ITF301415 Big Data - Processing and Analysis (Autumn 2015)

Compulsory course in:

• Bachelor in Computer Science
• Bachelor in Information Systems

Elective course in other study programmes.

Relational databases and large data volumes:

Relational algebra and query optimisation, other forms of optimisation, distributed databases and replicating, triggers and stored procedures. Different forms of connections between client and server. Alternatives to relational databases.

Data warehouse / business intelligence:

Various ways of building a data warehouse, the transformation process, data mining.

"Big data":

Massive data volumes, acquisition, storage, processing, visualisation. Legal and ethical aspects of big data.

Knowledge:

On completion of the course, the student has:

• in-depth knowledge about the relational model, relational database systems, and alternatives to relational databases
• knowledge about how large data volumes are managed efficiently in relational form
• knowledge about data warehouses/ business intelligence and 'big data'
• knowledge about how to find patterns in large data volumes, and how this can be used for example in business strategies, marketing, social sciences, natural sciences and other subjects

Skills:

On completion of the course, the student is capable of:

• handling large data volumes, structured in different ways and on different platforms (LAN, WAN, the cloud)
• setting up and operating a database system
• creating expressions in relational algebra and seeing the connection between this and optimisation
• creating simple stored procedures and triggers
• designing a data warehouse
• analysing large data volumes using different techniques
• working with different types of database systems

General Competence:

On completion of the course, the student:

• has good knowledge of how large data volumes can be structured, processed, analysed and presented, on different platforms
• has more knowledge about how to search for information in and become acquainted with new IT systems

Portfolio examination and written examination

The individual final grade is awarded on the basis of two partial exams. Students must pass each partial exam in order to pass the whole course.

Partial exam 1
Portfolio examination consisting of reports from four projects carried out in a group. The portfolio is assessed as a whole and one overall grade is awarded. The portfolio examination counts 49%. Individual grades are awarded.

Partial exam 2
Individual written examination lasting 3 hours that counts 51%. No support materials permitted.

Letter grading scale A?F.

In the case of resit and rescheduled examinations, each part of the examination may be retaken. In the case of resit and rescheduled examinations, the topic of the project assignments must be agreed with the course instructor.

This course is evaluated as follows:

• Mid-semester evaluation (optional)
• Final evaluation (compulsory)

The course instructor prepares a course report on the basis of student feedback and on his/her own experiences of the course. Course reports are discussed with the Committee for Study Quality at the Faculty of Computer Sciences.

Thomas M Connolly and Carolyn E Begg. Database Systems: A Practical Approach to Design, Implementation and Management - 6th Edition.

Distributed material and web-based resources - to be published on Fronter.