Diploma in Governance, Quality and Operational Data Catalog
Online postgraduate diploma of 800 hours in operational data governance, quality and cataloguing. 8 modules covering ISO 8000-61, ISO/IEC 25012:2008 and ISO/IEC 38505-1, with OpenMetadata, DataHub, Great Expectations and dbt, with an assigned technical tutor.
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
Define a data governance framework tailored to operations.
Assess data quality using standardised dimensions.
Automate data quality measurement and control.
Manage asset and material master data.
Implement catalogues and glossaries for operational data.
Apply security, privacy and compliance requirements.
Plan a sustainable governance programme.
Who it's for
- Industrial data stewards.
- Data governance managers.
- Data quality engineers.
- Data architects who need governance built into the platform.
- Master data analysts.
- Chief Data Officers in operations.
- Engineering or science graduates aiming to enter manufacturing.
What you'll work with
- ISO 8000-61 (data quality: process management)
- ISO/IEC 25012:2008 (data quality model)
- ISO/IEC 38505-1 (governance of data)
- ISO 14224:2016 (reliability and maintenance data)
- Regulation (EU) 2016/679 (GDPR)
- Regulation (EU) 2023/2854 (Data Act)
- ISO/IEC 11179 (metadata registries)
- OpenMetadata
- DataHub
- Great Expectations
- dbt
- Collibra
8 modules
1.1Concept and scope of data governance1.2The DAMA-DMBOK reference framework1.3Operational data versus master data1.4Roles: owner, custodian and data steward1.5Policies, standards and procedures1.6Centralised and federated governance models1.7Data mesh and data domains1.8Data governance maturity1.9The business case for governance1.10Workshop: RACI matrix for plant data
2.1Accuracy, completeness and consistency2.2Timeliness, validity and uniqueness2.3The ISO/IEC 25012 model2.4Quality of sensor data2.5Frozen values, jumps and drift2.6Quality of order and event data2.7Cost of poor quality2.8Data profiling2.9Quality thresholds and agreements2.10Practical: profiling historian data
3.1Declarative quality rules3.2Great Expectations and Soda3.3Pipeline testing with dbt3.4Anomaly detection in quality metrics3.5Quality dashboards3.6Data incident management3.7Fixing at source versus cleansing3.8Data quarantine3.9Quality indicators by domain3.10Lab: automatic validation with Great Expectations
4.1Asset and material master data4.2Equipment hierarchies according to ISO 142244.3Coding and taxonomies4.4Deduplication and matching4.5Golden record and sources of truth4.6Creation and change workflows4.7Synchronisation between ERP, CMMS and MES4.8ISO 8000 standards for master data4.9MDM tools on the market4.10Case study: cleansing the equipment master
5.1Types of metadata: technical, business and operational5.2Business glossary5.3Data catalogues: functions and architecture5.4DataHub, OpenMetadata and Amundsen5.5Data discovery and search5.6Classification and tagging5.7Dataset certification5.8Integrating plant metadata5.9User adoption of the catalogue5.10Lab: deploying OpenMetadata
6.1Information classification6.2Role-based and attribute-based access control6.3Personal data on the shop floor and the GDPR6.4Retention and deletion6.5Regulated data: GxP and ALCOA+ integrity6.6Sharing data with third parties6.7The EU Data Act6.8Access auditing6.9Policies as code6.10Case study: access policy for process data
7.1Data governance roadmap7.2Selecting pilot domains7.3Communication and training7.4Data steward community7.5Programme indicators7.6Change management7.7Integration with analytics projects7.8Funding and sustainability7.9Common mistakes in governance programmes7.10Workshop: 18-month implementation plan
8.1Maturity assessment8.2Domain selection8.3Roles and policies model8.4Quality rules and measurement8.5Master data model8.6Catalogue and glossary8.7Data governance implementation plan8.8Data governance monitoring indicators8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
Training is 100% online 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 OpenMetadata, DataHub, Great Expectations, dbt and Collibra, in free, academic or evaluation versions. Practical work is based on real procedures: profiling and measuring the quality of sensor data, deploying a catalogue with a business glossary, and cleansing and deduplicating master data. Assessment is continuous by module, plus the final project.
Standards covered: ISO 8000-61, ISO/IEC 25012:2008, ISO/IEC 38505-1, ISO 14224:2016, Regulation (EU) 2016/679 (GDPR), Regulation (EU) 2023/2854 (Data Act) and ISO/IEC 11179.
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
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's 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 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 OpenMetadata, DataHub, Great Expectations, dbt and Collibra, 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 computer able to run the 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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