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The lecture deals with different Business Intelligence projects which were conducted in Croatia in the past 15 years.

Današnji zahtjevi s kojima se svijet susreće zahtijevaju brza i efikasna rješenja. Takva rješenja omogućavaju nerelacijske baze podataka koje su usmjerene na poslovne sustave ne bi li se rukovalo s nestrukturiranim i strukturiranim podacima i samim time povećala fleksibilnost i brzina razvoja. Problem koji se razmatra u radu je kako pospješiti komunikacijski proces između profesora i studenta/učenika u školskom sustavu koristeći nove tehnologije. Kroz rad će se demonstrirati izrada aplikacije te iznijeti prednosti i nedostaci NoSQL sustava i ključ- vrijednost baze podataka.

Process mining is a set of techniques which allow the automatic process analysis. Databases are places where all the data about process execution are stored. Data warehouses are databases of a special kind which collect and store data from different heterogeneous sources, including the data about processes. This article explores the existing literature about two related areas: process mining and data warehouses. The aim of this article is to research the methodologies used in previous researches, find out in which areas process mining combined with data warehousing is used, and what kind of tools researchers used to perform analysis.

Koncept NoSQL baza podataka obuhvaća niz tehnologija za alternativni (nerelacijski) pristup upravljanju podacima. Kao jedna od kategorija NoSQL baza podataka, grafovske baze podataka specifične su po prikazivanju podataka u obliku čvorova i veza u grafu nad kojima se prilikom izvršavanja upita izvršavaju različiti algoritmi iz teorije grafova. Društvene mreže najčešći su scenarij korištenja grafovskih baza podataka, budući da je osobe i veze između njih „najprirodnije“ prikazati kao čvorove i veze u grafovskim bazama podataka. U ovom ćemo radu napraviti pregled dosadašnjih istraživanja vezanih uz grafovske baze podataka općenito, sustave za upravljanje grafovskim bazama podataka i upitne jezike za interakciju s grafovskim bazama podataka, te ćemo posebnu pozornost obratiti na buduće trendove razvoja ove zanimljive i sve popularnije kategorije NoSQL baza podataka.

Databases enable users to store and retrieve data. However, uncontrolled data entry often results in having duplicate or incorrect data stored in the database, which makes it inconsistent. To prevent this, it is recommended to specify integrity constraints in the database. In this paper, the current possibilities in the field of integrity constraints, with special emphasis on graph databases as a relatively new category of NoSQL databases, are discussed. After giving an overview of the current situation regarding integrity constraints in mostly used graph database query languages, a successful implementation of UNIQUE integrity constraint in a Neo4j graph database is shown.

The issue of maintaining a database in a consistent state is becoming more challenging in situations where users are able to store all kind of data in the database without any control. Leaving this process unattended can lead to invalid and duplicate data in the database, which can directly affect the correctness of gathered data. In this paper, an overview of integrity constraints is given with the emphasis on graph databases, as well as the level of support provided by Neo4j, the most popular graph database management system (DBMS). A new integrity constraint has been implemented, which prevents users from entering data with values outside the permitted predefined set of values.

Even though relational databases have been (and still are) the most widely used database solutions for many years, there were other database solutions in use before the era of relational databases. One of those solutions were network databases with the underlying network model, whose characteristics will be presented in detail in this paper. The network model will be compared to the graph data model used by graph databases, the relatively new category of NoSQL databases with a growing share in the database market. The similarities and differences will be shown through the implementation of a simple database using network and graph data model.

Graph databases, which are presently classified as one of the most interesting database types, are being used on a daily basis. However, different systems are available and different languages are used to operate using graph databases. To summarize, a large number of languages hinders graph databases’ wider use. There also have been attempts to create universal SQL for graph databases in order to make things more standardized and intuitive to use. In this paper, we propose Gremlin By Example. This is a new language for graph databases that resembles Query By Example, which is a query language for relational databases. Because people are familiar with Query By Example, and Gremlin By Example looks almost the same, by using the similar interface people should be able to use graph databases without knowing the details of different graph query languages.

In this paper we discuss some aspects of the current state in the field of business information systems domain with an emphasis on the domain (context) of business rules, ranging from theoretical assumptions through modelling (in appropriate languages and tools) to use in business, with a focus on so called business rule paradox. It is well known that in many areas of human activity there is a gap between theory and practice and that this gap is mostly expressed either through inadequate theory or inadequate practice, where it is usually more often the case that the theory is more developed then the practice, or (in its own way, even though that may seem to be paradoxical) practice is more developed then theory. In the context of business processes and rules, their modelling and effective application to business practices, there is a paradox of the existence of highly developed theories which would enable quality practices, and a whole array of individual, very proficient practical solutions (implementations of business rules) on the one side, but no universal and generally accepted methodology for modelling bussines rules as a service for business processes and information systems to support them on the other side. The part of the problem is to be found in the inherent complexity of corresponding theories and tools which are necessary for modelling business rules and processes, but a part is to be found in inadequate (and due to systemic reasons incomplete) education of the main participants in that process, as well as a lack of communication between them. Business rules are undoubtedly one of the most important resources of any business subject. They are inherent to every business process, independent of its being conducted manually or with the support of information technology. In the first case they are dispersed in the multitude of laws, statutes, standards, business regulations, business and technical documentation and so on. In the second case, in the context of modern business practice, which is increasingly dependent on the support of information technology and is conducted in the virtual world of computers and computer nets ranging from local to global, like the World Wide Web, they are partially implemented in the processes through which business itself is pursued. Large companies and software manufacturers like Microsoft or IBM, conscious of a potentially vast market in the business rules segment, have developed or are currently developing large-scale development environments for business support, such as BizTalk Server (Microsoft) or WebSphere ILOG JRules (IBM), which, among other features, contain “modules” or even “languages” for modelling business rules. The importance of business rule modelling is additionally emphasized by the fact that a whole host of professional association (such as Business Rule Community (1), Object Management Group (2) - OMG, W3C (3), Eclipse (4), Protégé (5), IIBA, (6) …)is developing standards, specific programming languages, modelling languages (especially markup languages grouped around XML) and development environments for the requirements of the business rule and business process modelling as well as for the so-called accompanying technologies (semantic web, ontologies, Web services). This is equally true of the academic community involved in these research areas. Scientific research in the area of modelling business rules belongs within a wider context of the so-called semantic technologies. Next to modelling business rules, they encompass categories such as ontologies and semantic Web. These encompass a few narrower areas, such as developing logic formalisms (Descriptive logic, F-Logic, …) for the business rules modelling and the development of corresponding programming languages and environments (Protégé, Ergo Suite, Flora-2, DATALOG, …). A part of the research and development is done through the development of (the) corresponding standards under the auspices of the already mentioned associations such as W3C, OMG and Business Rules Group. The other part is done through the research of numerous research teams and individuals within the academic community and the research departments of large software companies, profit-oriented (IBM, Microsoft, Google (to a certain extent), Vulcan, Coherent Knowledge Systems, …) and non-profit (Eclipse Foundation, …). Nevertheless, despite all the things described above, concerning the development of theory, programming languages, tools and development environments, very few (the authors aren't familiar with one single case) cases of implementation of business rule systems (by the (Business Rule) Book) exist which fulfil the criteria established in a well-reasoned manner as irrefutably valid by Ronald Ross and his collaborators. We will proceed to elaborate why this is the case and to suggest a solution for the above mentioned paradox. In order to understand that paradox we will shortly describe the existing practice of business rule and business process modelling, some (not all) theoretical pillars necessary for their successful modelling and also present the main “players” in that “game”. Finally, we will “distribute” that set of theoretical knowledge and practical skills to these players according to their respective “jurisdictions” over business processes and business rules.

Nowadays, most enterprises still use relational databases to store their data. However, in a modern and dynamic environment the relationships connecting stored data are gaining more importance than the data itself. In this situation, graph databases have proven to be quite useful. Regardless of which database management system is being used to manage the company data, the issue of database query performance must be considered due to the increasing amount of data. Indexes are data structures, which can be used to improve database query performance. Due to their significant impact on the database performance, indexes have been developed and implemented both in relational and graph databases. In this paper, an overview of various indexing methods in the previously mentioned database categories has been made in order to detect their similarities and differences.

Modern business systems, especially those of middle and large size, generate a large amount of different data.This data is important for proper analysis, prediction of future trends or in other words for making various business decisions. The large amount of data that can be found in many different formats and in different technology can be stored on multiple locations that all refer to the same business system. Education about technology, such as various business organizations’business intelligence systems and data warehouses is important part of many higher education curriculums. However, since many business intelligence tools rely on various graphical representations of data they are not suitable for visually impaired students. In this paper a discussion about challenges that visually impaired students encounter when trying to learn about business intelligence is given along with directions for future research