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Kursusnavn (dansk):Big Data Management (Technical)  Help
Kursusnavn (engelsk):Big Data Management (Technical)  Help
Semester:Efterår 2018  Help
Udbydes, softwareudvikling og -teknologi (sdt)  Help
Omfang i ECTS:7,50  Help
Kursussprog:Engelsk  Help
Kursushjemmeside:  Help
Min. antal deltagere: Help
Forventet antal deltagere: Help
Maks. antal deltagere:90  Help
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. 
I øvrigt skal man opfylde IT-Universitetets generelle optagelseskrav. Help
Læringsmål:After the course students should be able to:

• Analyse and discuss the characteristics and societal issues of data exploration and analysis with large, fast-growing and diverse data sets.
• Reflect upon the relative merits of data management systems in the context of big data management.
• Design, conduct and report result of experiments with existing data management systems in the context of two specific data sets.
• Work constructively with domain specialists to fully understand a problem, as well as non-technical stakeholders to choose a model and operationalise results.  Help
Fagligt indhold:Big data offers opportunities and risks, requiring deep technical knowledge as well as critical skills to analyse the quality and impact of any approach or solution. Just a few years ago most data could be extracted, transferred and loaded into data warehouses where it could be analysed off-line. Traditional 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, possibly in real-time, of this data is a key challenge for many organizations, institutions and governments so that they can understand and adapt quickly to changing conditions. For example, a hospital could incorporate GPS data about the actual location of its ambulances and helicopters with data about the mission these vehicles are involved in, as well as emergency calls and current status in various emergency rooms in order to take decisions in real-time when faced with an emergency call (also in the face of large-scale disasters). At the same time, availability of low-cost sensing and network connectivity technologies drives myriad technical innovations affecting every aspect of life through data-based services.

There is no longer one approach that can fit all data management problems. For each problem, IT specialists have to work with non-technical stakeholders to fully understand the problem, and then decide on appropriate models and systems to handle the relevant data. Big data denotes the processes involved in making data from various data sources available for advanced analytics. In this course, we will address the technical issues that emerge in the course of collection, management, processing and analytics of large-scale data. We will introduce modern approaches to organizing and making sense of large, fast growing and diverse data sets. We will cover the principles of big data analysis and illustrate a hands-on approach to big data modelling and management. Students will be introduced to technical skills necessary for assessment of current approaches to big data management and analytics as well as critical theoretical tools for identification and discussion of potential pitfalls, obstacles and opportunities that working with data and analytics may bring up.  Help
Læringsaktiviteter:14 ugers undervisning bestående af forelæsninger og lejlighedsvise øvelser

The course will be based on lectures, exercises, and three practical projects with a range of different datasets and data management systems. Exercises will prepare students specifically to design and conduct experiments on an actual Big Data Platform. A major part of the course is the three practical projects, where teams of DIM students from the Critical Big Data Management Course work together with SDT students from the Technical Big Data Management Course. Students submit reports for each of the three projects throughout the course for feedback. The final versions of the project reports then form the portfolio submitted as part of the exam.  Help

Obligatoriske aktivititer: Help
Eksamensform og -beskrivelse:C: Skriftlige arbejder uden mundtlig eksamen., (7-scale, external exam)

The examination consists of written work. The exam includes a) an individually written exam report and b) a project portfolio consisting of the group reports for the three practical projects. The exam report is 10 pages. It is based on the lectures and the three practical projects. The students have 3 weeks to complete the exam report and submit it in Learn IT.   Help

Følgende personer underviser på kurset:
NavnStillingUndervisertypeIndsats (%)
Björn Thór Jónsson Lektor(ITU) Kursusansvarlig 50
Sebastian Baunsgaard Hjælpelærer(ITU) Hjælpelærer 0
Omar Shahbaz Khan Hjælpelærer(ITU) Hjælpelærer 0
Iman Elghandour Postdoc(ITU) Underviser 50