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Master’s in Regulatory Data Governance Engineering

Online master's programme of 1,900 hours in regulatory data governance engineering. 12 modules covering data in regulated contexts, governance frameworks, data quality, metadata and lineage, data protection, European data regulation, information security, retention, data architectures, compliance reporting and governed AI, 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 data governance frameworks in regulated environments.

02

Ensure data quality and integrity.

03

Manage metadata, catalogues and lineage.

04

Comply with data protection legislation.

05

Interpret European data regulation.

06

Design data architectures for compliance.

07

Govern analytical and artificial intelligence models.

Profile

Who it's for

  • Data governance managers setting up governance models in regulated industries.
  • Regulatory data stewards responsible for type-approval and compliance data.
  • Data protection officers working with engineering and connected-product data.
  • Data architects designing platforms for regulatory evidence.
  • Data quality analysts profiling and monitoring critical data sets.
  • Information security managers applying ISO/IEC 27001 to engineering data.
  • Engineering or science graduates looking to move into regulated industries such as automotive.
Standards & tools

What you'll work with

  • Regulation (EU) 2016/679 (GDPR) (General Data Protection Regulation)
  • Regulation (EU) 2023/2854 (Data Act) (harmonised rules on fair access to and use of data)
  • ISO/IEC 27001 (information security management systems)
  • ISO 8000 (data quality)
  • ISO/IEC 38505-1 (governance of data)
  • Regulation (EU) 2022/868 (Data Governance Act)
  • Regulation (EU) 910/2014 (eIDAS) (electronic identification and trust services)
  • Directive (EU) 2022/2555 (NIS2) (high common level of cybersecurity across the EU)
  • Collibra
  • Alation
  • Informatica
  • Microsoft Purview
  • DataHub
Syllabus

12 modules · 1900 h

  1. 1.1Data as regulatory evidence
  2. 1.2Types of data: test, production, field and software
  3. 1.3Regulatory requirements on data
  4. 1.4ALCOA+ data integrity principles
  5. 1.5Data integrity in regulated sectors
  6. 1.6Risks of poor data
  7. 1.7Cases of data-related penalties
  8. 1.8Data culture in engineering
  9. 1.9Data roles in the organisation
  10. 1.10Case study: integrity audit of test data
  1. 2.1DAMA-DMBOK and its knowledge areas
  2. 2.2The DCAM maturity model
  3. 2.3ISO/IEC 38505 and data governance
  4. 2.4Policies, standards and procedures
  5. 2.5Governance committees
  6. 2.6Data owners and custodians
  7. 2.7Maturity models
  8. 2.8Governance indicators
  9. 2.9Phased implementation
  10. 2.10Workshop: designing a governance model
  1. 3.1Quality dimensions
  2. 3.2ISO 8000 and master data quality
  3. 3.3Data profiling
  4. 3.4Validation rules
  5. 3.5Cleansing and correction
  6. 3.6Continuous quality monitoring
  7. 3.7Quality of sensor data
  8. 3.8Quality of supplier data
  9. 3.9The cost of poor quality
  10. 3.10Lab: profiling a test data set
  1. 4.1Technical and business metadata
  2. 4.2Data catalogues
  3. 4.3End-to-end data lineage
  4. 4.4Business glossaries
  5. 4.5Data classification
  6. 4.6Metadata standards
  7. 4.7Lineage automation
  8. 4.8Integration with PLM and MES
  9. 4.9Search and discovery
  10. 4.10Practical exercise: lineage of a type-approval data item
  1. 5.1The General Data Protection Regulation
  2. 5.2Lawful bases for processing
  3. 5.3Data protection impact assessment (DPIA)
  4. 5.4Privacy by design
  5. 5.5Connected vehicle data
  6. 5.6Anonymisation and pseudonymisation
  7. 5.7International data transfers
  8. 5.8Data subject rights
  9. 5.9Security breaches
  10. 5.10Case study: DPIA for a telematics platform
  1. 6.1The EU Data Act
  2. 6.2The Data Governance Act
  3. 6.3European data spaces
  4. 6.4Access to vehicle data
  5. 6.5The Digital Services Act
  6. 6.6The AI Act and data
  7. 6.7The NIS2 cybersecurity directive
  8. 6.8The Cyber Resilience Act
  9. 6.9Interaction between regulations
  10. 6.10Workshop: Data Act obligations for a manufacturer
  1. 7.1ISO/IEC 27001 requirements
  2. 7.2ISO/IEC 27002 controls
  3. 7.3Access management
  4. 7.4Encryption and key management
  5. 7.5Cloud security
  6. 7.6TISAX in the automotive industry
  7. 7.7Cybersecurity of production data
  8. 7.8Incident management
  9. 7.9Business continuity
  10. 7.10Practical exercise: risk analysis to ISO/IEC 27005
  1. 8.1Retention requirements by sector
  2. 8.2Long-term archiving
  3. 8.3Preservation formats
  4. 8.4Digital chain of custody
  5. 8.5Electronic signatures and time stamps
  6. 8.6The eIDAS Regulation and trust services
  7. 8.7Evidence for authorities
  8. 8.8Secure data deletion
  9. 8.9Archive audits
  10. 8.10Case study: retention policy for type-approval data
  1. 9.1Data warehouse and data lake
  2. 9.2Data lakehouse architecture
  3. 9.3Data mesh and data products
  4. 9.4Integration of industrial data
  5. 9.5Master data management
  6. 9.6APIs and data sharing
  7. 9.7Real-time data
  8. 9.8Governance in the cloud
  9. 9.9Selecting an architecture
  10. 9.10Lab: regulatory data architecture
  1. 10.1Type-approval data
  2. 10.2Post-market surveillance data
  3. 10.3Substance and material data
  4. 10.4Emissions and sustainability data
  5. 10.5Cybersecurity and software data
  6. 10.6Automated reporting to authorities
  7. 10.7Report quality
  8. 10.8Report auditing
  9. 10.9Change management in reporting
  10. 10.10Workshop: automated regulatory reporting workflow
  1. 11.1Governance of analytical models
  2. 11.2Training data and bias
  3. 11.3Model explainability
  4. 11.4Model life-cycle management
  5. 11.5Data ethics
  6. 11.6Algorithm auditing
  7. 11.7The AI Act and governance
  8. 11.8Model documentation
  9. 11.9Emerging AI risks
  10. 11.10Practical exercise: governance sheet for a model
  1. 12.1Selection of an organisation or process
  2. 12.2Data maturity diagnosis
  3. 12.3Design of the governance model
  4. 12.4Quality and metadata plan
  5. 12.5Privacy and security compliance
  6. 12.6Proposed data architecture
  7. 12.7Implementation roadmap
  8. 12.8Conclusions and future work
  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 each intake, so the programme fits around your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Collibra, Alation, Informatica, Microsoft Purview and DataHub, in free, academic or evaluation versions. Testing is studied through real procedures for data integrity audits, data quality profiling and data protection impact assessments. Assessment is continuous, module by module, plus the final Master's Thesis.

Standards covered: Regulation (EU) 2016/679 (GDPR), Regulation (EU) 2023/2854 (Data Act), ISO/IEC 27001, ISO 8000, ISO/IEC 38505-1, Regulation (EU) 2022/868, Regulation (EU) 910/2014 (eIDAS), Directive (EU) 2022/2555 (NIS2).

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Regulation (EU) 2016/679 (GDPR), Regulation (EU) 2023/2854 (Data Act) and ISO/IEC 27001 applied to real cases, not as a theoretical annex.
Industry software:Collibra, Alation, Informatica, Microsoft Purview and DataHub, in free, academic or evaluation versions.
Master's Thesis with defence:a complete regulatory data governance model for an organisation or process, from maturity diagnosis to the implementation roadmap, 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.

Governance model design
Design a data governance model with roles, policies and committees.
Data quality profiling
Profile a test data set and define validation rules.
Type-approval data lineage
Trace the end-to-end lineage of a type-approval data item.
DPIA
Carry out a data protection impact assessment for a telematics platform.
Master's Thesis
A complete regulatory data governance model for an organisation or process, from maturity diagnosis to the implementation roadmap, defended before a panel.
Career opportunities

Where this takes you

Data governance managerRegulatory data stewardData protection officerData architectData quality analystInformation security manager
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, Alation, Informatica, Microsoft Purview and DataHub, 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, plus a computer able to run the programme software 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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