Course info

Data quality is related to the set of techniques able to guarantee the appropriateness a of a data set for the task at hand. The goal is to detect data errors, inconsistencies or delays that might negatively affect the output of processes (ranging from business processes to pure computational process). In particular, in a data-driven culture, it is important to feed data analytics applications with high quality input data in order to potentially increase the reliability and value of the obtained results.   

In the literature, several techniques and procedures to measure and improve data quality levels have been proposed. This course aims to: (i) provide an overview of the most effective assessment and improvement techniques, (ii) discuss the main data quality issues in data integration (iii) discuss the main data quality open issues in IoT and Big data analytics. 

Organizer:  Matteo Lissandrini

Lecturers:    prof. Cinzia Cappiello

ECTS:          2

Time:          22 and 23 May 2023 (09.00-12.00) and (13.00-16.00)

The course will take place at Selma Lagerløfs Vej 300, 9220 Aalborg

-  in room 0.2.90 on Monday  22/05

-  in room 0.2.13 on Tuesday 23/05

City:    Aalborg

Number of seats:  30

Deadline:              1 May 2023

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.