3Connectors and data sovereignty
  4. 3.4Catalogues and metadata
  5. 3.5Usage policies and their enforcement
  6. 3.6Identity and trust
  7. 3.7The European mobility data space
  8. 3.8Catena-X in the automotive sector
  9. 3.9Semantic interoperability and common vocabularies
  10. 3.10Laboratory: deploying an Eclipse EDC connector
  1. 4.1Types of marketplaces
  2. 4.2Actors: providers, consumers and intermediaries
  3. 4.3Marketplace functions
  4. 4.4Quality and description of data products
  5. 4.5Data usage licences
  6. 4.6Payment mechanisms
  7. 4.7Reputation and trust
  8. 4.8Existing marketplace cases
  9. 4.9Requirements for data intermediaries
  10. 4.10Practical exercise: designing a data product
  1. 5.1Direct sale of data
  2. 5.2Data as a service and APIs
  3. 5.3Derived analytics services
  4. 5.4Internal data monetisation
  5. 5.5Subscription and usage-based models
  6. 5.6Revenue sharing in ecosystems
  7. 5.7Pricing data
  8. 5.8Valuation of data assets
  9. 5.9Cannibalisation risks
  10. 5.10Workshop: data business model for a manufacturer
  1. 6.1Differential privacy techniques
  2. 6.2Secure multi-party computation
  3. 6.3Cross-organisation federated learning
  4. 6.4Homomorphic encryption and its limits
  5. 6.5Synthetic data generation
  6. 6.6Trusted environments and clean rooms
  7. 6.7Re-identification risk assessment
  8. 6.8Governance of data use
  9. 6.9Technology selection
  10. 6.10Practical exercise: generating synthetic data
  1. 7.1Data product life-cycle management
  2. 7.2Data quality agreements
  3. 7.3Lineage and traceability
  4. 7.4Documentation and metadata
  5. 7.5Support and versioning
  6. 7.6Usage and value metrics
  7. 7.7Incident management
  8. 7.8Ethics of data use
  9. 7.9Organising the data team
  10. 7.10Case study: data product dashboard
  1. 8.1Selecting the business case
  2. 8.2Data inventory
  3. 8.3Legal analysis of the case
  4. 8.4Designing the technical architecture
  5. 8.5Designing the data product
  6. 8.6Monetisation model
  7. 8.7Governance plan
  8. 8.8Conclusions and areas for improvement
  9. 8.9Report and presentation
  10. 8.10Final project: final review with your tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so the programme fits around your job.

Each module combines theory, guided reading of the original regulation and applied exercises. The working software is Eclipse Dataspace Connector, Snowflake Marketplace, Databricks, Collibra and Python, in free, academic or evaluation versions. Practical work is based on real procedures: deploying a data space connector, designing a licensed data product and analysing re-identification risk. Assessment is continuous by module plus the final project.

Standards covered: Regulation (EU) 2023/2854 Data Act, Regulation (EU) 2022/868 Data Governance Act, Regulation (EU) 2016/679 GDPR, Directive (EU) 2019/1024 on open data, ISO/IEC 25012, Directive (EU) 2016/943 on trade secrets, IDSA Reference Architecture Model 4.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the Data Act, the Data Governance Act, the GDPR and the IDSA reference architecture applied to real cases, not as a theoretical annex.
Industry software:Eclipse Dataspace Connector, Snowflake Marketplace, Databricks, Collibra and Python, in free, academic or evaluation versions.
Final project:a data monetisation project for a real business case, with legal analysis, technical architecture, data product, monetisation model and governance plan, reviewed by your tutor.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Data asset inventory
Identify and assess the data assets of the selected organisation.
Data-sharing contract
Draft a business-to-business data-sharing contract under the Data Act.
Connector deployment
Deploy an Eclipse EDC connector with usage policies.
Data product and business model
Design a licensed data product and its monetisation model.
Final project
A complete data monetisation project with legal analysis, architecture, product and governance plan, reviewed by your tutor.
Career opportunities

Where this takes you

Data Product ManagerData StrategistData Space ArchitectData Legal AdviserMonetisation AnalystData Partnerships Manager
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • An 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.

FAQ

Frequently asked questions

The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with Eclipse Dataspace Connector, Snowflake Marketplace, Databricks, Collibra and Python, 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 final project. 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 are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.

Prior technical training or professional experience in the sector (no university degree required), 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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