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Master'sBusiness, Management & Technology Policy Applications open

Master’s in Privacy, Data Governance and Data Monetisation Engineering

Online master's programme of 1,900 hours in privacy, data governance and data monetisation engineering: 12 modules covering data protection, privacy engineering, privacy-enhancing technologies, data governance, data quality and master data, data security, the European data economy, data monetisation, data product engineering, data ethics and data strategy, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Apply the GDPR and the LOPDGDD to technology-based data processing.

02

Embed privacy by design through impact assessments.

03

Use privacy-enhancing technologies such as differential privacy.

04

Design data governance and data quality models.

05

Protect data with appropriate security controls.

06

Develop monetisable data products within the European framework.

07

Assess the ethical and responsible use of data.

Profile

Who it's for

  • Data protection officers.
  • Data governance managers.
  • Privacy engineers.
  • Chief data officers.
  • Data product managers.
  • Data stewards.
  • Engineering or science graduates aiming to move into the technology sector.
Standards & tools

What you'll work with

  • Regulation (EU) 2016/679 (GDPR) (General Data Protection Regulation)
  • Spanish Organic Act 3/2018 (LOPDGDD) (data protection and digital rights)
  • Regulation (EU) 2023/2854 (Data Act)
  • Regulation (EU) 2022/868 (Data Governance Act)
  • ISO/IEC 27701:2019 (privacy information management)
  • ISO/IEC 27001:2022 (information security management)
  • ISO 8000 (data quality)
  • ISO/IEC 38505-1:2017 (governance of data)
  • Collibra
  • OneTrust
  • OpenDP
  • Great Expectations
  • Apache Atlas
Syllabus

12 modules · 1900 h

  1. 1.1GDPR principles
  2. 1.2Lawful bases for processing
  3. 1.3Data subject rights
  4. 1.4Spanish Organic Act 3/2018 on data protection (LOPDGDD)
  5. 1.5Record of processing activities
  6. 1.6Controller and processor
  7. 1.7Spanish Data Protection Agency and penalties
  8. 1.8Privacy in the transport sector
  9. 1.9Location and mobility data
  10. 1.10Case study: lawfulness of geolocation processing
  1. 2.1Privacy by design and by default
  2. 2.2Hoepman's privacy design strategies
  3. 2.3ISO/IEC 27701 management system
  4. 2.4ISO/IEC 29100 privacy framework
  5. 2.5Data protection impact assessment
  6. 2.6LINDDUN threat modelling
  7. 2.7Data minimisation
  8. 2.8Pseudonymisation and key management
  9. 2.9Consent management
  10. 2.10Workshop: LINDDUN threat modelling
  1. 3.1Anonymisation and k-anonymity
  2. 3.2Differential privacy and the epsilon budget
  3. 3.3Homomorphic encryption and its applications
  4. 3.4Secure multi-party computation
  5. 3.5Federated learning between organisations
  6. 3.6Synthetic data generation
  7. 3.7Trusted execution environments
  8. 3.8Re-identification risk
  9. 3.9European guidance on anonymisation
  10. 3.10Lab: differential privacy with OpenDP
  1. 4.1DAMA-DMBOK reference framework
  2. 4.2Data owners, custodians and data stewards
  3. 4.3Data policies and standards
  4. 4.4Data catalogue
  5. 4.5Data lineage
  6. 4.6Metadata management
  7. 4.7Data governance under ISO/IEC 38505
  8. 4.8Data governance maturity models
  9. 4.9Data mesh and federated governance
  10. 4.10Exercise: data governance operating model
  1. 5.1Data quality under ISO 8000
  2. 5.2ISO/IEC 25012 data quality model
  3. 5.3Data profiling
  4. 5.4Business rules and validation
  5. 5.5Master data management
  6. 5.6Deduplication and entity resolution
  7. 5.7Continuous quality monitoring
  8. 5.8Cost of poor data quality
  9. 5.9Remediation plans
  10. 5.10Lab: quality rules with Great Expectations
  1. 6.1Information classification
  2. 6.2Access control and least privilege
  3. 6.3Encryption at rest and in transit
  4. 6.4Data loss prevention
  5. 6.5ISO/IEC 27001 controls
  6. 6.6Data breach management
  7. 6.7Access logging and auditing
  8. 6.8Data security in the cloud
  9. 6.9Retention and secure deletion
  10. 6.10Case study: data classification and protection
  1. 7.1European data strategy
  2. 7.2Data Governance Act
  3. 7.3Data Act
  4. 7.4Common European data spaces
  5. 7.5Gaia-X and International Data Spaces
  6. 7.6Data altruism
  7. 7.7Data intermediation services
  8. 7.8Open data and re-use
  9. 7.9National access point for mobility data
  10. 7.10Workshop: joining a mobility data space
  1. 8.1Direct and indirect monetisation
  2. 8.2Designing data products
  3. 8.3Data as a service
  4. 8.4Data marketplaces
  5. 8.5Data pricing
  6. 8.6Valuing data as an asset
  7. 8.7Data-driven revenue models
  8. 8.8Cases in transport and automotive
  9. 8.9Legal and reputational risks
  10. 8.10Case study: data product built from telemetry
  1. 9.1Data platform architecture
  2. 9.2Data lakehouse architecture
  3. 9.3APIs for data distribution
  4. 9.4Data contracts between teams
  5. 9.5Data observability
  6. 9.6MLOps and models in production
  7. 9.7Cost of data in the cloud
  8. 9.8Scalability and performance
  9. 9.9Security in data distribution
  10. 9.10Lab: API for an aggregated data product
  1. 10.1Principles of data ethics
  2. 10.2Bias in data and models
  3. 10.3Responsible artificial intelligence
  4. 10.4The EU Artificial Intelligence Act
  5. 10.5Transparency towards users
  6. 10.6Surveillance and fundamental rights
  7. 10.7Data ethics committees
  8. 10.8Algorithmic impact assessment
  9. 10.9Customer trust and reputation
  10. 10.10Exercise: ethical assessment of a data use case
  1. 11.1Role of the Chief Data Officer
  2. 11.2Corporate data strategy
  3. 11.3Data-driven culture
  4. 11.4Data literacy
  5. 11.5Use case portfolio
  6. 11.6Return on data initiatives
  7. 11.7Governance and value indicators
  8. 11.8Budget and funding
  9. 11.9Organisational change management
  10. 11.10Case study: data strategy for a rail operator
  1. 12.1Selection of the organisation or data domain
  2. 12.2Privacy and governance diagnosis
  3. 12.3Data inventory and classification
  4. 12.4Design of the governance model
  5. 12.5Technical privacy measures
  6. 12.6Data product proposal
  7. 12.7Legal and ethical analysis
  8. 12.8Implementation and value plan
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
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 the intake, so the programme is compatible with work.

Each module combines theory, guided reading of the original regulations and standards, and applied exercises. The working software is Collibra, OneTrust, OpenDP, Great Expectations and Apache Atlas, in free, academic or evaluation versions. Exercises are built on real procedures: data protection impact assessment, anonymisation with differential privacy and design of a data product. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Regulation (EU) 2016/679 (GDPR), Spanish Organic Act 3/2018 (LOPDGDD), Regulation (EU) 2023/2854, Regulation (EU) 2022/868, ISO/IEC 27701:2019, ISO/IEC 27001:2022, ISO 8000, ISO/IEC 38505-1:2017.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the GDPR, the LOPDGDD and the Data Act applied to real cases, not as a theoretical annex.
Industry software:Collibra, OneTrust, OpenDP, Great Expectations and Apache Atlas, in free, academic or evaluation versions.
Master's Thesis with defence:A complete privacy, data governance and data product proposal for a real organisation or data domain, defended before a panel.
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.

Privacy and governance diagnosis
Select the organisation or data domain and diagnose its privacy and governance position.
Data inventory and classification
Build the data inventory and classify the data.
Governance model and privacy measures
Design the governance model and the technical privacy measures.
Data product and value plan
Propose a data product with its legal and ethical analysis and implementation plan.
Master's Thesis
Present the complete data governance project, defended before a panel.
Career opportunities

Where this takes you

Data protection officerData governance managerPrivacy engineerChief data officerData product managerData steward
Admissions & scholarships

Requirements

  • 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.

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FAQ

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, OneTrust, OpenDP, Great Expectations and Apache Atlas, 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 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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