| Kursusnavn (dansk): | Big Data Management (Erstatter Building Database Systems) |
| Kursusnavn (engelsk): | Big Data Management (Replaces Building Database Systems) |
| Semester: | Efterår 2013 |
| Udbydes under: | cand.it., softwareudvikling og -teknologi (sdt) |
| Omfang i ECTS: | 7,50 |
| Kursussprog: | Engelsk |
| Kursushjemmeside: | https://learnit.itu.dk |
| Min. antal deltagere: | 12 |
| Forventet antal deltagere: | 60 |
| Maks. antal deltagere: | 60 |
| Formelle forudsætninger: | This course assumes basic computer science and programming background. It requires that the participants have taken the introductory programming courses and a data modeling course (Introduction to Database Design) for the Software Development and Technology study programme.
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Information about study structure
This course is part of the SDT specialization Databases. |
| Læringsmål: | After the course students should be able to:
- Analyze and discuss the characteristics of data exploration and analysis with large, fast-growing and diverse data sets.
- Analyze and discuss the complexity of the database system landscape
- Reflect upon which database model/system should be used for a given problem
- Reflect over the potential and especially the limitations of 3 specific database systems and their designs
- Design, conduct and report result of experiments related to data exploration and analysis in the context of two specific data sets.
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| Fagligt indhold: | “Big data” has become a term for a class of problems where the volume, complexity and velocity of the data challenge traditional approaches to data modeling, data management and data analysis. A few years back, production data was stored in relational forms and manipulated in the context of well-defined applications. This data could be extracted, transferred and loaded into data ware-houses where it could be analyzed off-line. Relational approaches to data management could fit all forms of problems.
Today, large volumes of data are being captured online, through sensors, outside the scope of traditional database systems. Making sense, in real-time, of this data is a key challenge for many organi-zations so that they can understand and adapt quickly to changing conditions. For example, an hospital should incorporate GPS data about the actual location of its ambulances and helicopters with da-ta about the mission these vehicles are involved in as well as emer-gency calls and current status in various emergency rooms to take decisions in real-time when faced with an emergency call (also in the face of large-scale disasters). There is no longer one approach that can fit all problems. For each problem, IT specialists have to decide on appropriate models and systems to handle the relevant data.
In this course, we will introduce modern approaches to organizing and making sense of large, fast growing and diverse data sets. We will propose a hands-on approach to data modeling and manage-ment. The course will be based on lectures and practical weekly ex-ercises with a range of different datasets and database systems.
Two datasets will be selected as the outset for data exploration and analysis with relational, graph and document database systems. |
| Læringsaktiviteter: | 14 ugers undervisning bestående af forelæsninger og øvelser We will rely on exercises throughout the lectures to favor student involvements and to prepare for the exam.
We will rely on labs.
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See the schedule here:
link to the time table
The schedule will be available shortly before the beginning of the term. |
| Obligatoriske aktivititer: | Der er ingen obligatoriske aktiviteter. Vær venlig KUN at ændre denne tekst når der er obligatoriske aktiviteter./
There are no mandatory activities. Please, change this text ONLY when there are mandatory activities. |
| Eksamensform og -beskrivelse: | X. experimental examination form (7-scale; external exam), 7-trins-skala, Ekstern censur Duration of exam: 4 hours
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| Litteratur udover forskningsartikler: | No Big Data textbook is available yet, so the study material is com-bined from multiple sources:
- “NoSQL Distilled – A Brief Guide to the Emerging World of Polyglot Persistence” of Pramod J. Sadalage og Martin Fowler, Addison-Wesley, 2012
“Data Mining – Concepts and Techniques”, 3rd ed. chapters 2-4, of Jia Han og Micheline Kamber
- Online Big Data tutorials (Microsoft, Google, Hadoop, Graph databases)
- Material specific to each database system
- Material specific to each dataset
Optional/supplementary:
- - “Seven Databases in Seven Weeks – A Guide to Modern Data-bases and the NoSQL Movement”, Eric Redmond og Jim R. Wilson, The Pragmatic Programmer, 2012.
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Kursusoversigt