Diploma in Catalog and Operation of Data Products
Online postgraduate diploma of 800 hours in data product catalogues and operations, with 8 modules covering data products and catalogues, catalogue platforms, lineage and semantics, quality and operational reliability, access, security and compliance, platform operations and federated adoption and governance, with an assigned technical tutor.
Diploma in Catalog and Operation of Data Products — studying from the United Kingdom
Data science, artificial intelligence and simulation are central to engineering practice across the United Kingdom, with strong hubs in London, Cambridge, Oxford, Bristol and Edinburgh. Universities, research institutes such as the Alan Turing Institute and industrial users in aerospace, automotive, energy and finance demand skills in modelling, machine learning and computational analysis. Engineering simulation tools are widely used for design validation and digital twins. Organisations seek professionals who can turn large datasets into engineering decisions while meeting data protection and governance requirements.
Fees for the United Kingdom: £1,250 (Pound sterling), with instalments and employer sponsorship available.
Relevant bodies in the United Kingdom
Typical roles
Questions from the United Kingdom
Which UK bodies recognise data and AI qualifications?
In the UK, the British Computer Society (BCS), the Royal Statistical Society (RSS) and the Institute of Analytics are relevant professional bodies, and the IET covers many engineering-related AI and data areas. SEIUM's qualifications are private and not accredited by these bodies. Check directly with BCS or RSS whether your study would be considered towards their membership or certification.
Do UK employers in data and AI value private online qualifications?
UK employers in finance, retail, health, technology and public sector analytics typically assess candidates on technical skills, portfolio work and experience with real data. A private qualification may help demonstrate specialist learning, but its value depends on each employer's judgement. Publishing projects and showing practical results will usually matter most.
Can I study this online from the UK alongside work, and what English level is required?
Yes, the programmes are fully online and can be studied from anywhere in the UK without a student visa. Teaching is in English, so you need a solid working level of technical English. An assigned technical tutor will support you. Check the programme hours against your working commitments and ask about instalment payments or employer sponsorship.
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 data products with their ports, metadata and owners.
Implement catalogue platforms such as DataHub or OpenMetadata.
Capture column-level lineage and build business glossaries.
Publish quality indicators and service levels in the catalogue.
Design access and security policies that comply with regulations.
Operate a self-service platform with CI/CD and cost control.
Drive catalogue adoption through federated governance.
Who it's for
- Data product owners.
- Data platform engineers.
- Catalogue and metadata leads.
- Data stewards.
- Data governance architects.
- Data quality analysts.
- Engineering or science graduates aiming to enter banking and insurance.
What you'll work with
- ISO/IEC 11179 (metadata registries)
- W3C DCAT 3 (data catalogue vocabulary)
- Regulation (EU) 2016/679 – GDPR (General Data Protection Regulation)
- ISO 8000 (data quality)
- ISO/IEC 38505-1 (governance of data)
- Royal Decree 311/2022 – ENS (Spanish National Security Framework)
- Regulation (EU) 2022/868 – Data Governance Act (data sharing and intermediaries)
- DataHub
- OpenMetadata
- Unity Catalog
- dbt
- OpenLineage with Marquez
8 modules
1.1Operational definition of a data product1.2Input, output and control ports1.3Technical, business and operational metadata1.4Catalogue versus internal data marketplace1.5Discoverability and semantic search1.6Domain ownership and accountability1.7Data Product Descriptor Specification1.8Life cycle: onboarding, versioning and retirement1.9Catalogue maturity models1.10Workshop: data product specification in YAML
2.1DataHub: architecture and metadata model2.2OpenMetadata and connectors2.3Unity Catalog on Databricks2.4Microsoft Purview and Collibra2.5Automated metadata ingestion2.6Metadata APIs and events2.7Integration with BI tools2.8Platform selection criteria2.9Costs and licensing2.10Practical: deploying OpenMetadata with connectors
3.1Table-level and column-level lineage3.2OpenLineage and Marquez3.3Lineage from dbt and Spark3.4Business glossary and taxonomies3.5Lightweight ontologies and SKOS3.6Automatic classification of sensitive data3.7Sensitivity tags and propagation3.8Change impact analysis3.9The DCAT model for catalogues3.10Lab: column lineage in a dbt project
4.1Quality dimensions applied to products4.2Declarative quality rules4.3dbt and Soda tests4.4Freshness and volume monitors4.5Quality scores visible in the catalogue4.6Incidents and communication with consumers4.7Data product SLOs4.8Change management with semantic versioning4.9Orderly deprecation of versions4.10Case study: quality score published in the catalogue
5.1Access request and approval workflows5.2Role-based and attribute-based access control5.3Policy as code with OPA5.4Dynamic masking and row-level filtering5.5Record of processing activities5.6Data retention and deletion5.7Access auditing5.8Secure data sharing between domains5.9Classification under the ENS (Spanish National Security Framework)5.10Practical: attribute-based access policy
6.1Self-service platform teams6.2Product templates and scaffolding6.3CI/CD for data products6.4Infrastructure as code6.5FinOps and cost allocation per product6.6Platform observability6.7Support and request management6.8DORA metrics applied to data6.9Living documentation and onboarding6.10Workshop: product template with CI/CD
7.1Data communities of practice7.2Catalogue adoption metrics7.3Collaborative metadata curation7.4Incentives for domain owners7.5Federated governance and global standards7.6Interoperability between domains7.7Cultural change management7.8Maturity assessment7.9Evolution roadmap7.10Case study: catalogue adoption plan
8.1Diagnosis of the starting situation8.2Metadata model design8.3Tool selection and implementation8.4Onboarding pilot products8.5Published lineage and quality8.6Access policies8.7Operations and adoption plan8.8Catalogue success indicators8.9Report and presentation8.10Final project: final review with the tutor
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 it can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is DataHub, OpenMetadata, Unity Catalog, dbt and OpenLineage with Marquez, in free, academic or evaluation versions. Real procedures are studied: deploying a catalogue with automated metadata ingestion, publishing lineage and quality scores, and designing governed access workflows. Assessment is continuous by module plus the final integrative project.
Standards covered: ISO/IEC 11179, W3C DCAT 3, Regulation (EU) 2016/679 (GDPR), ISO 8000, ISO/IEC 38505-1, Royal Decree 311/2022 (ENS), Regulation (EU) 2022/868 (Data Governance Act).
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.
- An 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 DataHub, OpenMetadata, Unity Catalog, dbt and OpenLineage with Marquez, 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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