A Design Comparison: Data Warehouse Schema versus Conventional Relational Database Schema

ABSTRACT Initially, relational database is for both operational and decision support system, as the information society experiences exponential growth in the amount of data/information to be stored in a database, a line has been drown between transactional database and decision support database. Unlike traditional database, data warehouse aims to come from a number of preexisting databases (developed from relational schemas). This conceptual paper discusses traditional database schema design and that of data warehouse schema architectural designs strategies that could be a guiding principles for both learners and beginners in database management system. It has explored the stages in development processes of the two. Subject orientation, data integration, non-volatility of data, and time variations are the key issues under consideration that could differentiate between traditional databases and data warehouse schema designs. It has also presented Design Modelling Techniques as well as addressing logical data models for data warehouse schema and traditional relational database

Tra indicatori di convivenza e Sistema Informativo: un possibile ruolo dei processi di auditing nella “misura” del cambiamento organizzativo

In una visione sistemica delle organizzazioni, il concetto di misura assume un’importante rilevanza quale strumento per la verifica degli andamenti degli output organizzativi e la messa in atto di opportune azioni di intervento in risposta ad anomalie riscontrate nei valori delle variabili misurate. In tal modo si ottiene la chiusura di un anello di controreazione che tende a stabilizzare le uscite del sistema rispetto agli andamenti desiderati, mediante interventi di sviluppo nei processi organizzativi e nel sistema informativo a supporto degli stessi. Con il nostro contributo intendiamo proporre un nuovo metodo di misura del cambiamento organizzativo che si avvalga di metodologie e strumenti propri dei processi di auditing in uso nella gestione della sicurezza dei sistemi informativi. L’applicabilità di tale metodo richiede una preliminare definizione di appositi indicatori connessi alle variabili di convivenza organizzativa, la cui interpretazione potrà consentire un supporto alle decisioni coerente con il processo di cambiamento in atto.In una visione sistemica delle organizzazioni, il concetto di misura assume un’importante rilevanza quale strumento per la verifica degli andamenti degli output organizzativi e la messa in atto di opportune azioni di intervento in risposta ad anomalie riscontrate nei valori delle variabili misurate. In tal modo si ottiene la chiusura di un anello di controreazione che tende a stabilizzare le uscite del sistema rispetto agli andamenti desiderati, mediante interventi di sviluppo nei processi organizzativi e nel sistema informativo a supporto degli stessi. Con il nostro contributo intendiamo proporre un nuovo metodo di misura del cambiamento organizzativo che si avvalga di metodologie e strumenti propri dei processi di auditing in uso nella gestione della sicurezza dei sistemi informativi. L’applicabilità di tale metodo richiede una preliminare definizione di appositi indicatori connessi alle variabili di convivenza organizzativa, la cui interpretazione potrà consentire un supporto alle decisioni coerente con il processo di cambiamento in atto.Monograph's chapter

Transformasi Ontologi ke Model Dimensional

Data warehouse  adalah salah satu komponen penting untuk analisis bisnis yang efektif. Salah satu model pada data warehouse adalah dimensional model yang banyak digunakan karena performa permrosesan yang lebih cepat dari model lain. Dua faktor utama pada perancangan dimensional model adalah adalah sumber data dan kebutuhan bisnis.Salah satu sumber data yang banyak digunakan adalah ontologi karena mampu merepresentasikan data menjadi informasi yang koheren yang dapat dimasukkan ke dalam Data Warehouse. Dalam penelitian ini dihasilkan sebuah tools berbasis ontologi yang digunakan untuk secara otomatis mendapatkan dimensional model untuk data warehouse dari sumber data dan kebutuhan bisnis. Tahapan yang dilakukan mengidentifikasi semua informasi pada file ontology yang dimasukkan pengguna, kemudian daftar dimensi dan fact dihasilkan berdasarkan aturan perancangan dimensional model. Pembuatan fact tabel dan dimensi tabel dirancang berdasarkan rule perancangan dimensional model yang diperkenalkan oleh Kimball. Setelah tabel fact dan dimensidiidentifikasi, maka tabel fact dan dimensi tersebut diubah ke dalam bentuk kueri yang dapat dieksekusi pada MySQL. Penelitian ini berhasil menghasilkan dimensional model dari sumber data ontology.AbstractThe data warehouse is one of the essential components for effective business analysis. One of the models in the data warehouse is the dimensional model that is widely used because the processing performance is faster than other models. The two main factors in designing a dimensional model are data sources and business requirements. One of the most widely used data sources is ontology because it is able to represent data into coherent information that can be entered into the Data Warehouse. In this research, an ontology-based tool is produced which is used to automatically obtain dimensional models for the data warehouse from data sources and business needs. The step taken identifies all the information in the ontology file entered by the user, then a list of dimensions and facts is generated based on the design rules for the dimensional model. The creation of fact tables and dimension tables are designed based on the dimensional model design rules introduced by Kimball. After the fact and dimension tables are identified, the fact and dimension tables are converted into queries that can be executed in MySQL. This study succeeded in producing dimensional models from the ontology data source.

A Context Framework for Process-oriented Information Logistics

A continuously increasing data overload makes it a challenging task for knowledge-workers and decision-makers to quickly identify relevant information, i.e., information they need when executing business processes. To tackle this challenge, process-oriented information logistics is a promising approach. The basic idea is to provide the right process information, in the right format and quality, at the right place, at the right point in time, and to the right people. To achieve this, it becomes particularly important to take the work context of process participants into account. In fact, knowing and utilizing context information is a prerequisite to effectively provide relevant process information to process participants. This paper provides a sophisticated context framework for enabling context-awareness in process-oriented information logistics

Determining the Link and Rate Popularity of Enterprise Process Information

Today's knowledge workers are confronted with a high load of heterogeneous information making it difficult for them to identify the information relevant for performing their tasks. Particularly challenging is thereby the alignment of process-related information (process information for short), such as e-mails, office files, forms, checklists, guidelines, and best practices, with business processes. In previous work, we introduced the concept of process-oriented information logistics (POIL) to bridge this gap. POIL allows for the process-oriented and context-aware delivery of relevant process information to knowledge workers. So far, we have introduced concepts to integrate business processes with process information. A remaining challenge is to identify the process information relevant for a given process context. This paper tackles this challenge and extends our POIL approach with techniques and algorithms for identifying relevant process information. More specifically, we introduce two algorithms for determining the relevance of process information based on their link and rate popularity. We use a scenario from the automotive domain to demonstrate and validate the applicability of our approach

Process-oriented Information Logistics: Aligning Enterprise Information with Business Processes

Today, enterprises are confronted with a continuously increasing amount of data. Examples of such data include office files, e-mails, process descriptions, and data from process-aware information systems. This data overload makes it difficult for knowledge-workers to identify the information they need to perform their tasks in the best possible way. Particularly challenging is the alignment of process-related information with business processes. In fact, process-related information and business processes are usually managed separately. On the one hand, enterprise content management systems, shared drives, and Intranet portals are used for organizing information, on the other hand, process management technology is used to design and enact business processes. With process-oriented information logistics (POIL) this paper presents an approach for bridging this gap. POIL enables the process-oriented and context-aware delivery of process-related information to knowledge-workers. We also present a clinical use case and a proof-of-concept prototype to demonstrate the application and benefits of POIL

On Maintaining Semantic Networks: Challenges, Algorithms, Use Cases

PURPOSE: Knowledge workers are confronted with a massive load of data from heterogeneous sources, making it difficult for them to discover information relevant in the context of their daily tasks. As a particular challenge, enterprise information needs to be aligned with business processes. In previous work, the authors introduced the Semantic Network (SN) approach for bridging this gap, i.e., for discovering explicit relations between enterprise information and business processes. What has been neglected so far, however, is SN maintenance, which is required to keep an SN consistent, complete, and up-to-date. The paper tackles this issue and extends the SN approach with methods and algorithms for enabling SN maintenance. DESIGN/METHODOLOGY/APPROACH: The paper illustrates an approach for SN maintenance. Specifically, the authors show how an SN evolves over time, classify properties of objects and relations captured in an SN, and show how these properties can be maintained. An empirical evaluation, which is based on synthetic and real-world data, investigates the performance, scalability and practicability of the proposed algorithms. FINDINGS: The authors prove the feasibility of the introduced algorithms in terms of runtime performance with a proof-of-concept implementation. Further, a real-world case from the automotive domain confirms the applicability of the SN maintenance approach. ORIGINALITY/VALUE: As opposed to existing work, the presented approach allows for the automated and consistent maintenance of SNs. Furthermore, the applicability of the presented SN maintenance approach is validated in the context of a real-world scenario as well as two business cases

Specification of management views in information warehouse projects

With respect to the major role information warehouses play for the management an approach for specifying management views within the requirements specification phase is presented. Based on a framework relating development phases and abstraction layers the roles of documents within development processes are organised. The importance of using management views as metadata and parameters in later development phases is elaborated. Formally the transformation of management views into logical data mart schemes and report queries is shown by means of algorithms. Development phases are integrated based on meta level relationships. <br/