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DRPS : Course Catalogue : School of Informatics : EPCC on-campus

Postgraduate Course: Fundamentals of Data Management (EPCC11005)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryBetter and more effective approaches to managing digital research data are becoming increasingly important in computational science and beyond. The scientific data sets that underpin research papers can now occupy many gigabytes of storage, and are increasingly complex and challenging to work with. This course introduces students to the ideas, methods and techniques of modern, digital data management.
Course description The course will cover:
- Why managing research data better matters, and why it's hard
- Data management planning: a required part of twenty first century research
- Data formats: structuring data and keeping them useful
- Relational and NoSQL databases
- Metadata: describing data and keeping them useful
- Publication and citation of research data
- Persistence, preservation and provenance of research data
- Licensing, copyright and access rights: some things researchers need to know
- Important distributed data processing tools and techniques, such as: Spark and MapReduce
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2024/25, Available to all students (SV1) Quota:  84
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Supervised Practical/Workshop/Studio Hours 11, Summative Assessment Hours 2, Revision Session Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 62 )
Assessment (Further Info) Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Additional Information (Assessment) Written Exam 70%
Coursework (Assessed practicals) 30%

Written examination comprised of 3 compulsory questions (equally weighted).

The coursework elements are comprised of assessed practicals spread throughout the Semester. These will be short quizzes taken following practical classes with each worth 10%.
Feedback Provided via practical class sessions, assessed practicals, and after the exam.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Fundamentals of Data Management2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Identify common data formats and understand applicable usage of these.
  2. Demonstrate both an understanding of data storage techniques and an ability to apply these techniques
  3. Explain and appreciate the importance of long-term data management
  4. Analyse important distributed data processing models
  5. Synthesise these concepts to address data management problems
Reading List
Made available via Learn/Leganto
Additional Information
Graduate Attributes and Skills - Solution Exploration, Evaluation and Prioritisation.
- Critical thinking
- Communication of complex ideas in accessible language
- Working in an interdisciplinary field
- Programming and Scripting
Special Arrangements There are limited spaces on this course.
KeywordsFDM,EPCC,Data Science,Data Management,Data Processing,Databases,NoSQL,HPCwDS,MapReduce,Spark,Data
Course organiserDr Christopher Wood
Tel: (0131 6)51 5330
Course secretaryMr James Richards
Tel: 90131 6)51 3578
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