Ljiljana Brkić

Business process management systems selection guidelines: Theory and practice

Nowadays many business process management systems (BPMSs) are available on the market and it is quite difficult to select the appropriate one. This paper presents a set of criteria and proposes guidelines for BPMS selection. The proposal has been developed on the basis of literature overview and the feedback from practical experience in BPM projects. The results of this research are valuable for both academic and business community.

A Time-Constrained Algorithm for Integration Testing in a Data Warehouse Environment

A data warehouse should be tested for data quality on regular basis, preferably as a part of each ETL cycle. That way, a certain degree of confidence in the data warehouse reports can be achieved, and it is generally more likely to timely correct potential data errors. In this paper, we present an algorithm primarily intended for integration testing in the data warehouse environment, though more widely applicable. It is a generic, time-constrained, metadata driven algorithm that compares large database tables in order to attain the best global overview of the dataset’s differences in a given time frame. When there is not enough time available, the algorithm is capable of producing coarse, less precise estimates of all datasets differences, and if allowed enough time, the algorithm will pinpoint exact differences. This paper presents the algorithm in detail, presents algorithm evaluation on the real project’s data and TPC-H dataset, and comments on its usability. The tests show that algorithm outperforms the relational engine when the percentage of differences in the database is relatively small, which is typical for data warehouse ETL environments. DOI: http://dx.doi.org/10.5755/j01.itc.47.1.18171

Software supporting international student exchange program in Higher Education

International student exchange programs allow students to study in various countries and experience challenges in new academic environment. International student exchange processes are complex and accompanied with extensive administrative tasks involving many higher education institutions (HEI). These administrative processes can be facilitated with the help of an appropriate software. This paper presents a software designed for managing data required for various processes in student exchange programme. The software, allows the user to manage data about HEI, bilateral agreements signed between institutions in European Higher Education Area (EHEA), applications of the outgoing students for an annual tender and the outcome of the competition. It supports automatic procedures for student ranking considering their choices, achievements and propositions of the tender. The main outcome of the software is the ranking list of the students with associated outgoing HEI complied with the quotas agreed in bilateral agreements and students preferences.

Recommender system based on the analysis of publicly available data

A recommender system is a software system aimed to make recommendations. To be able to do that, recommender system feature several components, such as: data collection and processing, recommender model, recommendation post-processing and a user interface. Recommender systems apply one or the combination of few of the recommendation techniques. In this paper we present recommender system developed to provide users with recommendations in accordance with their interests in different domains. We deduce user interests based on his activities and posts in social network. Social network used as a source of information on user (Facebook) provides Open API allowing access to the information about the user collected on the social network. Thanks to this data we are overcoming the so-called “cold start” problem and building user profile. A recommender system is commonly associated with only one domain, while the recommender system described in this paper is able to generate recommendations from different domains (movies and music). In addition to recommendations related with the specific domain, our system is able to recommend the web articles (unstructured text), relevant to the user that may belong to more than one category of interest.

Delta view generation for incremental loading of large dimensions in a data warehouse

Incremental load is the preferred approach in efficient ETL processes. Fact tables are the ones who benefit the most from this approach, since they are large in terms of row count. For the sake of simplicity, dimension tables are often ignored and populated in a full reload manner. However, big dimensions (e.g. Client) can also have a significant impact on the ETL process and should also be considered for incremental load. Although they have much smaller cardinality than a typical fact table, it usually takes much more resources to calculate one dimension table row than to calculate one fact table row. Large dimension tables are based on multiple source tables, and it is not trivial to determine the changed records that should be considered for the incremental load because changes in any and all of underlying source tables must be considered. In this paper, we present an algorithm for the dimensions delta view generation. Delta view for a dimension encompasses all its source tables and produces a set of keys (e.g. ClientIds) that should be incrementally processed. We have employed this approach in a real world project and have noticed a significant reduction in the loading time of big dimensions.