What The Course Is About
Big data is not only about large files or fast processing. Real systems must deal with volume, velocity, variety, and veracity while remaining understandable, governable, and fit for use in production environments.
The 2026 version focuses on scalable and responsible big data infrastructures: data exchange, knowledge representation, stream-oriented architectures, workflow orchestration, and the trust and compliance constraints that increasingly shape data engineering.
Course History
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Until 2022-2023
Big Data Science
The earlier 6-credit course, then coded E018210, was taught in semester 2 by Dieter De Witte, with Pieter Colpaert and Erik Mannens as co-lecturers.
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2023-2024
Big Data Technology
The course changed to a 4-credit semester-1 course, E018240, with Dieter De Witte as lecturer-in-charge and Erik Mannens as co-lecturer.
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2024-2025
Big Data Technologies
The course continued as Big Data Technologies in the first semester.
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2025-2026
Big Data Tech / Science
Offered in both the MatStat program (BDS - 3 credits) and Computer Science Engineering (BDT - 4 credits)
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2026-2027
BDT in 2026
A 3-credit semester-1 course with Pieter Colpaert as lecturer-in-charge. The course has been fully redesigned.
Course Facts
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3 credits
Workload
The 2026 ECTS file lists 90 hours of study time.
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Semester 1
Timing
The course is offered in English in Ghent during the first semester.
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Lecturers
2026-2027
Pieter Colpaert, Beatriz Esteves and Julián Rojas.
Topics
- Foundations of big data: volume, velocity, variety, veracity, and architectural patterns
- Knowledge representation, interoperability, storage models, serializations, and Web APIs
- Veracity and trust: identifiers, identity, verifiable credentials, data spaces, ODRL, and DPV
- Velocity and streaming data: stream processing, publish-subscribe protocols, and event-driven architectures
- Compliance and governance, including intellectual property, privacy, and European data frameworks
- Variety and AI, unstructured data, scheduling, orchestration, workflows, and industry examples
What Students Learn
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Designing Data Architectures
Explain distributed storage and processing architectures and assess trade-offs in scalable systems.
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Building Interoperable Systems
Choose representation, storage, serialization, and Web API approaches for heterogeneous data-intensive use cases.
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Handling Trust And Compliance
Apply concepts such as digital identity, verifiable credentials, usage control, governance, and legal constraints.
Format And Assessment
The course combines lectures and practical sessions with industry examples and lab work. The 2026 ECTS file describes end-of-term and continuous assessment.
The exam is open-book and combines written work with oral discussion. The continuous assessment is based on lab assignments, possibly in groups.
Official Information
Use the official 2026 Ghent University ECTS file for the current programme, assessment, and enrolment context.
For historical context, the 2023 Big Data Technology ECTS file documents the 4-credit version, while the 2022 Big Data Science ECTS file documents the older 6-credit version taught by Dieter De Witte.