IN9040 – Advanced Database Systems for Big Data
IN5040/IN9040 will not be taught Autumn 2021 due to sabbatical leave.
Exams in IN5040/IN9040 will not be held Autumn 2021 due to sabbatical leave.
Changes in the course due to coronavirus
Autumn 2020 and Spring 2021 the exams of most courses at the MN Faculty will be conducted as digital home exams or oral exams, using the normal grading scale. The semester page for your course will be updated with any changes in the form of examination.
Please note that there may be changes in the form of examination for some courses taught Spring 2021. We aim to bring both the course description and the semester page of all courses up to date with correct information by 1 February 2021.
In this course you´ll learn about new database technologies to handle Big Data: Data Stream Management Systems, Complex Event Processing, Distributed and Heterogeneous Database Systems, Data Warehousing and Data Mining, Web Data Management, and Cloud Data Management.
After you have successfully passed this course:
- You know the challenges, initiatives and history of the new database technologies to handle Big Data.
- You are able to explain the idea, application domains, concepts, and structure of Data Stream Management Systems, Complex Event Processing, Distributed and Heterogeneous Database Systems, Data Warehousing and Data Mining, Web Data Management, and Cloud Data Management.
- You understand the strength and weaknesses of the new database technologies to handle Big Data: how the specific problems can be solved, which new problems are introduced, and how these problems can be solved; which challenges are introduced by data centers.
- You have the ability to identify and discuss the strength and weaknesses in Big Data Management solutions. You can design and apply concepts for specific Big Data solutions to improve existing approaches.
- You have in-depth knowledge about the fundamentals and usage of Data Stream Management Systems and Complex Event Processing through the lectures and the mandatory exercise.
Admission to the course
Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.
A maximum of 60 students (IN5040 and IN9040 alltogether).
- Phd-studentes who have the course approved in their study plan
- Masterstudents in Informatics: programming and system architechture/Informatics: Programming and Networks who have the course approved in their study plan
- Masterstudenter in Informatics-programs who have the course approved in their study plan
- Masterstudents in Mat.Nat-faculty who have the course approved in their study plan
- Masterstudents in Informatics-programs
Recommended previous knowledge
- 10 credits overlap with IN5040 – Advanced Database Systems for Big Data.
- 10 credits overlap with INF5100 – Advanced database systems (continued).
- 10 credits overlap with INF9100.
3 hours lectures per week, emphasis is given on active involvement of the course participants in discussions and problem solving.
Mandatory presentation on selected topics in Big Data Management.
It is strongly recommended to attend the first lecture since it will be given important information.
The course includes mandatory assignments.
Oral or written exam (depending on the number of course attendees).
All mandatory assignments must be approved to be allowed to take the exam.
It will also be counted as one of your three attempts to sit the exam for this course, if you sit the exam for one of the following courses: IN5040 – Advanced Database Systems for Big Data, INF5100 – Advanced database systems (continued),INF9100
Grades are awarded on a pass/fail scale. Read more about the grading system.
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester. Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.